We investigated the effect of increased spring (April–May) dust aerosol over the Arabian Peninsula (AP) on the subseasonal- to-seasonal (S2S) variability of the Asian summer monsoon (ASM) using MERRA-2 re-analysis data (1980–2018). Result shows that abundant AP spring dust leads to more dust covering the AP and Pakistan northwestern India (PNWI) during May–June, causing a cooler land surface and a warmer lower and middle atmosphere with enhanced local atmospheric stabil- ity. However, the warmer atmosphere increases the meridional temperature gradient, boosting moisture transport from the Arabian Sea to PNWI, causing increased convective potential energy in PNWI region. As season advances, the accumulated convection potential energy eventually breaks through the local stability, via the elevated heat pump (EHP) effect, increas- ing precipitation over PNWI. In July and August, cloud radiation-circulation feedback further enhances the warming of the upper troposphere, strengthening precipitation in PNWI. Dynamical adjustments of large-scale circulations induced by the feedback strongly modulate ASM precipitation. Over southern and central China, precipitation is reduced, in conjunction with a contraction of South Asian High, and the development of an anomalous east-to-west oriented upper-level wavetrain in July. In August, the upper level wavetrain undergoes strong wave-mean flow interaction, culminating in the development of an anticyclonic center with drought conditions over northeast China, Korea and Japan. Over the Indian subcontinent, increased precipitation in PNWI plays an important role in initiating the EHP feedback leading to increased precipitation over the Indian subcontinent, and in modulating the jetstream-wave interaction in downstream East Asian regions in July–August

The Asian Tropopause Aerosol Layer (ATAL) has emerged over recent decades to play an increasingly prominent role in the upper troposphere and lower stratosphere above the Asian monsoon region. Although the effects of the ATAL on the surface and top-of-atmosphere radiation budget have been examined by several studies, the processes and effects by which the ATAL alters radiative transfer within the tropopause layer have been much less discussed. We have used a conditional composite approach to investigate aerosol mixing ratios and their impacts on radiative heating rates in the Asian monsoon tropopause layer in MERRA-2. We have subsampled based on the evolution of emission and data assimilation inputs to the MERRA-2 aerosol analysis to isolate the ATAL contribution and compare it to radiative heating signatures in the monsoon anticyclone region after volcanic eruptions. The results indicate that the ATAL impact on radiative heating rates in this region is on the order of 0.1 K/day, similar to that associated with ozone variability in MERRA-2 but weaker than cloud radiative effects at these altitudes. We have validated these results and tested their sensitivity to variations in the vertical structure and composition of ATAL aerosols using offline radiative transfer simulations. The idealized simulations produce similar but slightly stronger responses of radiative heating rates to the ATAL. Although the ATAL perturbations inferred from MERRA-2 are only about 10% of mean heating rates at these levels, their spatial distribution suggests potential implications for both isentropic and diabatic transport within the monsoon anticyclone, which should be examined in future work. Our results are limited by uncertainties in the composition and spatiotemporal variability of the ATAL, and reflect only the conditions in this layer as represented by MERRA-2, targeted observations and model simulations are needed to adequately constrain the uncertainties.

The precipitation variability is subject to impacts of both ocean and land surface condition changes. The influence of sea surface temperature (SST) anomalies in the tropical Indo-Pacific region on the Indochina Peninsular precipitation variability has been shown in previous studies. The present talk presents evidence for the role of land surface condition in the interannual variation of the early rainy season (May-June) precipitation over the Indochina Peninsula. A precursory signal is identified in surface air temperature (SAT) during March-April over central Asia after the late 1970s. The air temperature anomalies extend to middle troposphere and persist to early summer (May-June) and modulate the land-sea thermal contrast and lower-level and upper-level winds over the North Indian Ocean and thus affect the early rainy season precipitation over the Indochina Peninsula. The maintenance of SAT anomalies over central Asia is related to that of surface heat flux anomalies that in turn is attributed to the persisting atmospheric wind anomalies. The precursory signal is weak before the late 1970s due to the lack of persisting atmospheric wind anomalies. The interdecadal change in the persistence of central Asian SAT anomalies is associated with a difference in the distribution of the North Atlantic SST anomalies. After the late 1970s, the North Atlantic SST anomalies with a southwest-northeast distribution excite a wave train that extends from the North Atlantic to central Asia during May-June. Before the late 1970s, the wave train associated the North Atlantic SST anomalies with a south-north distribution is confined to the North Atlantic region. The role of the North Atlantic SST anomalies is illustrated using numerical model experiments.

Future change in summertime rainfall under a warmer climate will impact the lives of more than two-thirds of the world’s population. However, the future changes in the duration of the rainy season affected by regional characteristics are not yet entirely understood. We try to understand changes in the length of the rainy season as well as the amounts of the future summertime precipitation, and the related processes over regional monsoon domains using phase six of the Coupled Model Intercomparison Project archive. Projections reveal extensions of the rainy season over the most of monsoon domains, except over the American monsoon. Enhancing the precipitation in the future climate has various increasing rates depending on the subregional monsoon, and it is mainly affected by changes in thermodynamic factors. This study promotes awareness for the risk of unforeseen future situations by showing regional changes in precipitation according to future scenarios.

A reliable projection of future South Asian summer monsoon (SASM) benefits a large population in Asia. Using a 100-member ensemble of simulations by the Max Planck Institute Earth System Model (MPI-ESM) and a 50-member ensemble of simulations by the Canadian Earth System Model (CanESM2), we find that internal variability can overshadow the forced SASM rainfall trend, leading to large projection uncertainties for the next 15 to 30 years. We further identify that the Interdecadal Pacific Oscillation (IPO) is, in part, responsible for the uncertainties. Removing the IPO-related rainfall variations reduces the uncertainties in the near-term projection of the SASM rainfall by 13 to 15% and 26 to 30% in the MPI-ESM and CanESM2 ensembles, respectively. Our results demonstrate that the uncertainties in near-term projections of the SASM rainfall can be reduced by improving prediction of near-future IPO and other internal modes of climate variability.

Linkages between the variability of the Antarctic Sea Ice Extent (AnSIE) and the tropical climate has been extensively investigated. The study examines the interannual relationship between the variability of sea ice extent in the Indian Ocean (SIEIO) sector (20º–90ºE) and Indian summer monsoon rainfall (ISMR) under the influence of the Mascarene High (MH). SIEIO in high (HIP) and low (LIP) ice phase years during April-May-June (AMJ) appeared to have a significant correlation to ISMR in the Peninsula India region during June-July-August-September (JJAS), with correlation coefficients of 0.51 and 0.71, respectively. Composites of mean sea level pressure (MSLP), 500 hPa geopotential height, and 850 hPa wind anomalies during HIP and LIP also showed that there was a relationship between the SIEIO and the MH, revealing that HIP and LIP correspond respectively to the strengthening and weakening of the MH as well as increases/decreases in ISMR. During the respective HIP and LIP years, positive and negative MSLP anomalies were found respectively, particularly over the MH region associated with the eastwards and westwards shifts of its center from the normal locations. Similar features were also observed at 500 hPa geopotential height anomalies. In addition, 850 hPa wind flow illustrated strong anti-cyclonic and cyclonic anomalies in the MH region, which lead to corresponding strong and weak southwesterlies and thus respective positive and negative ISMR anomalies. Hence, a positive MH anomaly was associated with more ISMR.

The summer monsoon 2020 (June through September 2020) has been very erratic with episodes of heavy and devastating rains, landslides, catastrophic winds over South Asia (India, Pakistan, Nepal, Bangladesh), over East Asia (China, Korea, and Japan), and Southeast Asia (Singapore, Thailand, Vietnam, Laos, Cambodia, Philippines, Indonesia). The Korean Peninsula has experienced back-to-back severe typhoons during the 2020 monsoon period. Post the monsoon period the South China Sea / the Philippines Sea experienced super typhoons. China recorded a Dam burst. The withdrawal of the summer monsoon over India was delayed by more than a month. In fact India has experienced two consecutive excess monsoons 2019 and 2020. Monsoon season over South Korea has been the longest during 2020 season. Even the river Nile reached its highest level for more than a century due to torrential rains. Could the lockdown activities initiated to control the COVID-19 spread a possible cause for these major episodes?   The lockdown activities resulted in the practical standstill of the Travel Industry (Air, Rail, and Road) and the Construction industry. Even shopping malls and restaurants were closed, vehicle and human movements were restricted. These activities may have resulted in a considerable decrease in air pollutants – dust and aerosols. Reduced use of diesel and petrol may have also resulted in reduced CO2 emissions. Recent studies on the variation of air quality have documented a considerable reduction in air pollutants over East Asia as well as South Asia. It has been well documented that dust particles, aerosols can modulate the atmospheric circulation and precipitation distribution through alteration of the solar and terrestrial radiation.  Details of these episodes over the Asian domain as well over other parts of globe are planned to be discussed at the Virtual AOGS21 meeting in Singapore      

During autumn season, typhoons located far away from Japan sometimes cause large amounts of precipitation in Japan. The mechanism of remote precipitation is not clearly understood and only a few case studies have been conducted in Japan. A phenomenon like remote precipitation over North American continent is called Predecessor Rain Event (PRE), and many cases have been conducted. However, remote precipitation occurs mainly over the sea, while PRE occurs over land, so the environmental fields are quite different, and not all cases in Japan can be explained by the characteristics of PRE. In this study, we extracted and statistically analyzed the cases which remote precipitation occurred and didn’t occur when typhoons were approaching Japan in September for 40 years from 1980 to 2019. The characteristics of remote precipitation are as follows: the distribution of typhoons center at the time of occurrence is widely distributed from east to west between 120E and 150E, and the proportion of typhoons causing remote precipitation in September is about 24%. In more than 90% of the cases, remote precipitation tends to occur in the north to northeast direction of the typhoon. In most of the cases, the path of the typhoons was northward or approaching while recurving to Japan. The composite analysis of remote precipitation showed that the extending change of the subtropical high was weakening tendency from day-2 to day0. The positional relationship between the 200hPa isotach and the precipitation area showed that the precipitation area is located to the right of the jet streak entrance, like the PRE. On the other hand, in the cases of not remote precipitation, the subtropical high extended westward from day-2 to day0, which is opposite to remote precipitation. 

Typhoon Haiyan crossed the Philippines on November 8, 2013. It is estimated to be the lowest pressure ever recorded, and one of the largest tropical cyclones to hit there in recent years (Hoarau et al., 2017). The typhoon caused economic damage amounted to about US$2 billion, with the loss of at least 6,300 lives, 28,689 injured and 1,061 missing. The devastated area seemed to be suffered by the storm surge rather than the winds. Particularly, the interaction between the surface winds and the funnel-shaped coast along San Pedro Bay caused a storm surge of 6m in Tacloban (Galvin et al., 2014). As for this disaster, we analyzed the cloud properties of typhoon Haiyan using thermal infrared imagery of MTSAT-1R, i.e. IR1<10.3-11.3µm>, IR2<11.5-12.5µm>, IR3<6.2-7.3µm> and IR4<3.3-4.2µm, hourly from 1830UTC on November 3, 2013 to 0430UTC on November 11, 2013. The brightness temperature difference (BTD) among the four infrared bands, i.e. SPL<IR1-IR2>, DIW<IR1-IR3>, DIN<IR4-IR1>, were also analyzed. The area of analyses was defined within the radius of 1,600km from the center of typhoon Haiyan, and the time variations of the brightness temperature and BTD were investigated. Then the center position was obtained by interpolating the Typhoon Best Track Data, prepared every six-hour by Japan Meteorological Agency. The results revealed that the clouds which made up Haiyan were developing before landfall in the Philippines. The IR1 images showed that the cloud top temperature started to decrease after the afternoon of November 6. At the same time, the water vapor content within Haiyan increased according to IR3 images. In addition, the area of the brightness temperature differences between IR1 and IR3 to be lower than the threshold indicating cumulonimbus (typically 1.5 degrees) enlarged during the same period, suggesting the extraordinary intensity of typhoon Haiyan before hitting Philippines. 

Korea AirForce (KAF) has been retaining the numerical weather prediction model to forecast the daily weather conditions and to produce customized disaster information for aiding the military operation early and for minimizing the damage from the severe weather conditions. Along with the development of KAF’s numerical weather prediction models and the increasing number of computational resources, the need for the study to develop the operational numerical model to make it for the better prediction to the severe/local weather conditions that occurred in a short time was increased. Thus, the numerical weather prediction model for typhoon forecasting was newly developed based on the KAF's operational high-resolution regional model (KAF-WRF) to improve its performance of the original typhoon forecast model (KAF-TWRF) through the research service project in 2019. The newly developed model for typhoon forecasting (KAF-NTWRF) is consisted of three domains with 12km (601x451), 4km (301x301), and 1.33km (301x301) horizontal resolutions (grid points), respectively. We used the two-way moving nesting technique for domain 2 and 3 to resolve the inner core structure of typhoons realistically. To compare the sensitivity of physics settings to typhoon forecasting and their dissimilar reaction to the synoptic-scale weather phenomena, we selected three cumulus parameterization schemes (CPS) of Kain-Fritsch (KF), Betts-Miller-Janjic (BMJ), modified Tiedtke (TDK), and also three microphysics schemes (MPS) of WRF-single-moment-microphysics class 3 (WSM3), WRF-single-moment-microphysics class 6 (WSM6), Predicted Particle Properties (P3). We selected three TCs that recently affected South Korea and suffered rapid intensification while they moved to the mid-latitudes. The results show that there was a significant difference in simulated typhoon intensity and track performances depending on the physics schemes. Generally, the typhoon forecast skills were improved in sensitivity experiments with KF for CPS and P3 or WSM6 for MPS than others, which related to the better performances in the typhoon intensification process. 

We conducted an ensemble simulation with 1000 members on the Supercomputer Fugaku by using a nonhydrostatic icosahedral atmospheric model (NICAM) with a 14-km mesh, which was targeted to Typhoon Faxai (2019). Ensemble members started from different initial dates from 26 August 2019 to 4 September (10 days). NICAM-LETKF JAXA Research Analysis (NEXRA) was used as the initial atmospheric condition of the ensemble experiment. The NEXRA provided 100 perturbed atmospheric conditions for each initial date. The total number of ensemble members was 1000 in this study. The sea surface temperature was calculated by a slab ocean model, which was nudged to NOAA OI SST V2.1. The ensemble simulations ran for about 30 days. As a Faxai-like typhoon in an ensemble member, we regarded a tropical cyclone that met the following two conditions. 1) The tropical cyclone must pass over an area within 10 degrees of the Faxai genesis location (156.7E, 18.6N) and within 5 days of the Faxai genesis time (18UTC 4 Sep. 2019). 2) The tropical cyclone must pass an area within 10 degrees from a location (139.7E, 35.3N) within 5 days before or after 18UTC 8 Sep. 2019. Fewer number of ensemble members with the short lead time reproduced the Faxai-like typhoon than that of members with the long lead time. This is a possible reason why the short lead time is insufficient for a vortex being intensified, which may become a typhoon. As for tracks of the Faxai-like typhoon, these tracks differed between members of which even experiments started from the same initial date. The variations were more prominent in the long lead time experiments than those of the short lead time experiments. We will investigate a reason why the genesis and track of the Faxai-like typhoon substantially differ between the members.

This study develops a seasonal prediction model based on the statistical correlation between East Asia (EA) tropical cyclone (TC) landfall and atmospheric circulation, and its predictability is verified. The developed model is called statistical-dynamical seasonal typhoon forecast model (SDTFM) and uses the atmospheric circulation predicted by a coupled general circulation model as a predictor. A total of 40 ensemble members produced through different data assimilation and time-lag methods introduced as a way to reduce the initial condition error and model uncertainty enabled the development of the new SDTFM. According to the results, the SDTFM developed in this study shows a significant predictability in TC landfall prediction, when using the month of May for the initial conditions for the entire East Asia (EEA) and Northern East Asia (NEA), including the Korean Peninsula and Japan. Also, for Middle East Asia (MEA), including Taiwan, Fujian, Zhejiang, Jiangsu, and Shanghai, and Southern East Asia (SEA), which includes the south of China, the Philippines, and Vietnam, predictions using February for the initial conditions are better. The annual variability of EA TCs that make landfall is significantly predicted at the 99% confidence level, except for SEA, where the results are still significant at the 95% confidence level, even after cross-validation. The reason for the relatively low predictability in SEA seems to be a lack of outstanding steering flow in the region.
Acknowledgement
This work was carried out with the support of Cooperative Research Program for Agriculture Science and Technology Development (Project No. PJ01475503)" Rural Development Administration, Republic of Korea.

Understanding the impact of transit-oriented development (TOD) on the urban thermal environment is essential to guide the effective urban design at the neighborhood scale. TOD has a direct impact on urban mobility, lifestyle thus modifying the thermal environment. However, the level of the impact is unknown which requires additional investigation. This study numerically assesses the impact of urban development along with the Tsukuba Express (TX) railway, Tokyo, Japan on the change in thermal environment and human comfort. The TX is selected because the railway connects the high, mid-urban and suburban areas in-around the Tokyo Metropolitan region. Thus, the impact of TX on the urban environment could be evaluated separately for each type of urban area. The Weather Research and Forecasting (WRF) model with a 250-m horizontal resolution is used to simulate the area along the entire railway line including the three representative stations from 05 to 08 of August. The study uses two simulation cases: 2005 and 2015, before and after the construction of the TX, respectively. First, the results from the control simulation were verified against observations. The WRF model reproduced well the diurnal temperature variation in 2005 and 2015 along the TX railway. The mean model bias is from -0.3 C to 0.1 ºC in 2005 and 2015. Second, the impact of urbanization on the surface air temperature distribution along the TX railways is evaluated. The results show that the most significant temperature increase (2.3ºC) is simulated in Kenkyu-gakuen station between Cases 2005 and 2015 at 1900 JST. In this area, after the development of the TX railway, the anthropogenic heat release from buildings and traffic rapidly increase by around 80 W m^2, and the land-use cover changes from non-urban (Case 2005) to urban (Case 2015) by more than 80%.

The Kingdom of Saudi Arabia is characterized by a hot and arid desert climate. Occasionally, however, extreme precipitation has led to flooding events that caused extensive damage in terms of human life and infrastructure. The 25 November 2009 and 30 December 2010 flash floods in the city Jeddah have for instance caused heavy damages in urban areas. Mesoscale convective systems associated with strong moisture convergence ahead of an upper-level trough that merge with the Red Sea Trough are the major initial features triggering the intense rain events. This study investigates the effect of incorporating an urban canopy model and urban land cover within the Jeddah simulating severe weather events with the Weather Research and Forecasting model (WRF) at a convective-permitting scale (1.5 km grid spacing). Using 150 most heavy rain events (99th percentile) over 40 years (1980-2019) to setup an atmospheric climatology, we perform 3 experiments varying land surface conditions: (1) pre-settlement land surface (PRESET), (2) Low-density residential urban surface, 20 W/m² anthropogenic heating (LU.1985), and (3) High-density residential urban surface, 70 W/m² anthropogenic heating (LU.2018). Results show that LU.1985 and LU.2018 produces 5% and 18% more rainfall compared to PRESET, respectively. Tripling the urban surface area combined with higher population density may cause about threefold rise in rainfall. The results of this study have important implications on surface hydroclimatology and urban flooding. Climatologically, expanding the urban area and increasing energy usage will intensify rainfall from extreme events over the city of Jeddah, Saudi Arabia.

Cities, home to more than half of the human population, are becoming increasingly vulnerable to extreme rainfall occurrences caused by global warming and urbanization. Understanding future changes in heavy rainfall patterns is essential to derive effective urban design to save human life and maintain sustainable development. However, projecting city-scale extreme rainfall is challenging because coarse-resolution global climate models (GCMs) not adequate to represent the localized processes of urban precipitation as well as the interactions between urban areas and other mesoscale mechanisms such as sea-land and mountain-valley breezes explicitly. This study investigates the future change in extreme precipitation patterns over Tokyo, Japan in response to the warming climate caused by greenhouse gas emissions. The convection-permitting Weather Research and Forecast (WRF) simulations are employed for dynamically downscaling the future August rainfall climate up to the 2050s and 2090s from CMIP5 GCMs outcomes with two emission scenarios RCP4.5 and 8.5 considered. The pseudo-global warming (PGW) approach is used to generate future initial and boundary conditions to force the WRF by adding climate anomalies obtained from GCMs ensemble mean in the future to the present climate in the reanalysis data ERA-Interim. The response of short-term rainfall occurrences and its extremes to the future warming climate is analyzed to answer two questions: is there a robust signal of global warming on the change in extreme localized rainfall at the scale of the city; how will urban-induced modification in extreme rainfall patterns change in the future warming climate. The physical mechanisms behind such changes are also discussed here.

This study presents the first results to project the future change in extreme convection rainfall in a tropical large city such as Singapore. The convection-permitting WRF model is employed for dynamical downscaling the future change in rainfall considering 2050s and 2090s from the ensemble mean of CMIP5 GCMs outcomes with two scenarios RCP4.5 and RCP8.5. Pseudo Global Warming (PGW) approach is used for creating initial and boundary atmosphere conditions to force the WRF. The response of extreme rainfall occurrences in terms of both frequency and intensity are analyzed to answer two critical questions: (i) is there a robust signature of global warming on localized heavy rain at a city-scale; (ii) how will the urban effect on future rainfall change when background climate becomes warmer?  The physical mechanisms behind these changes are also analyzed here. This study adds value to the ongoing discussion about urban extreme precipitation, focusing on how it will change in future. The study will benefit urban planners to prepare appropriate plans to handle the challenge caused by global climate change. 

Study of shallow precipitating system remains a critical source of uncertainty in satellite based remote sensing, especially in regions of complex mountain terrain region. To solve this problem, we studied the vertical structure of shallow clouds and precipitation using the unique recent in-situ observations data sets from Braemore (8.75°N, 77.08°E), mid altitude region of the Western Ghats (WG) over the Indian Peninsula during the period 1 June 2019 to September 2019. The observed precipitation systems are classified into four categories: shallow-convective, shallow, stratiform and mixed convective-stratiform based on by vertical profile of radar reflectivity (Z) at and above the melting level from Micro rain radar and rain rate (R) from Disdrometer. The shallow precipitation is identified if the vertical extention of radar reflectivity is below the melting layer (below 4 km). From the rain rate analysis, it is found that the shallow convective system with low cloud base height has crucial role in the rain occurrence frequency over Braemore compared to other precipitating systems. The shallow-precipitation raindrop size distributions (DSDs) have small drop mass-weighted diameter (Dm) compared to other precipitating system. The averaged vertical profile of precipitable liquid water content shows that liquid water content (LWC) gradually increases with height and reach its peak value at 1.8 km then it is decreases with height. Minimum LWC value 0.1 gm^-3 observed at 4km and maximum LWC value 1.5 gm^-3 observed at 1.8 km. systematic and comprehensive study of characteristics of Shallow clouds and precipitation over a region is important to improve the understanding on rain microphysics and rainfall estimation from in-situ observations. 

Information about the raindrop size distribution (RSD) is vital to comprehend the precipitation microphysics, improve the rainfall estimation algorithms, and appraise the rainfall erosivity. Previous research has revealed that the RSD exhibits diversity with geographical location and weather type, which perpetrates to assess the region and weather-specific RSDs. Based on long-term (2004 to 2016) disdrometer measurements in north Taiwan, this study pursued to demonstrate the RSD aspects of summer seasons that were bifurcated into two weather conditions, namely typhoon (TY) and non-typhoon (NTY) rainfall. The results show a higher concentration of small drops and a lower concentration of big-size drops in TY compared to NTY rainfall, and this behavior persisted even after characterizing the RSDs into different rainfall rate classes. RSDs expressed in gamma parameters show higher mass-weighted mean diameter (D_m) and lower normalized intercept parameter (N_w) values in NTY than TY rainfall. Forbye, sorting of these two weather conditions (TY and NTY rainfall) into stratiform and convective regimes did reveal a large D_m in NTY than the TY rainfall. The RSD empirical relations used in the valuation of rainfall rate (Z –R, D_m–R, and N_w–R) and rainfall kinetic energy (KE–R, and KE–D_m) were enumerated for TY and NTY rainfall, and they exhibited profound diversity between these two weather conditions. Attributions of RSD variability between the TY and NTY rainfall to the thermo-dynamical and microphysical processes are elucidated with the aid of reanalysis, remote-sensing, and ground-based datasets. 

In the past few decades, extremely severe rainfall events have become more frequent and intense. Most of them are due to the afternoon thunderstorms in summer. Afternoon thunderstorm causes floods and landslides, which not only hurts the sociality of humans, but also the biosphere. Hence, the most important topic is to understand the detail of rainfall changes in the future.In this study, WRF model will be used to simulate the long-term projection of precipitation. First, we divide the 21^st Century into four parts, which are 2011-2015, 2046-2050, 2071-2075 and 2096-2100. By using CMIP5 under RCP8.5 scenario, a standard of changes of the weather conditions, we utilize GFDL model’s results as WRF input. The results show that the intensity of the afternoon thunderstorm in Taipei will increase. There are five main reasons that cause changes in afternoon thunderstorm: (1) Stronger southwesterly, (2) stronger sea breeze from Tamsui River, (3) stronger convergence in the daytime in Taipei basin, (4) higher mixing ratio at 850hPa, (5) higher equivalent potential temperature from surface to 500hPa. The difference between the present and the future will become larger as time approaches the end of the 21^st century. Furthermore, the strongest 10% afternoon thunderstorm cases have been selected. After rearranging all the cases sorted by rainfall amount, we find out that the median will increase by 25% and the rainfall of the most extreme case will double. The extreme afternoon thunderstorm rainfall will become more intense in the future. The change in dynamic conditions, thermal conditions, and water vapor can lead to the intensity change of the afternoon thunderstorms over Taipei basin in the future. 

From the time series of Climate Forecast System Reanalysis (CFSR), rain gauge data, and case studies, two widespread heavy rainfall (> 80 mm day^-1) periods over Taiwan during the South China Sea Two Island Monsoon Experiment (SCSTIMX) (1 to 4 June and 14 to 18 June 2017) are found to be closely related to the large moisture transport within the marine boundary layer (MBL) from the northern South China Sea [integrated vapor transport (IVT) between surface and 900-hPa level > 220 kg m^-1 s^-1] to the Taiwan area. With most of the moisture confined within the boundary layer, the moisture transport to the Taiwan area mainly occurs in the marine boundary layer jet (MBLJ). For both periods, the synoptic system-related low-level jet (SLLJ) coexists with the MBLJ, which is a subsynoptic feature. The MBLJ develops and intensifies when the mei-yu trough over southern China deepens and/or the western Pacific subtropical high strengthens and extends westward. With significant upstream moisture transport within the MBL (IVT ~300 - 315 kg m^-1 s^-1), extreme torrential rain (> 500 mm day^-1) occurs over Taiwan during 2 to 3 June of the first widespread heavy rainfall period. During the second widespread heavy rainfall period, there are two sub-periods of MBLJs and rainfall peaks (> 300 mm day^-1) on 14 and 17 June with lower moisture transport by MBLJs (IVT ~220 - 280 kg m^-1 s^-1) than during the first heavy rainfall period. For both periods, the moisture-laden MBLJs lifted by terrain and/or mei-yu jet/front systems produce heavy rainfall. The moisture transport within the MBL from the northern South China Sea to Taiwan provides a useful guide to predict heavy rainfall over Taiwan.

In summer 2020, South Korea experienced record-breaking rainfall. There were 11 consecutive heavy rainfall events (HREs) for 48 days from 29 June to 15 August. These HREs had two distinct synoptic structures depending on the occurrence periods. All HREs in 29 June–27 July (P1) were triggered by extratropical cyclones, while those in 28 July–15 August (P2) were mainly caused by monsoon rainband over the Korean Peninsula. Their transition was quite rapid. We argue that this transition is driven by the meridional teleconnection from the South China Sea (SCS) and the zonal teleconnection from the North Atlantic Ocean. In P1, the western North Pacific subtropical high (WNPSH) was significantly extended westward, but its northward expansion was delayed due to the meridional wave train from the suppressed convection over the SCS and the zonal wave induced by the negative summer North Atlantic Oscillation (SNAO). This condition prevented a northward migration of the monsoon rainband but allowed more extratropical cyclones to pass over the Korean Peninsula, resulting in four HREs. In P2, the meridional and zonal wave trains changed their phases due to the enhanced convection over the SCS and the positive SNAO, respectively, prompting an abrupt northward expansion of the WNPSH. This allowed strong southwesterly moisture transport along the northwestern boundary of the WNPSH, forming a monsoon rainband over the Korean Peninsula. As a result, seven HREs occurred, including one affected by an extratropical transition. This result demonstrates that the nature of summertime HREs in East Asia can be significantly influenced by remote forcings by determining regional synoptic conditions.

Using severe weather reports, precipitation observations, and composite Doppler radar reflectivity data, a 7-year climatology of the initiation, decay, and organization of severe convective storms (SCSs), as well as the associated severe convective weather, namely, short-duration heavy rainfall (SDHR), hail, and thunderstorm high winds (THWs), during the warm seasons (May–September) of 2011–2018 (except 2014) over North China was established. A total of 371 SCSs were identified. SCSs primarily initiated around noon with the highest frequency in the middle section of Mount Taihang. SCSs mostly decayed over the plains at night. The storm morphologies were classified into three types of cellular systems [individual cells (ICs), clusters of cells (CCs), and broken lines (BLs)], six types of linear systems [convective lines with no stratiform (NSs), with trailing stratiform (TSs), leading stratiform (LSs), parallel stratiform (PSs), embedded lines (ELs), and bow echoes (BEs)], and nonlinear systems (NLs). NLs were the most frequent morphology, followed by CCs. TSs were the most frequent linear morphology. A total of 1,429 morphologies of the 371 SCSs were found to be responsible for 15,966 severe convective weather reports. Linear (nonlinear) systems produced the most SDHR (hail and THW) reports. BEs were most efficient in producing both SDHR and THW reports whereas BLs had the highest efficiency for hail production. 

Typhoon Rammasun (2014) experienced a rapid intensification (RI) before its landfall in South China. The track, structure and intensity changes of Rammasun were reproduced reasonably in a simulation using the Weather Research and Forecasting Model (WRF-ARW). In this study, kinetic energy budget during the rapid intensification (RI) of the modeled Rammasun were analyzed to examine the dominant dynamic and thermodynamic processes associated with the RI.The winds were partitioned into environmental and tropical-cyclone winds, and the tropical-cyclone winds were further separated into rotational and divergent components. The results show that the environmental circulations tend to reduce rotational kinetic energy and divergent kinetic energy during the RI. Divergent kinetic energy is converted to rotational kinetic energy, which mainly enhances the rotational kinetic energy and leads to RI. The divergent kinetic energy comes mainly from the conversion of the available potential energy. Since the RI is defined as the increase in symmetric rotational energy, the further analysis will be conducted in a cylindrical coordinate where rotational and divergent winds are separated into symmetric and asymmetric components. The results of budget analysis of Rammasun during the RI will be reported during the session AS14 of AOGS.

Sea salt aerosols were assumed to be homogeneous spheres in WRF models. However, observations show that sea salt particles are inhomogeneous with different RHs. Using a two‐layer sphere model, we found that backscattering of solar radiation associated with sea salts is underestimated in homogeneous sea salt models. The Weather Research and Forecasting (WRF) model V3.7 is used to assess the inhomogeneity effect on typhoon Fitow, the No. 23 typhoon in 2013. To distinguish the effects of inhomogeneous sea salt on precipitation of the landfalling storm, Force (remove sea salt aerosol in radiative transfer in the WRF), control (no change in the WRF) and sensible (replace optical properties of sea salt at RH=70% in the WRF) experiments were conducted with different effects on radiative transfer. The results show that the inhomogeneous of sea salt aerosol has little effect on the track and intensity of typhoon. The main impact is concentrated on typhoon precipitation. The inhomogeneity of sea salt decreases the asymmetry factor and increases backscattering of solar radiation. Thus, the ground cooling effect is enhanced, and the atmospheric stability is increased. As a result, total accumulated precipitation in the typhoon main body is decreased. Keywords Typhoon, Precipitation, sea salt aerosols, WRF model

Over the complex terrain of the Maritime Continent (MC), it is challenging to produce accurate numerical analyses and forecasts of convection. To make matters worse, convection evolves on time scales of an hour. Since atmospheric motion vectors (AMV) and local in-situ observations are made every 3 hours or more, it is difficult for these observations to resolve convection. One solution to this challenge is to supplement in-situ observation with modern geostationary satellite infrared (GeoIR) observations. Modern GeoIR observations are frequently available (> 1 scan/hour) at high resolution (< 5-km pixel width), meaning that GeoIR observation can resolve the rapid evolution of meso-γ, or larger, convective systems. The assimilation of these GeoIR observations, on top of existing in-situ and atmospheric motion vector observations, can thus potentially improve the analyses and forecasts of MC mesoscale convective systems.In this talk, we will use an MC tropical squall event to explore the impacts of assimilating varying amounts of GeoIR observations (none at all, 3-hourly and half-hourly), on top of AMV and in-situ observations. Specifically, we employed GeoIR brightness temperature (BT) observations made by the upper tropospheric tropospheric water vapor channel (channel 8; ch08-BT) of the Advanced Himawari Imager, on board the Himawari-8 satellite. Both clear-sky and cloud-affected ch08-BT observations were assimilated. Without ch08-BT observations, the analyzed squall line propagated too quickly. While the addition of 3-hourly ch08-BT observations was found to improve the analyzed cloud fields, the addition did not noticeably improve the analyzed positions of the gust front and cold pool. In contrast, the use of half-hourly ch08-BT observations resulted in improved analyzed cloud fields, gust front position and cold pool position. These results motivate further study into using GeoIR observations to improve the analyses and forecasts to MC mesoscale convective systems.

Based on the hourly meteorological data of Zhejiang Province from 2014 to 2019,  the spatial distribution characteristics of summertime afternoon precipitation (14:00-19:00) without the influence of typhoon were analyzed. OLR (Ordinary linear region), GWR (Geographically weighted region) and GNNWR (Geographically neural network weighted region) models were used to estimate the afternoon precipitation considering geographical (latitude, longitude), topographic (altitude, slope, aspect) and meteorological (wind) factors, and the prediction effects of the three models were compared. The results show that: (1) the summertime afternoon precipitation in Zhejiang Province shows a decreasing trend from southwest to northeast, there is a wet tongue of precipitation, and there is an obvious high value area in the southern mountainous area. (2) GWR and GNNWR models considering spatial weights are superior to OLR model in both magnitude and spatial pattern. (3) GWR Model and GNNWR model with neural network have good prediction effects, the absolute error is less than 0.06, R² can reach 0.97. Compared with GWR model, GNNWR model is closer to the observed precipitation in spatial pattern, the prediction effect of local area is better. (4) The weight distribution of different factors can well explain the spatial distribution of observed and predicted precipitation in the afternoon.

For tropical cyclones (TCs) over the western North Pacific, the interaction between dry air and TC is extensive and significant since the dry air can come from not only the high-pressure system but also the dry mid-to-high-latitude continent. However, the question of how the dry-air intrusion influences the vertical structure of TC circulation and precipitation from observation has not been studied yet. In this study, we adopt several datasets from TRMM and NCEP FNL reanalysis data to explore both the vertical structure of precipitation and its variation for landfalling TCs over China. The study suggests that the process of environmental dry-air intrusion has an important regulation effect on the vertical structure and precipitation of TC, especially in the outer region of TC. 

Black carbon (BC) and dust impart significant effects on the south-Asian monsoon (SAM), which is responsible for ~80% of the region’s annual precipitation. This study implements a variable-resolution (VR) version of Community Earth System Model (CESM) to quantify two radiative effects of absorbing BC and dust on the SAM. Specifically, this study focuses on the snow darkening effect (SDE), as well as how these aerosols interact with incoming and outgoing radiation to facilitate an atmospheric response (i.e., aerosol radiation interactions; ARI). By running sensitivity experiments, the individual effects of SDE and ARI are quantified. It is found that ARI of absorbing aerosols warm the atmospheric column in a belt coincident with the May-June averaged location of the subtropical jet, bringing forth anomalous upper-tropospheric (lower-tropospheric) anticyclogenesis (cyclogenesis) and divergence (convergence). This anomalous arrangement in the mass fields brings forth enhanced rising vertical motion across south Asia and a stronger westerly low-level jet, the latter of which furnishes the Indian subcontinent with enhanced Arabian Gulf moisture. Precipitation increases of 2 mm d^-1 or more (a 60% increase in June) result across much of northern India from May through August, with larger anomalies (+5 to +10 mm d^-1) in the western Indian mountains and southern TP mountain ranges due to orographic and anabatic enhancement. Across the Tibetan Plateau foothills, SDE by BC aerosols drives large precipitation anomalies of >6 mm d^-1 (a 21 - 26% increase in May and June), comparable to ARI of absorbing aerosols from April through August. Runoff changes accompany BC SDE-induced snow changes across Tibet, while runoff changes across India result predominantly from dust ARI.

Coupling between the atmosphere and the heterogenous land surface can play an important role in the climate system. Traditional global climate models (GCMs) have coarse horizontal grid resolutions on the order of 100 km that poorly capture mesoscale processes in the atmosphere or the heterogenous land surface properties. To overcome this limitation, we have implemented a Multiple Atmosphere Multiple Land (MAML) framework in the Super-Parameterized Energy Exascale Earth System Model (SP-E3SM). In the standard SP-E3SM, all subgrid-scale atmospheric processes (e.g., radiation, clouds, and precipitation) are represented by a nonhydrostatic Cloud Resolving Model (CRM) embedded in each E3SM grid. As each atmospheric column of the CRM interacts with the same land surface represented by the E3SM Land Model (ELM), this configuration is called Multiple Atmosphere Single Land (MASL). In contrast, in the MAML framework, each atmospheric column of the CRM interacts with its own underlying land surface simulated by the ELM so that non-linear effects of land-atmosphere interactions can be better represented. To investigate the impact of the MAML approach, we perform two simulation experiments: one with the MASL approach and the other with the MAML approach. Preliminary results show that while total precipitation patterns are similar between these two simulations, regional precipitation shows some interesting difference:  MAML simulation produces less precipitation in the Amazon region worsening the dry bias, but more realistic precipitation over the Indian Monsoon region. Analysis of the results focusing particularly on the soil moisture-precipitation feedback in the two simulations and future development to improve modeling of land-atmosphere interactions in the MAML framework will be discussed.

Superparameterization means that conventional convective parameterization in a general circulation model (GCM) is replaced by a cloud-resolving model (CRM) in each GCM grid. One of the models is the superparameterized community atmosphere model (SPCAM). Although this framework can simulate deep convection directly, a previous study shows that slopes of fitting lines of precipitation as a function of column water vapor (CWV) over tropical oceans are flatter than observation. However, the study only examines a GCM scale; the CWV-precipitation relationship is not examined on a CRM scale. Our result shows that slopes of fitting lines are sharper in the CRM scale compared with observation. The inconsistency between the GCM scale and the CRM scale indicates that SPCAM cannot exhibit the CWV-precipitation relationship properly from the CRMs to the GCM. Because the precipitation of each grid in SPCAM is from an average value of its CRM, there will be moderate precipitation if wet and dry environments exist in a CRM simultaneously. Wet columns would tend to produce stronger precipitation, while dry columns tend to produce weaker precipitation. This wet-dry separation sometimes does not reflect the real distribution of convection in that scale which could be due to the periodic boundary condition in the CRM. This bias may get worse when the model simulates large convective systems like tropical cyclones. To improve SPCAM performance, one possible method is partially choosing CRM columns to feedback tendency to GCM grids. This method tries to decrease the effects of the periodic boundary condition. Sensitivity tests of domain sizes and resolution are conducted to find out the best combination.

The scaling exponents of the distributions of cluster rain amount, R, and cluster size, A, for oceanic rain clusters over the Indian and Pacific warm pools, and the intertropical convergence zones over the eastern Pacific and the tropical Atlantic, were obtained from a set of regional climate model downscaling products. The main aim of the investigation is to compare the model cluster’s scaling characteristics with those obtained from observations that have been reported previously. The scaling exponents for the model were found to be different across the ocean basins indicating the lack of universality in the modelled rain cluster distributions. The scaling exponent for the conditional mean of R given A = a, E(R|a), was found to be the same across the different ocean basins, and the estimated value of the exponent agrees with that obtained from satellite observed rain clusters. However, no crossover in the scaling of E(R|a) in the model for cluster size larger than mesoscale was seen, unlike those reported elsewhere. The implication is that in the model the intensification of rain with cluster size continues up to synoptic scale. Through simple scaling arguments it is believed that the model simulates the fundamental mesoscale dynamics well and thus estimated the E(R|a) in agreement with observations.

Air quality prediction is usually performed with regional climate models (RCMs) but also relies on global climate models (GCMs) for boundary and initial conditions, which can induce uncertainties to the simulation. Conventional RCMs and GCMs still also have some limitations in simulating multi-scale interactions between air pollution (aerosols) and large-scale processes. The development of variable resolution GCMs models provide a great opportunity to achieve two-way interactions at multi-scales and explore the physical and chemical processes in refined regional scales. In this study, multiple observation and MICS-Asia Phase III Regional Models datasets are applied to assess the performance of Community Atmosphere Model with Chemistry (CAM-chem) based on Spectral Element dynamical core (CAM-Chem-SE) with regional refined over East Asia at resolutions of 0.25 degree in the ozone pollution simulation. Our results show that, the regional refined CAM-Chem-SE model can generally reproduce the significant seasonal cycle, spatial distribution characteristics, and the vertical distribution patterns of ozone. However, ozone concentrations over China are slightly underestimated in the simulations, which may be related to the inaccurate description of pollutant emissions over China in CMIP6. A further modification of the emissions over China in CMIP6 will be needed in our evaluations. Analysis about the long-range transport of air pollutants, as well as the multiscale interactions between air pollution and climate change, will be further explored in this study.

The non-hydrostatic global variable-resolution model (MPAS-Atmosphere) is first time used to attempt at simulating the Mei-yu rainfall in 2015 over East China. Convection-permitting simulations with regional refinement at 4 km resolution (V4km) and uniform 60km resolution simulations (U60km) are compared, focusing on the diurnal variation of precipitation amount (PA), intensity (PI), and frequency (PF). Both simulations reasonably reproduce the spatial distribution of PA. V4km is more skillful in simulating the spatial distributions and magnitudes of PF and PI. The diurnal cycle of Mei-yu rainfall shows a major early morning peak and a minor afternoon peak, contributed by precipitation during two sub-periods with distinct large-scale circulations. With strong Mei-yu in the first sub-period, the diurnal variation of PA is controlled by nocturnal southwesterly jet. V4km overestimates the morning peak mainly due to its bias in simulating boundary layer inertial oscillation. Although U60km overestimates PF and underestimates PI, differences in PA between the simulations are small. With weak Mei-yu in the second sub-period, the diurnal variation of PA is controlled by both large-scale circulation and local convection. At both resolutions, deviations in the large-scale circulation modulated by a few typhoons lead to positive biases in the morning peak of PA. After removing the typhoon impacts, V4km captures the observed diurnal cycle of PA well, while U60km significantly underestimates the magnitudes of PA and PI particularly in the afternoon. Future studies focusing on advancing modeling of the southwesterly jet and typhoons may further improve the convection permitting simulations of Mei-yu rainfall.

The World Climate Research Programme (WCRP) has an international initiative called the COordinated Regional climate Downscaling EXperiment (CORDEX). The goal of the initiative is to provide regionally downscaled climate projections for most land regions of the globe, as a compliment to the global climate model projections performed within the Coupled Model Intercomparison Projects (CMIP). CORDEX includes data from both dynamical and statistical downscaling. It is anticipated that the CORDEX dataset will provide a link to the impacts and adaptation community through its better resolution and regional focus. Participation in CORDEX is open and any researchers performing climate downscaling are encourage to engage with the initiative. Here I present the current status, evaluation and future projections for the CORDEX-Australasia ensemble. The CORDEX-Australasia ensemble is the largest regional climate projection ensemble ever created for the region. It is a 20-member ensemble made by 6 regional climate models downscaling 11 global climate models. Overall the ensemble produces a good representation of recent climate. Consistent biases within the ensemble include an underestimation of the diurnal temperature range and an underestimation of precipitation across much of southern Australia. Under a high emissions scenario projected temperature changes by the end of the twenty-first century reach ~ 5 K in the interior of Australia with smaller increases found toward the coast. Projected precipitation changes are towards drying, particularly in the most populated areas of the southwest and southeast of the continent. The projected precipitation change is very seasonal with summer projected to see little change leaning toward an increase. These results provide a foundation enabling future studies of regional climate changes, climate change impacts, and adaptation options for Australia.

Coarse resolution global climate models (GCM) cannot resolve fine-scale drivers of regional climate, which is the scale where climate adaptation decisions are made. Regional climate models (RCMs) generate high-resolution projections by dynamically downscaling GCM outputs. However, evidence of where and when downscaling provides new information about both the current climate (added value, AV) and projected climate change signals, relative to driving data, is lacking. Seasons and locations where CORDEX-Australasia ERA-Interim and GCM-driven RCMs show AV for mean and extreme precipitation and temperature are identified. A new concept is introduced, ‘realised added value’, that identifies where and when RCMs simultaneously add value in the present climate and project a different climate change signal, thus suggesting plausible improvements in future climate projections by RCMs. ERA-Interim-driven RCMs add value to the simulation of summer-time mean precipitation, especially over northern and eastern Australia. GCM-driven RCMs show AV for precipitation over complex orography in south-eastern Australia during winter and widespread AV for mean and extreme minimum temperature during both seasons, especially over coastal and high-altitude areas. RCM projections of decreased winter rainfall over the Australian Alps and decreased summer rainfall over northern Australia are collocated with notable realised added value. Realised added value averaged across models, variables, seasons and statistics is evident across the majority of Australia and shows where plausible improvements in future climate projections are conferred by RCMs. This assessment of varying RCM capabilities to provide realised added value to GCM projections can be applied globally to inform climate adaptation and model development.

Highly industrialized East Asia, with its high greenhouse gas emissions, must inevitably increase renewable energy production to achieve the goals of the Paris Agreement. Photovoltaics (PV), a widely utilized renewable energy source, is directly affected by the weather and climate. This study conducted a first analysis of current and future PV potential (PVpot) changes over East Asia using the ERA5 reanalysis and multiple high-resolution regional climate model simulations. The recent PVpot over East Asia did not exhibit any notable changes, but the future PVpot is predicted to decrease by −4.0 % (winter) to −1.6 % (summer) on average. It was found that the widespread increase in near-surface air temperature leads to the overall PVpot decrease (around −2.0 %) over East Asia across all seasons. Interestingly, surface down-welling shortwave radiation increases in summer, offsetting temperature-induced PVpot decreases (by about 0.7%) while it decreases in winter and spring, intensifying the warming-driven PVpot decrease (by about -1.4% to -2.3%). Further, the changes in the number of rainy days are found to be associated with the changing patterns of surface down-welling shortwave radiation, indicating the importance of reliable projections of precipitation. Wind speed exerts a negligible effect.

In the mid-latitudes, synoptic-scale phenomena like high and low-pressure systems generate the variability of the regional-scale weather system. To identify the weather variability of extra-tropical region storm track activity has been analyzed based on observations since the mid-nineteenth century. After early-stage research that directly counted the movement of cyclones, it has been used that time filtering method based on grid analysis to an isolated disturbance with periods of 2~7 days. This bandpass filtering method has the advantage of being able to examine the distribution and the variability of the storm track spatially in vertical and horizontal space. In this study, we confirm the storm track activity in the East Asia region using the dynamical down-scale results from CORDEX (COordinated Regional climate Downscaling EXperiment) projects. Based on the analysis of reanalysis data, GCM (Global Climate Model) data which used for forcing in RCM (Regional Climate Model), and RCM data, it verifies the reproducibility and confirms the temporal change in the storm track activity. The role of added value from RCM is discussed, also.

Regional Climate Models (RCMs), including the RegCM4, are good tools for producing added climate information at a small scale (e.g., extreme precipitation) that the Global Circulation Model (GCM) cannot resolve. However, the results of RCM simulations forced by GCM have errors and uncertainties. To reduce these drawbacks, the Spectral Nudging Technique (SNT) has been applied as an alternative method for boundary conditions. To understand the impact of the SNT on the dynamical downscaling of RCM, in this study, we conducted the sensitivity experiments to the SNT using the RegCM4 forced by the United Kingdom Earth System Model (UKESM). The SNT studies in RegCM4 are considerably meaningful in the CORDEX East Asian region due to the insufficiency of previous studies. We focused on the impact of the SNT on mean and extreme precipitation. The sensitivity experiment showed that the SNT could improve the simulations of mean and extreme precipitation compared with GCM and RCM without the SNT. The impact of the SNT was significant in JJA as well as DJF, especially on extreme precipitation. Additionally, we analyzed the synoptic field related to mean and extreme precipitation to examine why the SNT improved the simulation of the RegCM4.

The Asian Precipitation Experiment (AsiaPEX) was launched in 2019 and is developing its Science Plan. It defined the objectives of AsiaPEX as "understanding of Asian land precipitation over diverse hydroclimatological conditions and multiple time scales for better prediction, disaster reduction, and sustainable development." Now is the time to finalize the Science Plan. In the AsiaPEX, we will not pursue a geographical region-oriented strategy, but a research approach-oriented strategy. Based on our six approaches, 1) observation and estimation of variation and extremes in Asian land precipitation and important variables, 2) process studies of Asian land precipitation focusing on diverse land-atmosphere coupling, 3) understanding and prediction of the variability of Asian monsoon from subseasonal to interdecadal time scales, 4) high-resolution land surface hydrological modeling and monitoring incorporating impacts of human water withdrawal, agriculture, vegetation and cryosphere, 5) coordinated observation and modeling initiatives, 6) detection and projection of the climate change impact on regional precipitation in Asia, we will review the recent development of the AsiaPEX activity. The AsiaPEX is the successor of the GAME and the MAHASRI projects under the GHP/GEWEX/WCRP, which had led the joint activity of the Asian hydroclimatological research community. These projects planned and conducted observational initiatives. The GAME project conducted its Intensive Observation Period in 1998. From 2007 to 2012, the Asian Monsoon Year (AMY) was conducted to improve Asian monsoon prediction for societal benefits through improving understanding of the variability and predictability of the Asian-Australian monsoon system. Following these achievements, one of the focuses of the discussion in the present session will be the discussion on the observational and modeling initiative of the AMY-II. We will present a plan for the AMY-II in this presentation.

Monsoons have always been of great interest to the World Climate Research Programme (WCRP), particularly to its core projects CLIVAR (Climate and Ocean: Variability, Predictability and Change) and GEWEX (Global Energy and Water EXchanges), which have jointly established a Monsoon Panel to coordinate the various monsoon related research activities with individual attention to regional monsoons around the world. Monsoons, as the primary source of water in the affected regions, have long attracted scientific attention to understand and predict their variability both in the weather and climate context. Although significant progress has been made in understanding the drivers of the monsoon processes including the complex ocean-atmosphere-land interactions, particularly during the last decade, monsoons remain a scientific challenge to model and reliably predict anomalies in their spatio-temporal patterns as well as intensity. This is crucial for a large part of the global population that are dependent on the monsoons for their annually recurring large-scale moisture transport that determines the water availability for the entire year. Furthermore, the various regional monsoon phenomena that can be found around the world share many commonalities and can be linked to large scale atmospheric and oceanic circulation. By facilitating monsoon research on local, regional as well as global scales, the WCRP aims to significantly advance our understanding and predictive capabilities, which have immense societal applications. In this presentation we introduce the objectives and structure of the Monsoon Panel and its activities including future perspectives in the light of the new WCRP Strategic Plan unfolding. A new initiative to establish an International Monsoons Project Office in collaboration with the World Weather Research Programme (WWRP) will be highlighted.  We will also showcase several examples of international collaborative monsoonal studies undertaken in the various parts of the world, and their potential implications for further advances in Asian monsoon research.

The Tibetan Plateau (TP), as a whole, has undergone a moistening process since the late 1990s. However, the southern Tibetan Plateau (STP) is an exception, where summer monsoon precipitation amount has decreased, and lakes have shrunk. The cause for the precipitation decrease is not clear yet. Here we show that the monsoon (June to September) mean precipitation changes in the STP from 1979 to 2018 features a decadal variation component with a peak of around ten years that is superposed on an upward ‘trend’ from 1979 to 1998 and a downward ‘trend’ afterward. We find that the decadal variation of the STP precipitation is associated with a large-scale dipolar sea surface temperature (SST) pattern between the equatorial central Pacific and the Indo-Pacific warm pool. A wet STP corresponds to negative SST anomaly in the equatorial central Pacific and positive SST anomaly in the Indo-Pacific warm pool. This equatorial SST gradient in the western Pacific generates pronounced easterly anomalies and a dipolar rainfall anomaly (i.e., a positive rainfall anomaly over the Maritime Continent and a negative anomaly in the equatorial western and central Pacific). Due to less precipitation over the equatorial western Pacific, the suppressed heat source appears to excite an anomalous anticyclonic band along 15-20°N extending from the Philippine Sea to the Bay of Bengal by emanating westward propagating descending transient Rossby waves. The low-level anticyclonic circulation over the Bay of Bengal further enhances northward moisture transport toward the STP and promote upward motion in the STP through changing local meridional circulation. Besides, the linearized atmospheric general circulation model experiments demonstrate that the dipole heating source can generate a high-pressure zone under the control of anticyclone over the western Pacific, which can extend westward to the Indian monsoon region.

The relation between extreme precipitation events and intraseasonal variation in Assam state, India has been investigated. First, the regional characteristics of extreme rainfall analyzed using in-situ observation data from 15 rain gauges in Assam from 2007 to 2016. The results show that the frequency of highest rainfall-rank (>50 mm d^-1) contributes significantly to the total frequency in western Assam and northern bank of the Brahmaputra. In Kokrajhar, located on the northern bank of Brahmaputra River in the western Assam, the highest rainfall rank accounts for about 20%. On the other hand, the lowest rainfall ranks (< 5 mm d^-1) are largely contributed by the south-central and central parts of Assam. Also, in Lumding and Diphu, about 60% of the rainfall is classified as the lowest rainfall rank. Based on the 99^th percentile values for each station, the maximum value is 175.1mm d^-1 in Kokrajhar and the minimum value is 68.5mm d^-1 in Nagaon. At Kokrajhar, 60% of the extreme rainfall events occur during the monsoon season (June–September). And the composite analysis of the 90^th percentile cases indicates that the extreme heavy rainfall over the northern bank of the Brahmaputra is associated with anomalies in the anticyclonic circulation over the Gangetic plain. Over the northeastern Indian subcontinent, convergence anomalies of water vapor fluxes are associated with the intensification of westerly water vapor fluxes. These cases correspond well with the break phase of the intraseasonal variation in the Bay of Bengal. 

Future greenhouse warming is expected to influence the characteristics of global monsoon systems. However, large regional uncertainties still remain. Here we use 16 Coupled Model Intercomparison Project Phase 6 (CMIP6) models to determine how the length of the summer rainy season and precipitation extremes over the Asian summer monsoon domain will change in response to greenhouse warming. Over East Asia the models simulate on average on the earlier onset and later retreat; whereas over India, the retreat will occur later. The model simulations also show an intensification of extreme rainfall events, as well as an increase of seasonal drought conditions. These results demonstrate the high volatility of the Asian summer monsoon systems and further highlight the need for improved water management strategies in this densely populated part of the world.

This study examines the characteristics of the diurnal variations of heavy rainfall episodes (≥ 110 mm in 12 h) in Korea and the related atmospheric circulation during the Changma rainy seasons of 1980-2020, aming at understanding what synoptic/mesoscale circulations were responsible for a series of long-lasting heavy rainfall events occurred in Korea during the summer of 2020. Focusing on July, the wettest period of the Changma season, the characteristics of the heavy-rainfall systems in 2020 are compared with their climatology. Two dominant pattens of diurnal variation of the heavy rainfall emerged over Korea: all-day heavy rainfall (AD) and morning only heavy rainfall (MO) types. For the AD type, the heavy rainfall is caused by abundant moisture content in conjunction with active convection in the morning (0-12 local time, LT) and the afternoon hours (12-24 LT). These systems are related to the enhanced moisture inflow and upward motion induced by the strengthening of the western North Pacific subtropical high and upper-tropospheric jet. The MO-type heavy rainfall events occur mostly in the morning hours; the associated atmospheric patterns are similar to the climatology. The 2020 heavy-rainfall system is considered a typical AD-type event and resembles the 1991 Changma in its overall atmospheric circulation. The present results suggest that extremely heavy rainfall episodes in Korea during the 2020 Changma rainy season would recur in the future if the AD-type’s conditions would be met. 

To clarify the past local characteristics of the Asian monsoon, this paper will focus on monsoonal climate events, especially from spring to autumn that effectively affected agricultural production in Takahama, a village in the Amakusa islands of Kyushu, Japan, in the pre-statistical area especially from 1793 to 1818. Nature-induced disasters such as earthquakes and storms were recorded in the diary of a village head, Shoya, at the top of his every day’s records for the village administration, because the village head briefly recorded the weather of the day after the date description using terms such as ‘fine’, ‘cloudy’, ‘rainy’, ‘storm’, ‘north wind’, ‘south wind’, ‘severe wind’, ‘earthquake in the afternoon’, and so on. To quantify these weather statements, 2 points for rain, 1 point for cloudy, 0 point for sunny day, 2.5 points for heavy rain and 1.5 points for weak rain are weighted. The difference in rainfall change from May to August is analysed based on monthly average points. There were strongholds of typhoons and heavy rains putting harvesting constraints against on an organic economy in Takahama. It was able to confirm that flooding did not occur during the peak season of typhoons, but that heavy rain, especially during the rainy season, caused enormous flood damage. Furthermore, it was understood that concern about the lack of rainfall all the time, suggested by rain-seeking rituals, was worried because the number of years for which such rituals were performed exceeded 70 percent of the years within the observed years. Sunshine was expected in July and prompt rainfall was also expected at the same time as securing the amount of solar radiation accompanied by fine weather in August. It was confirmed that the rhythm and balance of rainfall volume and solar radiation amount are important for rice growth. 

Ice clouds are mostly composed of different ice crystal habits. It is of great importance to classify ice crystal habits seeing as they could greatly impact single‐scattering properties of ice crystal particles. The single‐scattering properties play an important role in the study of cloud remote sensing and the Earth's atmospheric radiation budget. However, there are countless ice crystals with different shapes in ice clouds, and the task of empirical classification based on naked‐eye observations is unreliable, time consuming and subjective, which leads to classification results having obvious uncertainties and biases. In this paper, the images of ice crystals observed from airborne Cloud Particle Imager in China are used to establish an ice crystal data set called Ice Crystals Database in China, which consists of 10 habit categories containing over 7,000 images. We propose an automatic classification model of ice crystal habits, called TL‐ResNet152, which is a deep convolutional neural network based on the newly developed method of transfer learning. The results show that the TL‐ResNet152 model could achieve reliable performance in ice crystal habits classification with the accuracy of 96%, which is far more accurate than traditional classification methods. Achieving high‐precision automatic classification of ice crystal habits will help us better understand the radiation characteristics of ice clouds.  Reference: Xiao Haixia; Zhang Feng*; He Qianshan; Liu Pu; Yang Zhipeng; Classification of ice crystal habits observed from airborne Cloud Particle Imager by deep transfer learning, Earth and Space Science, 2019, 6: 1877-1886.

Observations have confirmed that clouds have a large impact on radiation which in turn affects cloud development. Most radiation parameterization schemes in WRF are parallel to the plane which ignores the inhomogeneous properties of clouds, while in fact almost no clouds fields are uniform. Inhomogeneity effects should be significant in Nagqu Prefecture of Tibet, which has frequent and massive local cumulus precipitation caused by intense radiation. The spherical harmonics discrete ordinate method (SHDOM) uses both spherical harmonics and discrete ordinates to represent the radiance field during different parts of the solution algorithm which can perform 3D unpolarized radiative transfer with high efficiency. In this paper we coupled the 3D SHDOM radiation scheme in WRF with microphysics scheme considering the surface albedo and underlying surface condition. We have done high resolution large-eddy simulations with the new radiation scheme of WRF to study the radiation characteristics of cumuli in Nagqu Prefecture, especially the effects of cloud top cooling on the cloud development. Comparing with the multi-observation data of ground and upper air in Nagqu Prefecture, the preliminary results show that the cooling and heating on cloud top highly impacts cumulus cloud developments in Tibet. 

As a new generation of hyperspectral sensor, the Tropospheric Monitoring Instrument (TROPOMI) on the Copernicus Sentinel-5 Precursor (S5P) was launched in October 2017 and started to globally map atmospheric trace gas constituents, clound and aerosols. In particular, aerosol parameters including UV aerosol index, optical depth, and aerosol layer height are vital to the assessment of the air quality in the lower atmosphere. The aerosol height information is derived based on absorption in the O₂ A-band in the near infrared wavelength range (759 and 770 nm). Aerosol retrieval from spaceborne measurements has been a challenging task and requires accurate and efficient forward modeling and inversion calculations. In this work, we present a conventional retrieval algorithm developed for TROPOMI/S5P O2 A-band and analyze the impact of different forward and instrument model parameters on the retrieval output. Through this work, an optimized retrieval configuration and a better understanding of the instrument characteristics can be achieved.

The Invariant Imbedding (IIM) T-matrix method is recognized as one of the most promising scattering models since it can perform the scattering simulation of the nonspherical particles in a semi-analytical way. However, because the T-matrix should be updated in each iterative process, its computational efficiency is an important issue in the actual scattering simulation. To alleviate this problem, the symmetrical properties for the nonspherical particles with symmetrical geometries are systematically investigated in this paper. Firstly, the symmetry of the U-matrix (an important matrix in the IIM T-matrix model) is derived for the particles with mirror symmetry with respect to the coordinate planes. In this case, the U-matrix is firstly decomposed into the sine and cosine components, and then its symmetrical properties are obtained by combining the spatial symmetry of the permittivity and the symmetry of the angular functions. In the second part, the symmetry of the U-matrix is derived for the particles with N-folds symmetrical geometry, and based on the symmetrical properties, the method to simplify the T-matrix iteration is further proposed. In this case, it can be found that by using the symmetry of the U-matrix, both the U-matrix and T-matrix can be rearranged into the block diagonal ones, and the calculation of the T-matrix can be decomposed into the iteration of several block sub-matrices, which can cut down the computational amount and memory consumption notably. Also, it can be seen that the derivation process also provides another point of view to understand the symmetry of T-matrix for the particles with N-folds symmetrical geometry.

Several radiative transfer schemes are compared in infrared spectra using the Rapid Radiative Transfer Model for General Circulation Models Applications (RRTMG). By calculating the root mean squared error of net flux (referred as RMSE(NF)) in various atmosphere, the sensitivities to cloud fraction are decreased in the order: non-scattering simplification (NS), the adding method of δ-two-stream discrete ordinate approximation (δ-2DDA), the adding method of δ-four-stream discrete ordinate approximation (δ-4DDA). The accuracy and efficiency of δ-2DDA and δ-4DDA schemes are studied under the contexts of using two different methods for dealing with the region where the solar and infrared spectra overlap. As one of the two overlap methods, One Band method (OB), which is used by RRTMG, has no advantage in model efficiency and is about 0.34 (0.41) W/m² higher in mean column RMSE(NF) of the δ-two-stream (δ-four-stream) schemes than Whole Bands method (WB). Moreover, a new scheme, which is simple but adequate to handle the overlap region, is derived to solve the solar energy in longwave spectra. Reference: Han Lin, Kun Wu*, Wenwen Li, 2020, Comparisons of radiative transfer schemes for infrared , spectra and the region with solar and infrared spectra overlap in RRTMG, Journal of Quantitative Spectroscopy & Radiative Transfer, 244, 106846. 

Sea salts are hygroscopic. During the deliquescence and crystallization processes, the particles could be nonspherical and inhomogeneous. Beccause of the importance of sea salt aerosol in atmospheric radiative transfer and remote sensing studies, the particle shape and inhomogeneity effects on the optical properties of sea salt aerosols should be examined. In this presentation, we report on recent progress on the polarized optical properties of sea salt aerosols. In particular, we highlight the inhomogeneity effect of sea salt aerosols on their single-scattering properties and the top of the atmosphere (TOA) polarized radiances. First, six sea salt particle models including homogeneous sphere, super-spheroids, inhomogeneous spheres with homogeneous sphere and super-spheroidal cores were defined to describe the morphologies of sea salt particles at different relative humidities. The Lorenz-Mie theory and the invariant imbedding T–matrix method were used to compute the single-scattering optical properties of the sea salt aerosols. Next, the polarized radiance at the top of the atmosphere (TOA) was simulated by using a radiative transfer model based on the adding-doubling method. Lastly, theoretial calcuations were then compared with PARASOL (Polarization and Anisotropy of Reflectances for Atmospheric Science coupled with Observations from a Lidar) observations. Based on the modeling results and the PARASOL observations, it is found that the inhomogeneity of sea salt causes salient negative polarization features at the backscattering angles (170°–175°). To explain such a phenomenon, a Debye-series formulation of light scattering by a coated-sphere is further employed to study the underlying scattering mechanism, and the geometric-optics term that causes the negative polarization is explicitly identified. These findings could be useful in remote sensing studies.

Cloudy sky spectral radiance at the top of the atmosphere has always been an important while difficult variable to simulate for fast radiative transfer models. In this paper, we focus on examining the impacts of cloud scattering properties on the spectral radiance signature of the High-spectral Resolution Infrared Atmospheric Sounder (HIRAS) onboard the Fengyun-3D (FY-3D) satellite by using the Advanced Radiative transfer Modeling System (ARMS) and the Community Radiative Transfer Model (CRTM). Cloud scattering properties used in the radiative transfer models are critical for modeling the spectral radiance under cloudy sky, which involves choices of appropriate cloud particle models and particle size distributions, etc. Multiple FY-3D HIRAS observations over Southern China and Southeast Asia with ice or liquid water cloud cover on 6 May 2018 are examined, respectively. Vertical atmospheric profiles are derived from the Modern-Era Retrospective analysis for Research and Applications, Version 2 reanalysis product. Cloud property retrievals from the Moderate Resolution Imaging Spectroradiometer are used. Cloud scattering property parameterization schemes based on spherical and nonspherical cloud particle shapes are implemented for liquid water and ice clouds in ARMS and CRTM, respectively. Results show that both ARMS and CRTM can well simulate the radiance at the HIRAS spectral ranges under liquid water cloud condition as compared with the HIRAS observation with mean absolute error (MAE) of brightness temperature of less than 1 K. However, for ice cloud conditions, ARMS model using assumed spherical ice properties exhibits large biases between simulation and observation. CRTM with nonspherical ice properties using 16-stream approximation shows MAE less than 1 K and MAE of about 1 K using 2-stream approximation.

The Directional Polarimetric Camera (DPC) carried by the GaoFen-5 satellite can continuously observe the earth in multiple bands, multiple angles, and high spatial resolution. This article uses the French multi-angle polarization load POLDER cloud recognition algorithm as a reference, and combines DPC multi-band reflectivity, polarization reflectivity, apparent pressure and other information to develop a cloud detection algorithm suitable for DPC. The algorithm is mainly divided into three parts: First, the threshold method is used to detect cloud pixels, and the apparent pressure is introduced to further restrict the conditions of clouds at different heights, and then use the 865nm band polarization Reflectance identifies the solar flare area reflected by the sea surface, and corrects the solar flare interference when the reflectance threshold is used to identify cloud pixels. In order to verify the accuracy of the algorithm, the MOD06 cloud mask product of MODIS on October 1, 2018 was compared with the results of the cloud recognition algorithm in this paper, and it was found that the cloud recognition results were in good agreement with the MOD06 products. In order to further quantitatively verify the accuracy of the cloud detection algorithm in this paper, the CALIPSO-VFM data from October 01 to 04, 2018 and the cloud detection results of this paper and the MYDO6 cloud mask product were selected to calculate the cloud/clear pixels hit rate and false alarm rate, respectively. The calculation results show that the average cloud hit rate of the algorithm is 13.501% higher than that of the MYD06 cloud mask product. The cloud error prediction rate is only 3.561% higher than that of MYD06 cloud mask products. The cloud detection algorithm proposed in this paper can provide important data support for subsequent DPC research on cloud parameters, water vapor, and aerosols. 

An early warning system for weather risk management in agricultural sector is operated by the Republic of Korea and covers major farming areas within the country. This system forecasts meteorological values and alerts individual farmers if a predicted meteorological condition may cause damage to their crops. However, meteorological forecasting can be especially difficult in complex mountainous terrain, where differences in the climate distribution, surface covering, and other conditions may cause spatial variation. Spatial downscaling using forecasts provided by the Korea Meteorological Administration has been well documented as a method to examine meteorological factors such as temperature, solar radiance, and precipitation. However, very little research has been conducted on the use of spatial downscaling forecast technology to predict relative humidity and water vapor pressure. This study examined the data collected from a network of 14 weather stations that were densely distributed in farming areas to quantify and explain the vapor pressure residuals obtained when calculating the relative humidity. Water vapor pressure was calculated using the temperature and humidity values observed at the end of each hour. Wind speeds were calculated by averaging the speeds measured over the last ten minutes of every hour.  The water vapor pressure deviation was corrected using hourly correction coefficients, whereas the remaining residuals were used to validate the vapor pressure differences due to surface covering (e.g., orchards, grasslands). Additionally, the maximum values of vapor pressure variation were calculated based on windless conditions. Our results showed that the characteristics of vapor pressure reduction at the target points depended on the wind speed and were expressed through an empirical equation. Areas with dense vegetation, such as forests and orchards, had a higher vapor pressure compared to grasslands, and there was generally very little net variation in vapor pressure during the night at wind speed of approximately 1m/s.

Traditional global climate models (GCMs) with coarse uniform resolution (UR) usually have deficiency in simulating realistic results at regional scale, while experimental global high-resolution models show benefits but also raise much computational burden. In recent years, variable resolution (VR) models with unstructured mesh are found to provide comparable results at regional scale and require less computational resources. In this study, the variable resolution CAM-MPAS model with the MPAS (Model for Prediction Across Scales) dynamical core coupled with CAM5 (Community Atmosphere Model Version 5) physics package is used to evaluate the effect of 30 km regional refinement over East Asia on the precipitation simulation. Our results show that the CAM-MPAS model can reasonably reproduce the annual and seasonal precipitation over East Asia, and the MPAS-VR simulation shows reduced mean bias and improvements in seasonal cycle, intensity distribution, and interannual variation compared with the low resolution MPAS-UR simulation. Furthermore, the major contribution to the improvements over the Tibet Plateau in the MPAS-VR experiment comes from the decrease of the grid spacing rather than the increase of the terrain resolution.

Over past years, the Weather Research and Forecasting (WRF) model has been widely used in the wind energy field, to determine the climatology of wind resource over large areas for site selection of wind farms, to assess the wind resource and annual energy production at a given site, and to forecast wind energy production of wind farms for electrical grid balancing purposes. Therefore, it is important to simulate accurately the wind speed at near-hub-height (typically ~100 m above ground) that is influenced by both mesoscale and local scale meteorological processes. This study evaluates a series of WRF simulations at resolutions from meso-scale (~5 km) to LES-scale (~60 m), i.e. 5 km, 3.3 km, 2 km, 1 km, 333 m, and 66 m, in terms of the model capability to reproduce the basic features of the wind at near-hub-height as well as the shape of wind shear. This study focuses on a few sites of Jiangsu Province, where intensive wind energy penetrations exist both onshore and offshore due to the favorable wind conditions and relatively large coastlines. The measurements of wind speeds at several altitudes are used to compare with the modeling results. The results show that the simulations with different horizontal resolutions tend to have different performance at the coastal and onshore stations. The simulations at all resolutions can roughly reproduce the wind speed at 70 m above the ground but overestimate the wind speed at the onshore site. The LES simulation captures more observed micro-scale wind features and reduces the monthly mean of modeling bias. More analysis of the difference in modeling results at various resolutions will also be discussed.

The rapid strengthening process of typhoon “Mujigae” over the offshore area was affected by various physical factors and processes including its structure, large-scale atmospheric circulation and marine environment. The improvement of typhoon intensity prediction requires the in-depth understanding of the dominant physical processes that are responsible for the rapid intensification of typhoon. Theoretical analysis of numerical simulation data was conducted to quantitatively identify such dominant physical factors and processes. The physical framework for rapid intensification of offshore typhoon with energy budget as the core was established and the high-resolution numerical simulation data of typhoon “Mujigae” were obtained by WRF. On this basis, the environmental wind field, divergent wind field and rotating wind field during the rapid intensification process of typhoon were decomposed, the kinetic energy and available potential energy budgets of typhoon rotation and divergence circulation were calculated. Analyzing the effects of the energy factors and the spatial configuration and temporal evolution of related physical quantities in the energy conversion process, the effects of barotropic, baroclinic, radiation, sensible heat and latent heat on the rapid intensification of typhoon were obtained, and the associated mechanism of the rapid intensification of typhoon over the offshore area was revealed.

We investigate this interaction using observational data and a high-resolution simulation of a hailstorm that occurred over Taizhou (Zhejiang, China) on March 19, 2014. During the hailstorm event, near-surface meso-γ vortices along a convergence line interact with hail cells. Herein the 10-m surface wind data from automatic weather stations shows that several meso-γ vortices or vortex-like disturbances existed over the convergence zone and played a vital role in the evolution of the hailstorm and the location of the hail. The model results agree with the observations and present a closer correlation between the hail and the low-level meso-γ vortices than those observed. The model simulation indicates that such low-level meso-γ vortices can be used to predict the next 10-min hail fallout zone. The low-level meso-γ vortices originated over the convergence zone and then fed back into the convergence field and provoked a stronger updraft. Vorticity budget analysis found that positive vorticity was mainly caused by the stretching and tilting term. Vorticity generation was initiated primarily by stretching and was extended by tilting. A three-dimensional flow analysis shows that the existence of low-level meso-γ vortices could help enhance a local updraft. Furthermore, the simulation reveals that the low-level meso-γ vortices existed in the bounded weak echo region at the front of the hail cell, enhancing convergence and strengthening updrafts. Graupel was broadly located between the 0°C isothermal line and the top of the clouds, roughly between the 0°C and −20°C isothermal lines. Accordingly, the hailstones grew rapidly. The suitable environment and the positive effect of the meso-γ vortices on the updrafts enabled hailstorm formation. 

Urban heat island is the most documented phenomenon of climate change. There are more than 450 cities where the phenomenon is experimentally documented. Urban overheating has a serious impact on energy, health, pollution and survivability of low income population. The present paper will present the more recent developments in the field of urban mitigation technologies. Progress on urban greenery, reflective, chromic, fluorescent and photonic materials will be presented in detail. Their potential to decrease the peak ambient temperature will be analysed. The impact on energy demand, peak electricity consumption, heat related mortality and morbidity as well as on pollution levels will presented.  

Recently urban heat situation in summer becomes problematic more and more in most Asian cites. Urban heat is the combined effect of global warming and urban warming. The latter is possibly weakened by appropriate urban planning, though global warming cannot be hindered by local municipality’s efforts. Among many heat mitigation methods, a cool roof with high reflective painting seemed to be the most effective solution and many of the previous studies showed that cool roof installation reduced urban air temperature by 1 to 2 K. In addition cool roof required no running cost unlike the other mitigation techniques. Despite many numerical studies on the cool roof applied to various cities, we found cool roof potential has not been evaluated appropriately yet because they assumed uniform and homogeneous urban forms in their simulations. We simulated the effect of the cool roof installation in Tokyo Metropolis using the WRF model with a single-layer urban canopy model, which was modified so that the actual urban parameters were incorporated in the simulation. The result showed that near surface air temperature (Ta) reduced by 0.24 K on average over Tokyo Metropolis if reflective painting (0.85 in albedo) was applied to all the buildings’ roofs and this reduction was much smaller compared to previous simulations on cool roof found in the literature. In addition, the degree of the Ta reduction linearly increased with the value of packing density of buildings. Since the urban parameters in the default WRF seem to overestimate actual urban forms for many cities as exemplified in the value of plane area index, 0.50, previous studies possibly resulted in the overestimation of temperature reduction by cool roof. 

Governments around the world have implemented measures to slow down the spread of COVID-19, resulting in a substantial decrease in the usage of motorized transportation. The ensuing decrease in the emission of traffic-related heat and pollutants is expected to impact the environment through various pathways, especially near urban areas, where there is a higher concentration of traffic. In this study, we perform high-resolution urban climate simulations to assess the direct impact of the decrease in traffic-related heat emissions due to COVID-19 on urban temperature characteristics. One simulation spans the January–May 2020 period; two additional simulations spanning the April 2019–May 2020 period, with normal and reduced traffic, are used to assess the impacts throughout the year. These simulations are performed for the city of Montreal, the second largest urban centre in Canada. The mechanisms and main findings of this study are likely to be applicable to most large urban centres around the globe. The results show that an 80% reduction in traffic results in a decrease of up to 1 °C in the near-surface temperature for regions with heavy traffic. The magnitude of the temperature decrease varies substantially with the diurnal traffic cycle and also from day to day, being greatest when the near-surface wind speeds are low and there is a temperature inversion in the surface layer. This reduction in near-surface temperature is reflected by an up to 20% reduction in hot hours (when temperature exceeds 30 °C) during the warm season, thus reducing heat stress for vulnerable populations. No substantial changes occur outside of traffic corridors, indicating that potential reductions in traffic would need to be supplemented by additional measures to reduce urban temperatures and associated heat stress, especially in a warming climate, to ensure human health and well-being.

Transit-Oriented Development (TOD) aims to optimize environmental and economic issues and the quality of life (QOL) around a station of the public transportation system in a community area. TOD planning is especially expected to enhance low carbonization, improving the urban climate with compact and efficient land-use design in an area along with public transportation such as railways. However, the comprehensive and interactive methods for the above problems have not been investigated sufficiently. The study proposes a development concept for improving the environmental value and reducing the environmental load. The improvement of the environmental value aims to enrich the greenery around buildings and communities and cause to create a thermally comfortable environment to mitigate patients by heatstroke. The reduction of the environment load will be expected to find out the comprehensive methodology of both the modal-shift from the vehicle-oriented to the public transportation-oriented society and installing low carbon energy systems for all buildings in communities. This study evaluates numerically the network of railway stations along with the Tsukuba Express (TX) line in Japan using the Weather Research and Forecasting (WRF) model with a resolution of 250-m.  The results of this study will be valuable for further studies related to the urban climate, urban planning, TOD, human health, and energy management, as this study is the first numerically and multidisciplinary attempt focuses on transport development and human influences on the local climate and lifestyle. 

High levels of urbanisation, coupled with an increasing trend in extreme weather under future climate change scenarios, combine to create significant challenges to increasing urban resilience for the future (Masson et al., 2020). Urban climate services provide tools to support decision making at a range of scales across the city (Grimmond et al., 2020) and can therefore be used to inform city resilience. This presentation looks at a prototype urban climate service which provides long-term climate change projections at the city-specific scale. The ‘City Pack’ service is a set of factsheets which provide high-level non-technical summaries of climate change projections for an individual city and the science behind them. The audience for the City Pack includes city officials, city planners and the general public. In 2019 the first ‘City Pack’ was co-developed by the Met Office and Bristol City Council. Since then, the template developed with Bristol City Council has been used to develop City Packs for a number of additional cities across the UK. Feedback from this process is ongoing, with initial findings suggesting that the expansion of the City Pack within the UK has been successful. The City Pack is now being upscaled for a number of cities in China under the CSSP (Climate Science for Service Partnership) China Project. Prototype City Packs are currently being developed for the cities of Harbin, Shanghai and Chongqing. The project is seeking to ascertain if services which are co-produced with and bespoke to one set of stakeholders, may provide an equally valuable service for other cities and what support tools need to be in place to ensure effective use and uptake. In doing so, the project is also looking to investigate the ways in which a service may be upscaled to increase the reach and impact of the climate service.

Recent extreme heat events are likely to become more frequent over the 21^st Century and exacerbated in cities due to the urban heat island effect.  Due to high population densities and a concentration of assets, urban areas are more vulnerable to climatic extremes with impacts that traverse health, infrastructure, built environment and economic activity. Recent advances in high resolution modelling enable better representation of urban processes and provide greater understanding of extreme events. By exploiting such advances in underpinning science, the Met Office is generating urban climate services for city stakeholders to plan for and manage heat stress in their city. The Met Office has been engaging with local authorities and city stakeholders in China and the UK to co-produce a prototype, two tier, urban heat climate service to enhance the resilience of urban environments to extreme heat events. The prototype is based on a strong requirement from several cities to develop an evidence base of the heat hazard and understand current and future hot spots vulnerable to extremes of heat within the city. Tier 1 uses observations and high-resolution climate data to provide city specific information of the heat hazard in a graphical factsheet format. This includes information on future changes in temperature, extreme heat indicators, frequency and duration of heatwave events, and spatial distribution of heat across the city. Tier 2 involves working closely with city stakeholders to combine the hazard information with data on health, built environment and socio-economics, to provide tailored information on heat exposure and vulnerability. This will allow users to identify highly vulnerable parts of the city network and neighbourhoods for priority action. This two-tier service can provide an evidence base to inform urban policy, design and adaptation strategies, and prepare authorities and city stakeholders for future demand on city services.

The decision model of household evacuation has been developed and discussed for long decades. The complexity of decision making under uncertainty using weather forecast and early warnings makes the model design so difficult since many levels of factors should be considered and decision path should be clarified. This research aims to construct a structural equation model (SEM) to consider factors accounting for personal cognition on risk information, including individual demographic factors, rational assessment process, psychological responses, social interactions, and cultural backgrounds. We utilize this SEM to inspect the effectiveness of current weather forecast services and flood early warnings in raising risk perceptions and the likelihood of household evacuation for Taiwan and US residents. The research results suggest both countries should use media most trusted to disseminate weather risk information, either TV, broadcast, or social media. TV, broadcast, and social media could increase individuals’ exposure to risk information across lead times. We also suggest individuals read risk information as reminders to inform themselves of risk situations so they could adjust risk perceptions across lead times and make more proper decisions pertaining to household evacuations. Correct interpretation of weather forecasts are essential capacity which should be developed pervasively in both countries, and the needs for customized weather forecasts should be met for weather forecast users in both countries. Weather forecasts are imperfect information with uncertainty and we should emphasize the uncertainty of flood hazards and risk situations at earlier lead time to the general public, and let users understand the chance of potential hazards by reading probabilistic forecasts in addition to deterministic forecasts. With proper interpretation of weather forecasts and early warning by the general public, weather forecasts and early warnings could exert effectiveness in risk management and encourage household precautionary actions at proper and earlier lead time.  

Renewable energy has been increasingly developed and utilized in the recent years; however, the grid-connection and power dispatch scheduling of renewable energy is still a challenging issue because of the intermittent and unpredictable characteristics of renewable energy. High-quality meteorological forecasts play a critical role in renewable energy application and management, such as the unit scheduling for a power system. This study focuses on the evaluation of both forecast quality and economic benefit of the probabilistic forecasts of 100-meter wind speed from WRF ensemble prediction system (WEPS), and the purpose is to help users optimize their decision-making in strong wind situations, which influence the security and service life of wind turbines. The evaluation results indicate：(1) The probabilistic forecasts of 100-meter wind speed from WEPS display more obvious over-forecasting during northeast monsoon periods than southwest monsoon, and over northern Taiwan than the other areas; (2) Both reliability and potential usefulness of the probabilistic wind forecasts are satisfactory; (3) Almost all users can obtain economic values (EV) if they make decisions based on WEPS during the typhoon seasons for perennial time; and (4) Decision-makers can benefit more from the probabilistic forecasts than the ensemble mean forecasts derived from the same EPS because probabilistic forecasts take forecast uncertainty into account.

On 19 April 2019, a mature squall-line mesoscale convective system (MCS) with the characteristics of a leading convective line and trailing stratiform landed on Taiwan, resulting in strong gust wind and heavy rainfall. This squall-line MCS became asymmetric after landfall on Taiwan. There were two asymmetric features discussed in this study: one was the upwind-side asymmetry due to different ridge orientations, and the other was lee-side asymmetry associated with hydraulic jumps.    Two sets of idealized numerical simulations using the Weather Research and Forecasting (WRF) model were conducted to examine the impacts of realistic Taiwan topography on a squall-line MCS. Model results showed numerous similarities between the idealized simulations and real-case observations on 19 April 2019. The low-level Froude number which considered the terrain height (F_mt) was calculated to examine the blocking effect of the Taiwan terrain, and the cold pool (determined by the –2 K isotherm) was found to be completely blocked by the 500-m height contour. The northeast-southwest orientation of the Snow Mountain Range (SMR), and the north-south orientation of the Central Mountain Range (CMR) led to the upwind side asymmetry. On the other hand, the lee-side asymmetry was associated with the different intensities and occurrence locations of the hydraulic jump between the northern SMR and southern CMR, and the Froude number which considered cold pool depth (F_cp) was used to determine flow regimes. The low-level Froude number (F_mt) was determined by the terrain-height and low-level shear. A series of sensitivity experiments were conducted to better understand how the structure of the squall-line MCS varied along with the F_mt. Spatial correlation coefficient was utilized to quantify the degree of MCS symmetry in terrain-height experiments, and the low-level shear experiments were performed to better understand the characteristics of the hydraulic jump. 

System for Convection Analysis and Nowcasting (SCAN) is one of the operational forecast systems used by the Central Weather Bureau (CWB), which can provide the storm cells information by the function of Storm Cell Identification and Tracking algorithm (SCIT). This study presents an 8-year analysis of summer storm cells in Taiwan (from 2015 to 2018, May-Aug) based on the SCIT, discusses the characteristics of cells under different weather systems (synoptic or weak synoptic) and geographical environments (north or south of Taiwan). The results show that the movement of summer storm cells in Taiwan is mostly influenced by topography. Large amount of storm cells are triggered and distributed near the mountain areas. In addition, the lifetime is around one hour, and the maximum reflectivity is concentrated at 45~55dBZ. The statistical analysis also reveals that the one-hour forecast error in the southern region is higher than the error in the northern region, and the error in the synoptic day is higher than which in the weak synoptic day. For storm tracking nowcast, a method of Potential Track Area (PTA) is developed through the statistical results of storm track errors. It is able to define 0-1-hour severe storm warning area and quantitatively improve the warning capability of severe weather. By using the Probability of Detection (POD) to validate the performance, it is found that the PTA can capture the storm cells well in different types of weather systems.

The predictability of precipitation is very low because of its stochastic nature; therefore, the prediction of precipitation beyond 5 days is a big challenge for meteorologists. However, demand for medium- (3-to-10 days) and extended-range (10-to-30 days) precipitation forecasts by potential users in agriculture, forestry, livestock, and water resource management has grown significantly. In this study, a statistical post-processing technique combining similarity matching (SM) and probability-matched mean (PM), called SMPM, is developed to perform bias correction and downscaling of 1-to-14 day precipitation forecasts in Taiwan. The aim is to provide users with more accurate quantitative precipitation forecasts (QPFs) and reliable probabilistic quantitative precipitation forecasts (PQPFs). SMPM searches for the best analogs to the current forecast in a historical set of predictions. Similarity is defined based on large-scale circulation indices instead of precipitation patterns, as the former (1) is much more predictable, and (2) correlates well with local precipitation. The predicted SMPM precipitation forecast ensemble is the observed precipitation patterns corresponding to the historical forecasts that most resemble the current large-scale circulation forecast. For a single value forecast (QPF) with a realistic range of precipitation values, PM is applied on the mean of the forecast ensemble. Forecast evaluation shows that SMPM successfully corrects the precipitation pattern and amount of the raw forecasts, with some fine scale details added. Besides, SMPM significantly improves the accuracy of precipitation forecasts for reservoir water sheds, which helps water-resource management decision making. Also, the reliability of the PQPFs based on the SMPM ensemble is significantly higher than that from the raw precipitation forecast ensemble.  

The purpose of this study is to investigate the impact of assimilating additional polarimetric parameters with reflectivity (Z_H) and radial wind (V_r) in the high impact weather systems. A squall line case forced by the synoptic southwesterly wind and a local afternoon thunderstorm case are selected to conduct the assimilation experiments with WRF-LETKF Radar Assimilation System (WLRAS). In addition, different microphysics parameterization schemes, including GCE, MOR, WSM6 and WDM6, are examined in the experiments. The results in both cases show that assimilating Z_DR in addition to Z_H and V_r with single moment schemes (GCE and WSM6) can capture better raindrop mean size in the analysis field, yet it deteriorates simulated Z_H and K_DP compared with the observations. Differ from GCE and WSM6, assimilating Z_DR in double moment schemes (MOR and WDM6) would not lead to significant deterioration in the simulated Z_H and K_DP. This is because the prognostic hydrometeor variables include both mixing ratio and total number concentration, which provides more correction flexibility in the model. Additionally, the improvement of simulated K_DP in the analysis caused by assimilating K_DP is more obvious in WSM6 and WDM6 scheme than in GCE and MOR scheme. In conclusion, this study illustrates that double moment schemes can be adapted to the extra information from additional polarimetric parameters more flexibly than single moment schemes and might have more benefit in analysis and further improve the quantitative precipitation forecast for the heavy rainfall events.

Recently, South Korea have been suffering from an increasing number of short-duration extreme rainfall events (more than 20 mm/hr) and it is imperative to understand how these extreme events will change in the future. These meteorological disasters usually occur at small spatial (less than 5 km) and short time (hours) scales through the drastically developed local deep convection system. However, regional climate models (RCMs) have horizontal resolution of 12.5 ~ 50 km and utilize convective parameterization schemes, limited for simulating the short-duration extreme rainfall events. In this study, we run a convection permitting model (CPM) for historical and future periods using the CCLM (2.5 km resolution) and examine its performance and projection for the hourly extreme precipitation. Results from RCM runs (25 km resolution) which provide lateral boundary forcings to CPM runs are compared to identify CPM’s added values. The present-day simulations indicate that CPM can reproduce the observed hourly extreme precipitation intensity for given temperature ranges (from 8 to 28°C) and also capture the observed extreme precipitation-temperature (P-T) scaling, which overall follows the Clausius-Clapeyron relation. In contrast, the RCM run underestimates extreme precipitation intensity at temperatures above 18°C, more strongly at higher temperatures, resulting in a much weaker P-T scaling than the observed. Under the global warming scenario (RCP8.5), CPM projects an overall increase in extreme precipitation intensity over South Korea, which is stronger than the corresponding RCM simulation. CPM runs show that the P-T scaling will remain in a warmer world with an extension of the P-T slope into high temperatures, indicating the increased occurrence of short duration extreme precipitation events. The role of precipitation type (convective vs. large-scale) in the present-day and future P-T scaling will be discussed based on the evaluation of convective available potential energy (CAPE).

The urban heat island (UHI) is one of the most well-known urban climate phenomena. Recently, as opposed to UHI, the urban cool island (UCI) phenomena with lower daytime temperature in high-rise building areas than suburban have been reported. So far, not many studies have investigated the relationship between UCI phenomena and precipitation. Thus, in this study, we examined the effect of the urbanization factor (i.e., anthropogenic heat flux (AH), building height (BH)) that can affect UHI and UCI on urban precipitation by using WRF coupled to SLUCM. The AH experiments consisted of four types (CTRL, AH25, AH75, AH225) with hourly maximum AH prescribed 0, 25, 75, and 225 W·m^-2, respectively. The AH increased urban and downwind area precipitation, especially during the daytime. The AH is added directly to the sensible heat flux, which increases surface temperature, especially during the daytime, associated with the UHI. The surface heat is then transferred throughout the planetary boundary layer (PBL) by turbulence, which increases air instability. The BH experiments consisted of three types (CTRL, BH12, BH18) with BH of 7.5, 12, and 18 m, respectively. In the BH experiments, precipitation as well as surface temperature increased during the nighttime but increased during the daytime. The ground heat flux increased during the daytime and decreased during the nighttime as the BH increased and the sensible heat flux changed in the opposite direction to the ground heat flux for energy balance. The ground heat flux can also explain the phenomenon of UCI in areas where high-rise buildings are concentrated. Thus, increasing BH resulted in a decrease in the surface temperature during the daytime due to the thermodynamic factors and stabilizing the atmosphere throughout the PBL, causing reducing precipitation. The AH and the BH played a role in alleviating changes in precipitation during the daytime.

Diurnal cycle of precipitation over the Indochina Peninsula during the South East Asian summer monsoon season was examined by using non-hydrostatic (5km grid), and convection permitting (2k grid) regional climate models (NHRCM). Our results indicated that those fine grid models lead better performance to represent diurnal cycle of precipitation due to realistic representation of geographical distribution. The models successfully simulated the local circulation corresponding to the intensification of precipitation. They are consistent with the satellite-based observed diurnal cycle of the precipitation. The model simulation indicates that convergence area over the mountain on the south of Khorat Plateau occurred in the afternoon in association with the occurrence of precipitation. This migrated northward and contributed to the precipitation peak over the plateau at the night time. The models outperformed parent model MRI-AGCM in terms of the timing of diurnal peak of precipitation and total amount of precipitation, which is typical added value in the dynamical downscaling. Bias correction was also applied to the model results to study potential impact of climate change.

Current climate models often have significant wet biases in the Tibetan Plateau and encounter particular difficulties in representing the climatic effect of the Central Himalaya Mountain (CHM), where the gradient of elevation is extremely steep and the terrain is complex. Yet, there were few studies dealing with the issue in the high altitudes of this region. In order to improve climate modeling in this region, a network consisting of 14 rain gauges was set up at elevations > 2800 m above sea level along a CHM valley. Numerical experiments with Weather Research and Forecasting model were conducted to investigate the effects of meso- and micro-scale terrain on water vapor transport and precipitation. The results show that the simulations with high horizontal resolution, even without the Turbulent Orographic Form Drag (TOFD) scheme, can not only increase the spatial consistency (correlation coefficient 0.84–0.92) between the observed and simulated precipitation, but also considerably reduce the wet bias by more than 250%. Adding the TOFD scheme further reduces the precipitation bias by 50% or so at almost all stations in the CHM. The TOFD scheme reduces precipitation intensity, especially heavy precipitation (> 10 mm h⁻¹) over high altitudes of the CHM. Both high horizontal resolution and TOFD enhance the orographic drag to slow down wind; as a result, less water vapor is transported from lowland to the high altitudes of CHM, causing more precipitation at lowland area of the CHM and less at high altitudes of CHM. Therefore, in this highly terrain complex region, it is crucial to use a high horizontal resolution to depict mesoscale complex terrain and a TOFD scheme to parameterize the drag caused by microscale complex terrain.

This study provides an example of application of radar-based rainfall estimates for water hazard mapping and disaster risk communication. It is a prototype activity in the Borderless Radar Information Networking over South and Southeast Asia (BRAIN) project. This study investigates rainfall and its social impacts in the Kuma River basin flowing through Kumamoto Prefecture in Japan during the torrential rainfall event in July 2020. Using the Radar/Raingauge-Analyzed Precipitation product by the Japan Meteorological Agency (JMA), catchment-mean rainfall values are computed at all places (10,487 grid points) in the river basin and at the time scales from 1 hour to 48 hours for the 17-year period from 2004 to 2020. Then, probability density functions (PDFs) of catchment-mean rainfall are derived at each grid point and at each time scale; using the PDFs based on past records, catchment-mean rainfall values during the torrential rainfall event are converted into return periods as an index of rareness of rainfall. The return period values can be summarized as a geographical pattern of the maximum return period of catchment-mean rainfall during the event and in the 48 time scales. This geographical pattern clearly shows the locations of dangerous places with long return periods where embankment break, overtopping or inundation was confirmed at 35 points. The simple mapping of water hazard proposed in this study uses rainfall and flow direction data only. The latter flow direction data are available at any river basins over the globe. And thus, it is easy to apply this methodology in many countries and regions where long-term past records of rainfall are available. We call this methodology the Simple Water Hazard Mapping (SimpleMap). Outputs of the SimpleMap show simple information about rainfall. Therefore, they can be quite easily understood. It is an essential point in disaster risk communication. 

Raw outputs from Global Climate Models are hardly efficient in climate change impact assessment at catchment scale. In this study, departing from the conventional Top-Down model, a Bottom-Up approach is adopted to identify the changes in hydrological responses of the catchment due to changes in climate and land use. Climatological parameters (precipitation and temperature) have been analyzed for the period 1901-2013 and statistical measures like standard deviation, skewness, kurtosis, anomalies are calculated. The Mann-Kendall’s test and Sen slope analysis were used to check if any trend present in the datasets. Critical thresholds of climatic parameters and land use change are estimated to be classified as vulnerable for each hydrological indicator. The vulnerability index is chosen as the maximum acceptable change in climate and vegetation beyond which the hydrological responses turn out to be vulnerable. A correlation is established between these indices and watershed characteristics like topography, land use, and soil moisture. The RISE model setup was used for rainfall-runoff modelling and simulation of streamflow in daily timescale. Vulnerability of two year return period flood is quantified in response to various factors like wet spells, seasonal rainfall, vegetation condition, soil condition, proceeding drainage. Interaction between flood and its driving factors has been addressed with the help of comparative hydrology over a large range of watersheds. For generalization of the approach, fifty-six sub basins of the Brahmaputra river basin have been explored. Errors can be avoided up to great extent using this strategy because the impact assessment is independent of future projections of change drivers. Thus it sets a hope for water resources planners and managers to take more accurate decisions in ungauged basins in spite of large uncertainty.

Our previous research confirmed the high reliability of inundation pattern analysis using MODIS reflectance data, even for local inundation in Bangladesh. We found that waterlogging flood was associated with prolonged monsoon-inundation and local rainfall. Present research targeted to explain how waterlogging flood inside several polders on south-western parts of Ganges-Brahmaputra delta is related with local rainfall, monsoon inundation, water discharge rate and water level at distributaries related to targeted polders from the year 1970 to 2019. To detect temporal evolution of inundations and waterlogging flood, we will utilize Landsat reflectance data. Reliable seasonal rainfall data, water discharge ratio data and water level data for targeted rivers from 1970 to 2019 will be used to see the relationship of waterlogging flood. Several Tidal River Managements (TRM), a community-oriented solution for waterlogging flood, implemented by government agencies to solve this waterlogging flood on south western part of the Ganges Brahmaputra delta that are likely continued to further north.  But previously some protests had been arisen from the stakeholders (villagers, land owners, local elites) during and after implementation of TRM. Thus, our research includes community’s historical adaptation and perception to solve waterlogging flood other than TRM. Primary observation of the area and perception of the stakeholders confirmed the existence of waterlogging even in January 2020 and they are about to loss this year rice production. And they might accept the alternative of TRM only if the solution will not harm their crop and fish cultivation. The result may be helpful for policy makers.      

Bhubaneswar, the eastern recently developing city of India, has experienced rapid urbanization since 2000. The city has also witnessed heavy rainfall events that have been exhibiting spatiotemporal variability. The pre-monsoonal (March-April-May) rainfall events over Bhubaneswar city taking the India Meteorological Department (hourly station and daily gridded) datasets has been studied. The data is analyzed for the 1980-2018 period (39 years). Wavelet and trend analysis for temporal changes of rainfall reveals that the intensity of precipitation has increased over the study period; which is about 0.4 mm/season. The increase in the rainfall is preferentially high over the city and along the right side of the city compared to the left side of the city. To examine this type of variation in rainfall, a supervised classified land-use-land-cover (LULC) map of the Bhubaneswar region has been examined for 1980, 1990, 2000, 2010, and 2019 years. To produce these LULC map, cloud free Landsat imageries has been downloaded from United States Geological Survey. From the analysis, it is found that the urban built-up area is increasing over the region throughout the study period and the increment is about 100 km² from 1980 (22.5 km²) to 2019 (122 km²). There is a positive correlation with increase in urbanization and rainfall over Bhubaneswar and this correlation is also increasing with time.

Prediction of lightning is an area of interest and research for the decades. The study evaluates the relationship between lightning flash occurrences and the rate of change of stability indices for 17 years (1998-2015) over Bangladesh. In addition lightning climatology (1998-2015) and stability indices climatology for the same time period are studied to locate the hot spot over Bangladesh and its seasonal variation. A climatological study shows that lightning flash rate shows highest magnitude over North-East part of Bangladesh during pre-monsoon season. Lightning Imaging Sensors (LIS) on board Tropical Rainfall Measuring Mission (TRMM) derived lightning flashes (1998 to 2015) are analyzed and correlated with the JRA-55 reanalysis data derived Instability indices (Showalter Stability Index, Total Total Index, K Index, Precipitable Water, Cape, Mean Shear, Storm Relative Environmental Helicity, Vorticity Generation Parameter) to investigate the association among them. A brief spatial and temporal relationship between lightning flashes count and stability indices over Bangladesh are explored. A threshold analysis of stability indices based on K-means clustering technique is constructed to forecast the lightning flashes intensity.  

Lightning is a dangerous natural hazard and major concern of for the death of people and property loss. Due to heavy intensity lightning in Bihar region which kills around 120 people in less than 3 days in June month. The climatology of mean lightning flash rate for the global level is already produced but the detailed analysis of over India is not properly studied. In this study, Lightning climatology for the period of 17 years from 1998 to 2014, over India region by using Lightning Imaging Sensor (LIS) of 0.1° × 0.1° very high spatial resolution of Tropical Rainfall Measuring Mission (TRMM) satellite. The detailed analysis and comparison of these climatology has been studied with different resolution datasets of LIS-OTD sensor of satellite TRMM which are Low resolution (2.5), High resolution (0.5) respectively. Diurnal, monthly, seasonal and annual variations in the occurrence of lightning flashes rate density has also been analysed. This study has been focused on different aspect such as change in the lightning flash rate density with respect to current scenario with previous years to find out the hot spots over different regions of Indian land mass. The diurnal lightning event is mainly occurred in the afternoon/evening time duration. The highest lightning occurred in May Month and least in December. The distribution of lightning flash counts by season over India landmass is mainly in pre-monsoon (March-May) and monsoon (June-Sept) and decreased afterwards. Spatially, the distribution of lightning flashes at North Eastern region along Bangladesh, Jammu& Kashmir (South western region) border with Pakistan and Shivalik Himalaya (Himalayan foothills). Also, further work is to investigate trends in the lightning flash rate frequency, intensity and temporal shifting changes over the India, which will be helpful in better understanding of Lightning events. Keywords: LIS-OTD, TRMM, Lightning flash density, Trend analysis, Climatology. 

Understanding changes in subdaily rainfall extremes is critical to urban planners for building more sustainable and resilient cities. This study investigates changes in extreme hourly precipitation (EXHP) over eastern China, and relevant physical mechanisms as related to urbanization through observational analysis and convection-permitting modeling. Results show that statistically significant increases of EXHP occurrence frequency during the rapid urbanization period (since mid-1990’s) contribute to higher annual amounts of both total and extreme precipitation over the major urban agglomerations in coastal China, i.e., the Pearl River Delta (PRD) and Yangtze River Delta (YRD), as compared to the pre-urbanization era (early 1970’s to mid-1990’s). This suggests a possible link between the enhanced short-term rainfall and the rapid urbanization. An analysis of a large ensemble of EXHP events over the PRD and YRD reveals rainfall intensification over the urban agglomerations by the strong urban heat island (UHI) effect under varying synoptic backgrounds and seasons, especially over the inland urban regions where the major cities are distributed. Real-case and idealized WRF simulations indicate that the UHI effect not only helps convection initiation (CI) over the major cities, but also enhances downstream precipitation through the convectively generated cold outflows that induce downstream CI. Subsequent convection development and rainstorm merging lead to EXHP over the urban agglomerations with abundant moisture supply by monsoonal airflow and sea breezes. Such “relay transmission” caused by cold outflows could play a more important role in EXHP production over a large-sized urban agglomeration with many scattered cities (such as YRD) than an isolated city.

This study shows the observational evidence of the urban heat island (UHI) impact on radiation fog formation and development. The observation campaign was conducted in Tsukuba city, Japan, from October to December 2019. This is the first time that the radiation fog was observed together with air temperature, relative humidity, and wind, both inside and outside a city. The observational results show that the UHI affect can suppress the formation of radiation fog. During the clear night when radiation fog occurred, the fog is observed to become denser in the suburbs, lighter or not to occur over the city. The difference of surface air temperature between urban and suburban areas explain the difference in the fog distribution. On the other hand, during the cloudy night when radiation fog occurred, the urban-rural difference of fog was not observed. There was also no temperature difference between city and suburbs.

The sea breeze is a common phenomenon in coastal cities, but its cooling effect has not been well investigated. In this research, we firstly propose a metric of sea breeze cooling capacity (SBCC) to quantify the cooling effect of sea breezes in a coastal city, Adelaide, Australia. Based on data from the Adelaide urban heat island monitoring network in 2010–2013, we reveal the temporal and spatial patterns of SBCC in summer days at different spatial scales (the Adelaide Central Business District (CBD) and metropolitan Adelaide) and explore their associations with environmental variables. The results at the CBD scale (~3 km × ~4 km) show that the spatial variability of SBCC is explained by distance towards the coast, frontal area index (FAI), terrain ruggedness index (TRI) and temperature prior to the sea breeze onset. Specifically, SBCC is negatively correlated with FAI and positively correlated with TRI. Future development of high-rise buildings in the Adelaide CBD can lead to changes in both FAI and TRI. It is estimated that the projected building development may cause a change of SBCC ranging from −195 to 143 °C·h over an average summer. At the scale of metropolitan Adelaide (~25 km × ~20 km), most of the area is covered with single- or double-storey houses and the most influencing static environmental factor is the topography. Based on the declining trend of sea breeze cooling during the inland penetration, we estimate that the mean penetration distance for all sea breeze days is about 42 km. However, for heatwave days, the average inland penetration of sea breeze cooling is about 29 km, much shorter than other sea breeze days. This study has great implications on urban heat mitigation for coastal cities where a large number of people reside. 

This study investigates the impacts of urbanization on the past (from 1920s to 2010s) and future (from 2010s to 2030s) urban island (UHI) effect over the four greater metropolitan areas of the Southeast Asian capitals such as Jakarta, Manila, Bangkok, and Hanoi. Additionally, we investigated the urbanization impacts on precipitation in rainy season for the four mega-city cases. These impacts are compared with the two greater metropolitan areas of an East Asian capital, Tokyo. We use a dynamical downscaling method with a regional climate model coupled with an urban canopy model, WRF/UCM. A unique aspect of this study is that the past urban expansions estimated from the old maps in early 20 century. Another unique aspect is that future urban expansions estimated by the land use model are considered.

Present research investigates the climatic impacts of forthcoming urbanization over Mumbai Metropolitan Region, India using WRF 3.6.1 model. Primarily, by keeping fix metrological conditions, two numerical simulations (curr_exp, fut_exp) were conducted by incorporating 2018 and 2050 land-use/land-cover pattern. Then the spatial and temporal changes in surface air temperature, wind speed and thermal discomfort were assessed by comparing the simulated results of curr_exp and fut_exp. Furthermore, to remediate the adverse microclimatic impacts of future urbanization, mitigation-strategy was designed and implemented in third experiment (miti_exp). Simulation results show that, due to forthcoming trend of urbanization the average maximum (minimum) surface air temperature of the region would increase by 1.41 ºC (1.27 ºC) approximately. However, if we adopt the mitigation-strategy then this growth can be restricted to 0.69 ºC (0.92 ºC). In case of thermal comfort, in future additional 20% of the total area can undergo to hyper-thermal level. Though implemented mitigation-strategy is able to restrict the increasing temperature but it is ineffectual to minimize the thermal discomfort level. Outcomes of the study also implies that by 2050 suburban areas located around the eastern part of the metropolitan region are more liable to the alterations in thermal environment than core areas like Mumbai.

We developed a high-resolution emission inventory for Hanoi and the coal-fired power plants located in the north of Vietnam for 2017 and 2018, at a horizontal resolution of 1km for air quality modelling studies. The results for 2017 showed the total emissions of pollutants were 26.5 Gg of PM_2.5, 2.8 Gg of BC, 6.0 Gg of OC, 135.1 Gg of NO_x, 61.3 Gg of SO₂, 95.9 Gg of NMVOC, 22.8 Gg of NH₃, 34.9 Gg of CH₄, and 369.8 Gg of CO. For the entire emission inventory, industry was the main contributor to PM_2.5 emissions with 34 %, followed by crop residue burning (30.3 %), and transport (22.7 %). BC emissions were mainly contributed by transport (58.5 %). OC was mainly emitted by crop residue burning (53.7 %). NO_x was mainly emitted by power plants (61 %). On the other hand, power plants contributed 67.9% to the emissions of SO₂. Transport was the main source of NMVOC, contributing 46.5%. Emissions from gas stations made up 3.1% to the emission of NMVOC. The major NMVOC species were benzene, toluene, ethylene, ethane, and acetaldehyde. These species were mainly emitted by transport, residential sources, and solvent-containing products. NH₃ and CH₄ were mainly emitted by the agricultural sector which contributed 84.9 % and 83 %, respectively.  CO was mainly emitted by the transport sector (61.9 %). In Hanoi, SO₂ was mainly emitted by industries with 89.7 % contribution. On the other hand, transport was the main emission source of NO_x (71 %). We also developed temporal profiles for the emissions in Hanoi, which include diurnal, day-of-week, and monthly profiles. The emission developed in this study will be a good indicator of the key emission sources in Hanoi. This will also help to improve air quality modelling studies in Hanoi by providing better input data. 

Urban dwellers in many countries suffer from dreadful summer heat. In 2018, Japan experienced the record breaking number of heatstroke patients and more than 90 thousand citizens were raced to hospital. Heatstroke is not inevitable illness and we can prevent such disorder by appropriate actions of each citizen such as escaping from hot environment, resting in cool area, liquid intake, etc. An appropriate warning system on heat-related risk can encourage such citizens’ actions. For that, dense monitoring system of microclimate in cities is useful. Globe anemo-radiometer, GAR is an original sensor of the lead author, which can measure wind speed (U), short and longwave radiation (S and L) with three compact spherical-shaped thermometers. The features of the GAR are low cost, low power, compact, and omnidirectional. Since the GAR is based on the heat balance of the thermometers, accurate air temperature is necessary for measuring U, S and L. We upgraded GAR so that the sensor measures air temperature as well as U, S, and L. The upgraded sensor consists of three compact spherical-shaped thermometers (4 mm in diameter) and multiple infrared thermometers. With the output of the infrared sensors, the incoming longwave radiation to spherical thermometers is calculable. Then air temperature, U, and S are obtained as solutions of three heat balance equations of the spherical thermometers. The upgraded sensor required no forced ventilated radiation shield for accurate air temperature, thereby contributing to further low power consumption. With the developed sensor and Low Power Wide Area network module, we prototyped a wireless sensor network. This monitoring network will be deployed in Kumagaya city in 2021 summer for heatstroke risk monitoring system; Kumagaya recorded 41.0℃ air temperature in 2018 and is considered the hottest cities in Japan. The principle and the performance of the wireless sensor device will be presented.    

With increasing interest in urban meteorology and related services (Baklanov 2018), the need to appropriately represent urban environment in climate and weather models is given. These (regional) weather/climate models typically use a horizontal grid resolution of O (1) km, which is not sufficient to resolve the flows around buildings. The effect of the urban environment on the atmosphere above in such cases is represented through a bulk approach using the so-called Urban Canopy Parameterization (UCP) schemes (Grimmond et al. 2010). All existing UCPs use the repeating canyon-roof representation, which assumes homogeneous distribution of building within the grid box. Although not discussed exclusively, it is commonly accepted that the assumption of homogeneity holds at a resolution of O (1) km. However, the regional models are gradually approaching towards city-scale modelling employing grid resolutions of O (100) m (Leroyer et al. 2014, Boutle et al. 2016, Simon-Moral et al. 2020), where we believe that the use of existing UCPs is questionable. We call this resolution range spanning from a few hundred meters to tens of meters (i.e. building resolving-scales) as the building grey-zone following Barlow et al. (2017). In this work, we show that the assumption of homogeneous distribution of buildings indeed does not hold at resolution of O (100) m for the city-sate Singapore. To understand the possible influences of the use of a grid resolution where the UCPs are not valid, we propose a technique that allows us to estimate the parameterized fluxes from a typical UCP at different grid resolutions while keeping the same atmospheric grid. This is achieved by using the concept of a physics-grid used in the climate models to estimate parameterized fluxes in an atmospheric column (Dipankar and Stevens 2013, Herrington et al. 2019). Numerical results show variations of temperature and wind across different resolutions. 

An objective front detection method is applied to ERA5, CMIP5 historical, and RCP8.5 simulations to evaluate climate model performance in simulating front frequency and understand future projections of seasonal front activities. The study area is East Asia for two natural seasons, defined as winter (December 2nd –February 14th) and spring (February 15th –May 15th), in accordance with regional circulation and precipitation patterns. Seasonal means of atmospheric circulation and thermal structures are analyzed to understand possible factors responsible for future front changes. The front location and frequency in CMIP5 historical simulations are captured reasonably. Frontal precipitation accounts for more than 30% of total precipitation over subtropical regions. Projections suggest that winter fronts will decrease over East Asia, especially over southern China. Frontal precipitation is projected to decrease for 10-30%. Front frequency increases in the South China Sea and tropical western Pacific because of more tropical moisture supply, which enhances local moisture contrasts. During spring, southern China and Taiwan will experience fewer fronts and less frontal precipitation while central China, Korea, and Japan may experience more fronts and more frontal precipitation due to moisture flux from the south that enhances 𝜽𝒘 gradients. Consensus among CMIP5 models in front frequency tendency is evaluated. The models exhibit relatively high consensus in the decreasing trend over polar and subtropical frontal zone in winter and over southern China and Taiwan in spring that may prolong the dry season. Spring front activities are crucial for water resource and risk management in the southern China and Taiwan.

Wildfire activity is strongly influenced by climate/weather, fuel, ignition agents and human activities. Weather/climate is the most important factor to affect the wildfire activity when fuels are abundant. Observational and numerical studies have shown human-induced climate change leads to an increasing trend of wildfire activity and severity in western boreal North America. Warmer and drier climate is favorable for the occurrence of wildfire activities, which could cause the increase of smoke aerosols and worse air quality. This study investigates the impact of changing climate on biomass burning emissions over western US by building a regression model among meteorological fields, Canadian Fire Weather Index (FWI), and biomass burning emission during 1981-2019 using a machine learning approach. The meteorological fields are taken from the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) reanalysis and are further used to calculate the FWI to characterize wildfire activity. The meteorological increment is calculated from the time-slice High Resolution Atmospheric Model (HiRAM) simulations for current climate conditions (2005-2010) and future climate conditions (2095-2100, under the Representative Concentration Pathway (RCP) 8.5 scenario) and is added to the MERRA-2 meteorological field to present the pseudo global warming impact. The biomass burning emission data taken from MERRA-2 reanalysis is compiled from satellite-observed fire radiative power and fire locations. The regression model built in this study can explain 37-82% of the variance in monthly biomass burning emission over western US and shows the projected increase in biomass burning emission by about a factor of 1.9-4.7 over regions of Pacific Northwest, Nevada semi-desert, Desert Southwest, Great Plain, and Rocky Mountain Forest. The results highlight the potential increase of wildfire activity in extreme fire weather and could contribute toward improving fire weather predictions and mitigating fire prevention policy.

The damage caused by tropical cyclones depends on where they made landfall, the strength of the storms, and how long the tropical cyclones lasts, with an outsize effect on certain countries based on geographic location, landmass, and topography. In the case of a drastically smaller country, such as Taiwan, tropical cyclones have a much larger impact on the country as a whole. This due to several factors including its small landmass, geographic location in the West Pacific makes it a prime location for typhoons, and its topography allows for these rainfall events to have a lasting effect on its climate. A tropical cyclone in Taiwan can not only produce extreme rainfall, but induce mudslides and have lasting economic damage to the people of Taiwan, as these large tropical cyclones affect the whole island, not one specific area. The overarching goal of this study is to understand near-Taiwan tropical cyclone tracks in present-day versus projected future climate.  The National Science and Technology Center for Disaster Reduction (NCDR) conducted dynamic downscaling HiRAM using 5km WRF simulations to model typhoons impacting Taiwan in the present climate and in a future climate scenario.  The present climate simulations run from 1979 to 2015 and consists of four members with prescribed SSTs.  The future climate simulations run from 2079 to 2100 using the RCP8.5 scenario and consists of 16 members with four SST schemes. A statistical analysis is conducted.  The simulated storms are sorted into categories, landfalling/non-landfalling and into different track types (north, central, south) depending on where they made landfall or whether they passed north or south of Taiwan.  Extreme cases in both climates will be identified and then analyzed. 

This study aims to use the rapid-update analysis derived from the WRF-LETKF Radar Assimilation System to investigate the development of strong convective activities that lead to heavy rainfall over northern Taiwan on 8 September 2018. The convection development involves multi-scale interactions among the frontal system, afternoon thunderstorm, and tropical cyclone, and the topography effect. The environmental factors are identified by comparing the WLRAS analysis with the forecast without the convective-scale corrections. In the frontal area north of Taiwan, the analysis captures the enhancement of prefrontal southwestern flow, which contributes to the frontogenesis, and also provides favorable environment for heavy rainfall in the frontal zone. The adjustment of the northeastern and southwestern flow in the mid-lower altitude not only improves the frontogenesis but also builds the tilting structure, leading to further development of the convection along the frontal zone. The northwestern flow in the area of local thunderstorm over northern Taiwan is related to the front movement, which is captured by the analyses. At the same time, the easterly flow induced by the tropical cyclone southeast of Taiwan converges above the mountain range of Sylvia. A condition of low-level convergence and mid-upper level divergence maintains a favorable condition for thunderstorm development. The interaction between the thunderstorm and front helps encourage more thunderstorms and it is essential that the outflow of the previous thunderstorm can be represented in the analysis. In conclusion, the WLRAS analysis well represents the dynamic and thermodynamic condition for developing strong convection over norther Taiwan.

It is shown that the Mei-Yu jet/front affecting the Taiwan area on 6-7 June, 2003 during the early summer rainy season exhibits baroclinic charactistics as found in recent studies.  Appreciable horizontal temperature gradients exist within the frontal zone, especially below the 850-hPa level and above the 400-hPa levels as the cold, dry postfrontal northeasterlies from the Asian continent advance southeastward behind an upper-level tough and converge with warm, moist southwesterly monsoon flow from the subtropical ocean.  It has a marked northward vertical tilt with a frontal slope ~ 1/100.  A thermally direct circulation across the jet/front system with ascending motion within the prefrontal warm, moist air and descending motion within the postfrontal cold, dry air is evident. On 7 June 2003, widespread heavy rainfall (> 300 mm day^-1) occurred over southwestern Taiwan.  In addition to the subsynoptic low-level jet (SLLJ) associated with the jet/front system, a marine boundary layer jet (MBLJ) exists upstream of the southwestern Taiwan over the northern South China Sea (NSCS). The Integrated Vapor Transport (IVT) from the surface to the 850-hPa level by the MBLJ > 400 kg m^-1 s^-1 brings in the moisture over the Taiwan area. The MBLJ is formed due to large pressure gradients between a developing subsynoptic cyclone within the Mei-Yu front over the southern China coast and the West Pacific Subtropical High (WPSH). 

Heavy rainfall event occurred at the northern coastal area at Taiwan on 2^nd June 2017. This event occurred in the Mei-Yu season. The synoptic environment over Taiwan showed that upper level divergence providing favorable condition for low-level convection development. southwesterly monsoon, which came from Indo-China peninsula with high equivalent potential temperature and unstable air flow, enhanced the convective precipitation. Meanwhile, a frontal system gradually approaching the northern coastal area of Taiwan. A strong radar line echo arrived at 2^nd June 03 LST and stayed at coastal area until 12 LST. The maximum daily accumulated precipitation is 645.5mm.  This study used Weather Research and Forecasting Model simulated this event and to get higher temporal and spatial resolution data for analyzing. The result of control run (CTRL_run) showed high consistency with the observed daily precipitation. We compared the vertical water vapor flux from total vertical motion with upper motion by orographic effect, and the result showed that there was high vertical flux (>60 gkg^-1．ms^-1 ) in the convective system. The two orographic sensitivity experiments were also conducted in this study. One removed Taiwan island terrain (NT_run) and the other removed Young-Ming mountain (NY_run). Compare to the CTRL_run, the results of NT_run showed that the convective line moved more southward, the daily rainfall (458mm) was lesser, and the wind over Taiwan Strait was slower. As to the results of NY_run, it showed the same rainfall distribution but less 30mm precipitation than CTRL run. Through the sensitivity tests, results showed that the orographic effect played an important role in the movement of the system. Strong prevailing wind over Taiwan strait brought in a large amount of unstable air parcel and abundant water vapor, facilitated low-level convergence and the development of convective system. 

Drop size distribution (DSD) is an elemental parameter in Precipitating microphysics. The polarimetric radar system provides high temporal and high-spatial-resolution polarimetric data which could be used to retrieve Raindrop Size Distribution (DSD). Retrieving DSDs from polarimetric radar measurements not only can extend the capabilities of rain microphysics research and quantitative precipitation estimation (QPE) but also could be used to analyze the evolution of the precipitating weather system. In this study, three commonly used retrieved methods are compared, namely the μ-Λ method, the fitting method and the variational method. Use idealized experiments to combine different DSD models with different methods, and add variational methods to understand which method can effectively reduce uncertainty and errors in retrieval. The research results show that the variational method can get better results and it is difficult to correctly describe the μ-Λ relationship through second-order polynomial fitting.
On the other hand, the statistical relationship for DSD in previous researches had been classified by different seasons, regions, and rain types. However, seldom research focuses on the Taipei thunderstorm event. In this study, the disdrometer data combine with the polarimetric radar variables has been used to resolve explicitly the evolution of DSDs associated with different microphysics processes. Moreover, we try to categorize the feature of DSD Under the influence of collisional coalescence, breakup, or drop settling processes. In the result of retrieved DSD, the evaporation process can be observed in initial stage. Different microphysical process occurs in mature stage and dissipation stage, coalescence process is the main microphysics process in mature stage.

Northwest Pacific (NWP) tropical cyclones (TCs) impose a severe threat to the life and economy of people living in East Asian countries. The microphysical features especially, the raindrop size distributions (RSD) of TCs that improve the modeling simulation and rainfall estimation algorithms are limited to case studies, and an extensive understanding of TCs RSD is still scarce over the northwest Pacific. Here, we examine a comprehensive outlook on disparities in microphysical attributes of NWP TCs with radial distance and storm type, using long-term disdrometer, ground-based radar, remote sensing, and reanalysis datasets collected in north Taiwan. We find that for a variety of circumstances, the decrease in mean raindrop diameters with radial distance and this association is deceptive in intense storms. Our findings give an insight into critical processes governing microphysical inequalities in different regions of NWP TCs, with implications for the ground-based and remote-sensing rainfall estimation algorithms. 

 The precipitation properties of the North Indian Ocean [NIO: Arabian Sea (AS) and Bay of Bengal (BoB)] tropical cyclones (TCs) are analyzed using ground-based disdrometers installed at two south India stations (Kadapa and Thiruvananthapuram). Four TCs from AS and four TCs from BoB were recorded with the disdrometers installed in Kadapa (14.4742°N, 78.7098°E, ASL: 138 m) and Thiruvananthapuram (8.5335°N, 76.9047°E, ASL: 15 m) observational sites. The distinctiveness in the raindrop size distribution (RSD) characteristics of AS and BOB TCs are detailed. The present study reveals that the raindrops with a diameter greater than 1 mm are dominant in the AS TCs than the BoB TCs. On the other hand, raindrops with a diameter of less than 3 mm contributed primarily to the total number concentration and rainfall rate for both oceanic TCs. The RSDs classified into stratiform and convective types demonstrated the presence of more mid and large size drops in AS TCs than BoB TCs. The polarimetric radar rainfall relations used in quantitative precipitation algorithms are evaluated and assessed for both oceanic TCs. The RSD relations for the rain retrieval algorithms of global precipitation measurement radar are estimated for AS and BoB TCs. Further, rainfall kinetic energy relations that play a crucial role in rainfall erosivity studies are also derived for the NIO TCs.

This study focuses on how aerosols, serving as cloud condensation nuclei (CCN), affect the properties of the summertime diurnal precipitation under the weak synoptic weather regime over complex topography in Taiwan. Semi-realistic large-eddy simulations (LESs) were carried out using the vector vorticity equation model with high-resolution Taiwan topography (TaiwanVVM) and driven by idealized observational soundings. Since the aerosol effects on convection could be specific during different stages of the life cycle, we perform object-based tracking analyses, which diagnose both the spatial and temporal connectivity of convective systems, to highlight the convective clouds that are locked by topography and reduce the stochastic features of convection. The statistical analyses on the tracked extreme convective systems highlight the differences in structural characteristics of convection between the experiments with clean and normal CCN scenarios. For the orographic-locking regime, the effects of CCN on the diurnal precipitating systems are more significant. The precipitation initiation is postponed significantly, which prolongs the development of local circulation and convection. The occurrence of the cloud objects with extreme maximum rain rates doubles. Also, the P₉₉ of the maximum rain rate and the maximum cloud size during the lifetime of the diurnal precipitating systems increase by 16.9% and 6.7%, respectively. This study demonstrates that the object-based tracking analyses which target extreme precipitating systems are useful to investigate the CCN responses on orographic-driven diurnal convection.

Super-droplet Method (SDM) is a Lagrangian particle-based, Monte Carlo stochastic coalescence algorithm developed by Shima et al. (2009). In this method, each super-droplet represents a multiple number of aerosol/cloud/precipitation particles with the same attributes and position. Using SDM, cloud microphysical processes can be represented more accurately and interactions between clouds and aerosols can be also simulated explicitly. In order to find how fine the spatial resolution is required for accurate simulation of marine stratocumulus when using the SDM, a series of simulations based on the DYCOMSII (RF02) setup with different horizontal and vertical resolutions are conducted. The results are compared with that of a double-moment bulk scheme and the model intercomparison project (MIP) results. The horizontal and vertical grid length tested ranges from 25 m to 50 m and from 5 m to 10 m, respectively. Cloud fraction and liquid water path respond to the horizontal and vertical resolutions in opposite ways in the SDM simulations, while the bulk scheme is only sensitive to the vertical resolution. Cloud droplet number concentration (CDNC) is not sensitive to grid resolution in SDM, but in the bulk model, CDNC decreases when the vertical resolution becomes coarser. Numerical convergence of CDNC regarding super-droplet number concentration (SDNC) at different resolutions is also discussed. The result suggests that SDNC as small as 16 super-droplets per grid cell is sufficient. In conclusion, SDM results are in agreement with bulk scheme and MIP results in general. Our preliminary results suggest that 50 m x 50 m x5 m is needed for both SDM and bulk scheme, and 16 super-droplets per grid cell for the SDM. We are now conducting a more detailed analysis and the results will be also presented.

Bulk-type cloud microphysics parameterizations such as Weather Research and Forecasting (WRF) Single-Moment Microphysics schemes (WSMMPs) and WRF Double-Moment Microphysics schemes (WDMMPs) adopt the same ice microphysical processes suggested by Hong et al. (2004). Our study found the truncation error intrinsic to the ice microphysics processes together with the inaccurate calculation of gamma function in WDMMPs and WSMMPs. We investigated the impacts of these numerical errors on the simulated precipitating convections, especially using WDM 6-class (WDM6) microphysics scheme. The simulation cases include the regional climate, snowstorm, and heavy summer precipitation over the Korean peninsula. Among tested cases, the simulated regional climate cases show the significant difference in the simulated precipitation, hydrometeors profile, and radiation budgets between the simulations with and without the correction of numerical errors in WDM6. Cloud ice amount is decreased and cloud water amount is increased in the corrected WDM6. The outgoing longwave radiation at the top of atmosphere and the downward shortwave radiation at the surface are increased overall. These changes are responsible for the decreased precipitation amount, thus improved statistical skill scores. Acknowledgment: This work was supported by the Office of Science User Facility and the National Research Foundation of Korea (NRF) Grant 2019R1C1C1008482 funded by the South Korean government (MSIT). 

This study examines the role played by aerosol in mixed-phase deep convective clouds and torrential rain that occurred in the Seoul area, which is a conurbation area where urbanization has been rapid in the last few decades, using cloud-system resolving model (CSRM) simulations. The model results show that the spatial variability of aerosol concentrations causes the inhomogeneity of the spatial distribution of evaporative cooling and the intensity of associated outflow around the surface. This inhomogeneity generates a strong convergence field and the associated spatial inhomogeneity of condensation, deposition and associated cloud mass, leading to the formation of torrential rain. With the increases in the variability of aerosol concentrations, the occurrence of torrential rain increases. This study finds that the effects of the increases in the variability play a much more important role in the increases in the intensity of mixed-phase clouds and torrential rain than the much-studied effects of the increases in aerosol loading. Results in this study demonstrate that for a better understanding of extreme weather events such as torrential rain in urban areas, not only changing aerosol loading but also changing aerosol spatial distribution since industrialization should be considered in aerosol-precipitation interactions.  

The south Indian state of Kerala experienced a devastating flood during August 2018. It was the worst flood that the state experienced in 100 years. The major cause behind these floods was an extreme rainfall event which flooded 13 out of 14 districts in the state. The highest recorded rainfall occurred within nine days in two intervals. One from 8th to 10th August and another from 14th to 19th August. ERA- Interim data was used to find out the synoptic conditions which prevailed during the heavy rainfall days. A strong westerly jet in the lower troposphere and an offshore trough was observed in the days of heavy rainfall. Numerical simulation was done using the WRF model, with single domain of 25 km resolution. Simulations were done up to 120 hours using four different microphysics parameterizations. Results were compared with the IMD gridded data, ERA-Interim and TRMM data. Results showed that Thompson scheme provided the best results. Therefore, this scheme was used for further analysis. Its impacts on different parameters like horizontal and vertical wind, rainfall anomaly, CAPE etc. were studied. Results showed that the accuracy of the model declined with increase in forecast time. Numerical experiments were performed to investigate the reasons for the anomalous rainfall over Kerala. Study shows that a deflection of Low Level Jet from south-westerly to North-westerly direction and a split in the LLJ core slowed down the flow, and resulted in cyclonic vorticity over land. During the monsoon period, number of typhoons in the western Pacific Ocean was almost double the normal. These effects resulted in slow propagation of rain-bearing monsoon clouds, which precipitated for a long period than usual, and caused heavy flood over Kerala.

Heavy precipitation observes over Kyushu, southwestern Japan, during the Baiu season. Large-scale moisture inflow along the northwestern edge of the North Pacific Subtropical High is a key factor for the occurrence of heavy precipitation over Kyushu as well as the meso-scale atmospheric and orographic conditions. Meanwhile, plateau-scale disturbances coupled with cloud convections form over the Tibetan Plateau (TP) during summer, which sometimes propagate to east and cause flooding of the Yangtze River. Does the eastward propagation of plateau-scale disturbances influence on the heavy precipitation occurrence over Kyushu? To understand this issue, the time evolution of synoptic-scale atmospheric conditions associated with the anomalous moisture transport is statistically investigated by the composite analysis of JRA-55. Heavy precipitation day is defined as a day with area-averaged daily precipitation over Kyushu larger than 1.0 mm and ranked in the top 10 % during Baiu season between 1981 and 2015 (109 cases).Daily precipitation exceeds 100 mm day^-1 over Kyushu during heavy precipitation days. Several days before the heavy precipitation occurrence, the plateau-scale disturbance forms over the TP in association with the surface heating, which is accompanied with the cloud convections. This disturbance maintains and propagates eastward in the mid-troposphere. Then, a cyclonic circulation anomaly forms over the northwest of Kyushu, which enhances moisture transport to southwestern Japan.

Orographically-induced precipitation and meltwater from glaciers in the Himalayas feeds into the headwaters of major rivers such as the Indus, the Ganges, and the Brahmaputra, and provides water resources for the large population of South Asia. The glaciers in the central Himalayas are sustained by summer precipitation, and the diurnal cycle is an important part of the hydroclimate in the Himalayas. However, features of the diurnal cycle that affect precipitation from the foothills to glacierized, high-elevation areas are poorly understood. We investigated the diurnal cycle of precipitation using 3 years of in-situ observations recorded close to a glacier at 4,809 m asl, and 17 years of data from the TRMM PR and the IMERG. The mechanisms that drive the diurnal cycle were examined using hourly ERA5 reanalysis data. In-situ observations showed that the diurnal precipitation cycle has daytime and nighttime peaks. In addition, twice-daily maxima exist in the TRMM PR data, particularly over rain bands at around 500–1,000 m asl, and at ~2,000 m asl. Convective-type rainfall, with a lower rain-top height, occurs in the daytime, whereas stratiform-type rain, with a higher rain-top height, occurs at night, particularly over terrain at elevations above ~2,000 m asl. The effects of land-surface processes cause the two peaks in the diurnal cycle. Daytime surface heating drives upslope flows that promote condensation. At night, surface cooling over the plain to the south of the Himalayas causes low-level monsoon flows to accelerate, creating a nocturnal jet, which results in large-scale moisture flux convergence over the slopes.

East Asia has a complex topography, coastline, and atmospheric phenomena at various scales and regarded as being highly vulnerable to natural hazards because of the increase in climate extremes under global climate change and the large population (Stocker et al. 2014; Kim et al. 2021). The risks associated with some extreme-precipitation-related natural disasters have increased and the response of extreme precipitation in the East Asian monsoon region is among the greatest across all global monsoon regions (IPCC 2013). In this study, observed variabilities and changes in spatial extent of rainfall extremes are investigated using the revised Climate Extreme Index (CEI) (Gleason et al., 2008) to the region of East Asia. The CEI determines the areal extent of climate extremes for a specified region during a given year and is achieved by averaging several components, each identifying the fraction of an area experiencing a specific type of extreme associated with temperature or precipitation (Karl et al., 1996). Using the high resolution CPC Global Unified Gauge-Based Analysis of daily precipitation during 1979~2019, the observed changes in extreme rainfall are analyzed through the three CEI precipitation components: (1) SDII (simple daily intensity index) (2) R95p (very wet days) (3) PRCPTOT (annual total wet-day precipitation). The areal extent, the interannual variations, and the trend of these three components will be presented and compared in the presentation.  Acknowledgement. This work was funded by the NRF and WISET Grant funded by the Ministry of Science and ICT under the Program for Returners into R&D(WISET-2019-535).

The Meghalaya plateau of the Indo-Bangla region is the wettest place on planet earth. During pre-monsoon (March-May), sudden heavy precipitation (HP) (typically > 64.5 mm/day) to extremely heavy (>244.5 mm/day) events in this region can induce flash floods (at a time scale of 6 hours) over eastern and north-eastern India and Bangladesh, causing significant economic losses. It is a challenge to capture these flash floods in this complex hydrographic environment with fine-scale features. It is essential to predict heavy precipitation reliably and accurately at a finer scale too. In this study, an application of the Advanced Research version of the Weather Research and Forecasting (WRF-ARW) is presented for estimating heavy precipitation at a finer resolution for the HP event of pre-monsoon season 2017. The model simulated precipitation is assessed with the available rain gauge observation and the merged datasets of the India Meteorological Department (IMD) and Global Precipitation Measurement (GPM) mission. In our assessment, four different microphysics (MP), two cumulus (CU), and two planetary boundary layer (PBL) parameterization schemes were compared. The Eta (Ferrier) MP, Kain–Fritsch (KF) CU, and Yonsei University (YSU) PBL scheme performed the best to capture the premonsoon heavy rainfall events. The error bar in the rainfall amount is 20 mm. Our model opens up the possibility of accurate flash flood modeling over the region.

The southern state of Kerala, India, experienced an unprecedented heavy rainfall during 1-19 August of 2018 and 2019. It is reported to be the event of one in a 100-year frequency. Huge loss of life and damage to properties was caused due to the extreme rainfall and subsequent flooding over the state. In this paper, we have discussed the possible mechanism and potential of ensemble prediction system based on the globally highest resolution (12.5 km) National Centre for Environmental Prediction (NCEP) Global Forecast System (GFS) model with 21 members. Our analyses bring out a strong association of large-scale moisture convergence in phase with westward propagating Rossby wave that played possible trigger of the extreme events of 2018 and 2019. We have also shown that the deterministic forecast of rainfall has a limited accuracy with a shorter lead time, while the ensemble prediction system has provided much needed longer lead time of the extreme rainfall events. This could be essential for disaster management in such extreme rainfall events.

Tropical cyclones are a very common phenomena in Bangladesh. Along with many other hazards associated with the tropical cyclones, coastal flood is a very disastrous one. Predicting such types of floods are a bit tricky, since the coastal regions get usually inundated due to excessive rainfall during the cyclone events. A very common approach for prediction of coastal floods is to simulate the storm surge and then correlate the surge heights to the prescribed heights of water level to be considered as the danger level for declaring a flood event. A novel approach has been tried and tested in this research. The coupled atmospheric-hydrometeorological model, WRF-Hydro, has been utilized to predict the coastal flood in Bangladesh; with the case of Super Cyclone Amphan being the test case. A simulation period of 168 hours, prior to the landfall of the cyclone, were made. The results show that the model has a gradual increase of accuracy in forecast. The accuracy has been found to be 74%, 79%, 87%, 91% and 94% for 120 hours, 96 hours, 72 hours, 48 hours and 24 hours respectively before the flood activities. The NSE, PBIAS and RSR scores for the simulated results verified that the model performed well for prediction of coastal flood during that time. Therefore, the WRF-Hydro model has a great potential for further uses in future coastal floods owing to the occurrences of tropical cyclones at Bay of Bengal.

Synoptic analysis of the heavy rainfall events of 9-10 August 2011 is carried out using the Weather Research and Forecasting (WRF) model. These excessive rainfall events are found to be localized over many parts of Bangladesh and maximum rainfalls recorded are 254 mm at Hatiya, 218 mm at Cox’s Bazar and 152 mm at Khepupara on 9 August 2011, and 207 mm at Teknaf, 169 mm at Mymensingh and 161 mm at Cox’s Bazar on 10 August 2011 within a span of 24-h. The simulated rainfall is validated with Tropical Rainfall Measuring Mission (TRMM) 3B42RT and observed rainfall data. The simulated rainfall is found to range from 64 to 128 mm per 3 hours. The rainfall rates are comparable with the TRMM rainfall rates. But the model has overestimated the rainfall in comparison with the actual rainfall, having root-mean-square errors of 1.9-31.64 mm and 0.9-28.09 mm on 9 and 10 August respectively. The simulated maximum reflectivity is found to be >50 dBZ near the depression centre and some parts of Bangladesh and the northeast Bay of Bengal. The vorticity is found to be positive over Bangladesh on 9-10 August 2011. The maximum CAPE over southwest Bangladesh and the northeast Bay of Bengal is about 2000-2500 J kg^-1 at 0600 UTC. CAPE is practically absent over the low-pressure system, indicating that the rainfall is caused due to monsoon depression and monsoon flow, and not by thunderstorms or any convective storm. The study reveals that the relative humidity is higher and is extended to greater heights in the coastal stations. The cloud water mixing takes place between 950 hPa and 300 hPa. The Maximum cloud water mixing ratio of 600 mgm^-3 is near the depression centre with greater depth at Khepupara and Rajshahi.

Very Short-Lived Halocarbons have been linked to climate change through their potential to deplete the protective stratospheric ozone layer, influence atmospheric chemistry, and contribute to local weather change and radiative forcing via cloud nuclei formation. Seaweeds are known to be emitters of the short-lived brominated compounds including CHBr₃ and CH₂Br₂ and account to 70% of global bromoform production. The current seaweed industry is expanding globally with doubling in global production in recent year. This could increase the significance of seaweeds in contributing to the regional if not global halocarbon budget. Data from previous small-scale studies on tropical seaweeds in South-East Asia indicates a contribution of 6–224 Mmol Br yr⁻¹. However, variabilities and uncertainties in the current global estimates of oceanic halogen load, derived from top-down and bottom-up modelling, could arise from poor temporal and spatial data coverage, and are commonly attributed to a lack of data for oceanic inputs and under-representation of coastal and extreme emissions. In order to understand how changes in environment could affect the halocarbon emission by farmed seaweed species, we investigated the effect of temperature and the combined effect of varying levels of irradiance and temperature on the halocarbon emission by Kappaphycus alvarezii, a commercially farmed red seaweed in the Coral Triangle. We found that different exposure duration to varying temperature treatments, and the combination of irradiance and temperature affect the halocarbon emissions by K. alvarezii.  

Planktonic picocyanobacterial representatives are abundant and ubiquitous in coastal oceans. The genus Synechococcus is an important player in coastal water by playing a key role in carbon assimilation but its role in mangrove estuaries us not very well understood. In this study, the draft genome of Synechococcus moorigangaii CMS01 has been sequenced which was previously isolated from Sundarbans mangrove ecosystem facing the coastal Bay of Bengal. The genome is approximately 5.5 Mbp in size and contains approximately 0.5 Mbp plasmids. Genome annotation revealed total of 5806 genes out of which 5701 were CDSs. Of these, 5616 coding genes with 5616 protein coding CDSs were identified. Along with genes coding for essential metabolic proteins, transport proteins and other cellular apparatus, genome also codes for proteins involved in flagella and pilus formation which has not been widely reported before in any coastal species of Synechococcus. In silico phenotyping revealed that this species can metabolize growth utilizing carbon sources including sucrose, D-mannose and trehalose. Genome annotation revealed genes involved in photosynthesis including photosystem II reaction centre proteins (psbN, psbH, psbL, psbJ, psbZ, psbQ), photosystem I iron-sulfur centre protein (psaC), photosystem I reaction centre subunits VIII, IX; genes for nitrogen metabolism were also identified. The genome codes for linker polypeptides that are necessary for correct assembly of phycobiliprotein in phycobilisome rods. The presence of many features as identified from the draft genome revealed the adaptative features of this species and its ubiquity in coastal Bay of Bengal including implications for mangrove carbon cycling.

The annual and seasonal changes in the tropical Pacific Walker circulation (PWC) during the Last Glacial Maximum (LGM) are investigated using all available numerical experiments from the Paleoclimate Modelling Intercomparison Project Phases 2 and 3. Compared to the preindustrial period, the annual mean of the PWC intensity weakened by an average of 15%, and both the western edge and center of the PWC cell shifted eastward by an average of 9° and 8°, respectively, as obtained from the ensemble mean of the 16 models used for analysis during the LGM. Those changes were closely linked with an overall weakening of the equatorial Indo-Pacific east–west sea level pressure difference and low-level trade winds over the equatorial west/central Pacific. On the seasonal scale, the LGM PWC generally weakened and shifted eastward throughout the seasons of year. In response to the LGM large ice sheets and lower atmospheric greenhouse gas concentrations, the large-scale uneven surface cooling in the northern hemisphere led to an increased (a decreased) land–sea thermal contrast in boreal cold (warm) seasons. These induced decreases in the North Asian and African monsoon rainfall and hence suppressed a large-scale thermally direct east–west circulation in the two seasons. As a result, the LGM PWC weakened and shifted eastward in both boreal cold and warm seasons, which jointly contributed to the weakening and eastward shift of the annual mean PWC.

Solar Radiation Modification (SRM) has been proposed as a potential option to counteract anthropogenic warming. The underlying idea of SRM is to reduce the amount of sunlight reaching the atmosphere and surface, thus offsetting some amount of global warming. Here we use an Earth system model to investigate the impact of SRM on global carbon cycle and ocean biogeochemistry. We simulate time evolution of global climate and the carbon cycle from pre-industrial to the end of this century following three scenarios: RCP 4.5 CO₂ emission pathway, RCP8.5 CO₂ emission pathway, and RCP 8.5 CO₂ emission pathway with the implementation of SRM to maintain global mean surface temperature at the level of RCP4.5.Our simulations show that SRM, by altering global climate, has a profound effect on the global carbon cycle. Compared to the high-CO₂ (RCP8.5) simulation without SRM, by year 2100, SRM reduces atmospheric CO₂ by 56 ppm mainly as a result of increased CO2 uptake by the terrestrial biosphere. However, SRM-induced change in atmospheric CO₂ and climate has a small effect in mitigating ocean acidification. By year 2100, SRM results in a decrease in hydrogen ion concentration ([H⁺]) by 5%. On the other hand, SRM attenuates the seasonal amplitude of [H⁺] by about 10%. Our simulations also show that SRM slightly reduces global ocean net primary productivity (NPP) relative to the high-CO₂ simulation without SRM. Our offline calculations show that SRM-induced temperature change causes a 8% decrease in NPP and SRM-induced circulation change causes a 6% increase in NPP.

Peatlands cover a small portion of the Earth’s land surface but hold ~30% of soil carbon (C) globally. However, few studies have focused on the early stage of peatland development, which is a key stage in the initial C sink function of peatlands. An immature peatland is vulnerable to changes in environmental conditions, e.g., temperature and water conditions, as the peat accumulation process can be easily interrupted by such changes. It is important to understand how immature peatlands develop, what conditions are beneficial to this process, and the present status of these important peatlands. Plant macrofossil analysis and geochemical characteristics of peat were used to determine the plant succession and the degree of decomposition at two peatlands developing in the Changbai Mountain region of northeastern China. The results show that during the entire plant community succession, plants in the two studied peatlands are mainly characterized by sedges (Cyperaceae) and mosses (mainly Sphagnum). Plant macrofossil analysis reveals a wetter trend in the Yuan Lake peatland in the most upper part of peat layer, which provides favorable conditions for peat accumulation and peatland development. Peat geochemical indices indicate a steady decomposition process during initial peatland formation and relative richness in N and P. Plant composition affects peat quality and decomposition and plant communities reflect variations in moisture. Fire events have great impacts on biogeochemical processes, potentially affecting plant succession and promoting peat decomposition. An increase in major and trace elements suggests only weak disturbance due to the considerable distance to human settlements. This study determines the characteristics of pristine mountainous peatlands and highlights the importance of understanding the regular plant community in the early stage of peatland formation, as well as its potential effects on C sinks.

Northeast China contains the greatest concentrations of mountain peatlands in China, occupying about 6.9% of the national peatland resources, with the majority of these located in the mountainous areas to the north. Most of these are in the permafrost zone south of the Russian boarder. Since the 1970s, there has been a more than 35% loss of permafrost in northeast China and the southern border of permafrost has moved northward 50~120 km in response to regional warming. The projected temperature increases in the coming decades will reduce permafrost area by an additional 28-50%. Understanding the impact of temperature change and permafrost degradation on greenhouse gas emission of peatlands is of critical concern for regional and national carbon assessments. In this study we conducted growing season measurement of whole ecosystem CH₄ fluxes from a permafrost peatland located in the Da Xing’anling Mountains, northeast China. The objectives were to quantify CH₄ fluxes, investigate seasonal trends in the flux and determine the dominant environmental and biophysical drivers of the CH₄ flux for the permafrost peatland. CH₄ fluxes at the peatland had an obvious seasonal trend peaking in the late of the growing season. Maximum instantaneous fluxes were 1.34 g CH₄ m^-2 s^-1 and total seasonal CH₄ emissions were 0.38 to 1.27 g C-CH₄ m^-2. We used path analysis to examine environmental and biophysical drivers of the flux and found that soil temperature and thaw depth were most strongly correlated with seasonal CH₄ variability. Our results suggest that soil warming and deepening of the active layer will increase CH₄ emission.

Nitrous oxide (N₂O) is a potent greenhouse gas and peatland is one of the important sources for N₂O emissions due to its abundant carbon and nitrogen reservoir and unique redox environment. Accurate assessments and modeling of N₂O emissions from peatland are thus important but have remained elusive. A major reason is the high temporal and spatial variability in N₂O emission rates. "Hotspots" are temporally and spatially variable micro-sites in peatland that at a given point in time might be responsible for the majority of N₂O emission. Occurrence of a hotspot in peatland requires an optimal set of physical, chemical and biological conditions. However, these conditions are largely unknown. Extremely high temporal variability in hotspot occurrence, often referred to as "hot moments", makes their identification even more difficult. This study monitored the kinetics of N₂O emission in hotspot and tried to answer the following questions 1) what physical and chemical conditions are needed for a N₂O hotspot to emerge, 2) what microorganisms need to enable the hotspot's functioning. The results showed that N₂O emission in hotspot increased with decreasing pH, increasing temperature and porosity. Thaumarchaeota and Proteobacteria seemed to be responsible for the majority of N₂O emission. These results improve our understanding on the mechanism of N₂O emission in hotspot, and are useful in assessments and predictions of N₂O emissions in peatlands.

The extended Kalman filter is an extended version of the Kalman filter for a non-linear problem. This study applies this extended Kalman filter to the real-time estimation of the parameters of the dual-pol radar rain rate estimator. The estimated parameters are also compared with those based on the method of least squares. As an application example, this study considers storm events observed by the Beaslesan radar in Korea. The findings derived include, first, the parameters of the radar rain rate estimator obtained by the extended Kalman filter are totally different from those by the method of least squares. In fact, the parameters obtained by the extended Kalman filter are found to be more reasonable, and similar to those reported in previous studies. Second, the estimated rain rates based on the parameters obtained by the extended Kalman filter are found to be more similar to those observed on the ground. In conclusion, the extended Kalman filter can be a reliable method for real-time estimation of the parameters of the dual-pol radar rain rate estimator. The resulting rain rate is also found to be of sufficiently high quality to be applicable for other purposes like various flood warning systems. Acknowledgement: This work was supported by Korea Environment Industry & Technology Institute(KEITI) through Water Management Research Program, funded by Korea Ministry of Environment(MOE)(127559)

This study discusses the uncertainties of precipitation forcing inputs from multiple sources, including satellite or satellite-gauge quantitative precipitation estimates (QPEs), and quantitative precipitation forecasts (QPFs) from the global ensemble forecast system (GEFS) and mesoscale weather model WRF. The impacts of multiple precipitation forcing inputs on streamflow simulations are investigated though distributed hydrological modeling over the upper Huaihe River basin.     First, the distributed Variable Infiltration Capacity (VIC) model is used to investigate the impact of multiple satellite QPEs on the daily streamflow simulations. These QPEs include the TRMM/TMPA 3B42RT product, the NOAA/CPC’s CMORPH gauge merged product, and the PERSIANN CDR product. Also, an error correction method – SREM2D (two-dimensional stochastic satellite rainfall error model) has been applied to three selected satellite QPEs to implement streamflow simulations in the VIC model. Overall, SREM2D provides great potential to facilitate the application of satellite precipitation products in water management and decision making over Chinese river basins.      In addition, the impact of bias-corrected global ensemble precipitation forecasts on the improvement of summer streamflow prediction skill is discussed. Ensemble streamflow forecasting is implemented over the study basin using the VIC model, driven by the bias corrected ensemble precipitation forecasts from the GEFS reforecast data. The encouraging results suggest that the reforecast ensemble dataset exhibits a great value to improve hydrometeorological predictions for operational applications.     To further examine the impact of high-resolution QPFs on hydrological processes, the two-way coupled WRF/WRF-Hydro model is adopted to investigate the hydrological feedback on land surface-atmosphere interactions over the study basin. The differences of spatial precipitation patterns in one-way and two-way modelings are highly associated with the prevailing westerly wind and orographic effect. The hydrological effects result in a wetter near-surface air layer and more unstable atmosphere conditions, which may induce more precipitation during rainy seasons.

Extreme Precipitation Events (EPEs) have increased both in frequency and magnitude in India during the past decade. Various Quantitative Precipitation Forecasts (QPF) are available from the Numerical Weather Prediction Models such as the European Centre for Medium-range Weather Forecasts (ECMWF), Japan Meteorological Agency (JMA), National Centre for Medium Range Weather Forecasting (NCMRWF) and UK Met Office (UKMO). Since several QPFs are available with some characteristic difference, their comparative evaluation is vital to identify the most adequate one which can capture reliable information of precipitation extremes in India. Past studies have assessed the performance of QPFs only on the statistical basis and ignored their reliability to represent the distribution of intrinsic spatial structure of extreme precipitation. In this study, the performance of four different QPFs is evaluated to forecast the occurrence of various EPEs in different parts of India during the past decade. The representation of spatial pattern of EPEs is assessed by creating a network among the grids experiencing extreme precipitation using the theory of complex networks. The performance of QPFs is compared to the network created using the available gridded observation data for evaluating their relative accuracy. For this, first a network of rain grids is identified and created on the basis of their occurrence during the past decade. Three measures of CN such as Degree Centrality (DC), Betweenness Centrality (BC) and Clustering Coefficient (CC) are used to quantify different aspects of the internal spatial structure of extreme rainfall during the monsoon months of June, July, August and September (JJAS). The results from the ongoing work will be presented at the conference.

Advances in computing power and data assimilation techniques have enabled numerical weather prediction (NWP) models to issue forecasts at increasingly finer temporal and spatial resolution. High-resolution precipitation forecasts are expected to increase the accuracy of forecasts for floods and high flow events, particularly for rapid response catchments. However, all NWP forecasts contain systematic errors that limit their value for hydrological applications, particularly for flood forecasting. In order to reduce such errors and quantify uncertainties in precipitation predictions, we have developed a method called Catchment-scale Hydrologic Pre-processing of Precipitation forecasts (CHyPP).  CHyPP has been extensively tested for pre-processing precipitation forecasts from low-resolution NWP models in a range of Australian and international catchments. In this study we assess the benefit to streamflow forecasts of pre-processing precipitation forecasts from the high-resolution Australian NWP ACCESS-C (~1.5 km) model compared with low-resolutions ACCESS-R (~12 km) and ACCESS-G (~40 km) forecasts. We generate retrospective streamflow forecasts by forcing a hydrological modelling system with CHyPP forecasts from high and low-resolutions NWP models. The hydrological modelling system consists of semi-distributed hydrological models with GR4H rainfall-runoff model, Muskingum channel routing and the hydrological model error ERRIS.  CHyPP is highly effective at reducing forecast errors and produces reliable forecasts from both low and high-resolution NWP models. Despite the increase in NWP model resolution, we find that CHyPP forecasts from high-resolution NWP model produce streamflow forecasts of equivalent quality of those produced from low-resolution NWP models. In this presentation, we discuss the possible reasons for this. Although the high-resolution NWP model does not offer clear benefits over the lower resolution NWP models, the benefits of high-resolution models are likely to be more evident when modelling hydrological processes at finer spatial resolutions and using high-resolution precipitation observations.

Precipitation is one of the key components of the global water cycle, investigated intensively in many scientific fields. The microphysical characterization of rainfall play an important role in the process of precipitation estimation, remote sensing observations, radio communications, and cloud microphysics. However, few studies in the literature have focused on the large-scale assessment of rainfall microphysics characteristics. Since disdrometers measure raindrop size distribution (DSD) at point sites and ground dual-polarization radars that can be used to estimate DSD parameters are available in limited areas, space-based radars and mesoscale numerical weather prediction models provide the possibility to measure the DSD on a large scale. This study therefore proposes a retrieval scheme of large-scale raindrop microphysics characteristics based on Weather Research and Forecasting (WRF) and Global Precipitation Measurement (GPM) Dual-frequency Precipitation Radar (DPR), and assesses DSD, rain rate (R), kinetic energy and reflectivity (Z) by an impact-type disdrometer over Chilbolton, UK. Results show that both retrieval from the WRF and GPM provide an overall good fit to the reality, indicating the feasibility to use measurement or simulation to obtain raindrop microphysical processes on a large scale, especially that GPM mode has a perfect performance, which based on the measured data. This study can help to the improvement of large-scale rainfall microphysics estimation and provide insight as to large scale extension research of raindrop characteristics like rainfall erosivity estimation and accurate precipitation forecast.

When the research area is local scale or regional, and the data is large scale or global, analyzing regional characteristics with large scale data will cause huge errors. Downscaling is a method which increase the spatial resolution of the data and we will have a deeper understanding and accurate analysis of the research area. The study is aim to perform spatial downscaling of wind-related data (wind speed, wind direction,  etc.). The data we use are GCM historical and future simulation data and regional historical observation data. This research applies Diffeomorphic Dimensionality Reduction (Diffeomap), a nonlinear dimensionality reduction algorithm, to establish the relationship between GCM historical data and regional historical observation data. In addition, this also combines the relationship with GCM future simulation data to estimate the regional future data. At the same time, the goal of this study - downscaling - also achieved. The results provide decision-making units as a reference for future risks.

In mathematics, topology concerns about the invariant features under continuous deformation (i.e. stretching, bending, or twisting), for example, compactness and connectedness, which is different from the geometrical properties like length and curvature. For data analysis, the properties of topology make it more robust to noise and sufficient for complex datasets. As a result, our study applied the topological data analysis in the large-scale climate system, the Pacific. The Pacific Ocean covers almost one-third of the earth and more than 30,000 islands within. The climate system here is complex and chaotic, such as trade wind, South Pacific Convergence Zone (SPCZ), and El Niño Southern Oscillation (ENSO). In our study, we quantified the climate characteristic by topological data analysis strategies including Betti numbers, Euler integral, and persistence homology, providing new information for the Pacific hydrology.

Despite having a subtropical climate, typhoon-induced precipitation in Taiwan rarely occurs between November and May. Therefore, water scarcity caused by the uneven seasonal rainfall distribution results in reducing or suspending water supply for irrigation purposes, especially in Taipei, Taoyuan and Hsinchu. Keeping sufficient water levels in the reservoirs and decreasing the likely impact of the drought in these areas have become a major challenge for the authorities.This study conducts system dynamics and bifurcation analysis of water resources systems in Taiwan under uncertain scenarios. The main focus is the equilibrium and stability of the systems. Furthermore, bifurcation and chaotic behavior of uncertainty are simulated. 

Taiwan is an island that presents a south-north-long type. Most of the rivers in Taiwan flow laterally and the slopes of the river bed are steep.  The rainfall is usually concentrated in the early-summer rainy and typhoon season per year. The precipitation during a typhoon or torrential rain period increases the flow rate of rivers in the catchment area. Sediments carried by flood flow deposits in the reservoir, which may affect the hydrological and ecological environments downstream of the reservoir. Therefore, it is important to concern reservoir desiltation management strategies which require the measurement and analysis of high sediment concentration in the reservoir region. In this research, time-domain reflectometry (TDR) and ultrasonic monitoring system have been designed and manufactured for measuring sediment concentration during a typhoon and torrential rain periods. The stratified sediment concentrations at the water intake in front of Zengwen dam (at EL.177.5, 185, 190, 200, and 210 m.) were observed by the equipment during Typhoon Soulik in 2013. The sediment concentrations sampled in the field (at EL.177.5, 185, and 210 m.) were also obtained by the oven drying method in the laboratory. Besides, the concentration of the bottom outlet (at EL.177.5 m.) is calculated by a two-dimensional hydraulic and sediment transport model. The measured data by the sediment monitoring system are compared with the results by the oven drying method.  The numerically simulated results of sediment concentrations are similar to those observed by the sediment monitoring system. The monitoring technology can be applied to reservoirs in Taiwan for sediment concentration measurement, and the results of measured data and developed numerical model in the field can be both used for improving reservoir desilting operations during typhoon floods.

Limited by the natural environments of heavy rain and strong wind, it may be impossible to use unmanned aerial vehicles (UAV) to photograph the water surface of reservoirs during typhoon floods. Alternatively, in this study, the images recorded by the CCTV built at the reservoir banks are adopted as the data source for the flow patterns analysis at the reservoir. There are four locations where the image data was taken. They are images of upstream and downstream of No. 1 barrier taken by a network camera and images of upstream and downstream of No. 2 barriers captured by a dome camera. In the analysis, the time period with stronger surface ripples on images is selected for flow-field analysis using the Particle Image Velocimetry (PIV) and Particle Track Velocimetry (PTV) method. Then, a discussion of the feasibility and applicability of flow analysis using CCTV images is given. In this study, the images on June 14 of 2019, and May 22 and 23 of 2020 corresponding to the heavy rain period are used for analysis. The preliminary result shows that the measured flow field could be consistent with the observation if the surface tracking particles are sufficient. However, when surface ripples are lack, the analysis of the flow field could be difficult and result in unsatisfactory results. Therefore, in this study, it is still difficult and limited to use CCTV images to analyze the flow field at the reservoir. A further study is needed.

In the future, typhoon intensity and mean annual precipitation are expected to be increased due to global warming at mid-latitude humid regions. The Kuma River, in Kumamoto Prefecture, Japan overflowed by the heavy rains of July 2020, causing many casualties mainly in the Kyushu region. One of the reasons was that the rainfall forecasts were inaccurate, causing delays in evacuations. Rainfall phenomena is occurred in various spatio-temporal scales. Since rainfall phenomena are affected by many factors, it is necessary to examine the effects of these factors against accuracy of rainfall simulation. In this study, we conducted the simulation of rainfall at Japanese archipelago in several meteorological events that have caused severe damage. We then compared the calculated typhoon rainfall and frontal rainfall and observed ones. For the simulation, WRF which is one of weather forecasting models was used. The meteorological data of National Centers for Environmental Prediction (NCEP) was used as the initial value in the simulation. The simulations were conducted by changing the start time of the forecast. To investigate the sensitive physical options for rainfall phenomena in Japan, the cloud microphysics scheme, the cumulus parameterization, and planetary boundary layer scheme were varied. In order to evaluate the accuracy of the simulation, mean absolute error was calculated. The results showed that the absolute values of the errors (MAE) of typhoon rainfall and frontal rainfall were 2~5mm/h and 2~8mm/h, respectively. We also found the physical options which affects to the simulation accuracy. Depending on the selected physical options and the starting time of the forecast, the simulation results were varied, but the rainfall distribution was well reproduced. The presented results are expected to contribute to the improvement of rainfall prediction accuracy and evacuation systems during typhoons and heavy rains, because the physical options that affects to prediction accuracy were identified.

The precipitation products obtained from Numerical weather predictions (NWPs) models are used as the input data for hydrological models to forecast the streamflow. In India, National Center for Medium-Range Weather Forecasting (NCMRWF) provides forecasts from its UK Met office Unified Model-based deterministic model (NCUM), and ensemble prediction system (NEPS). In this study, we assess the accuracy of NWPs from NCUM and NEPSin obtaining the accurate streamflow forecasts. To overcome the uncertainty induced by a hydrological model in streamflow forecasting, a multi-modeling approach is used in this study. We use two hydrological models Soil and Water Assessment Tool (SWAT) and Variable Infiltration Capacity (VIC) for the application of multi-modeling in short-term streamflow forecasting. SWAT is a Hydrological Response Unit (HRU’s) based hydrological model. HRUs are the area that contains similar types of soil, land use and slope properties in a subbasin. The VIC model is a grid-based model with variable infiltration soil layers which characterizes the soil hydrological responses and local variability in land cover classes. We use ensembles and deterministic forecasted rainfall products from multiple NWP models for streamflow forecasting. The study area is the Upper Narmada River basin in central India. The precipitation data of the monsoon period (June to September), 2018 is used with lead times of 5 days. Indian Meteorological Department (IMD) rainfall product is used as the observed data. The calibration and validation of both the models show satisfactory results in obtaining streamflow forecasts. The multi-modeling and bias correction work is currently in progress, and the detailed results will be presented at the conference.

Based on TBB data from Geo-stationary Satellite FY2E (2010-2014) and FY2G (2015-2016), the gauge-adjusted CMORPH hourly precipitation and daily gauge observations, statistical characteristics of eastward propagation of cloud clusters from the Tibetan Plateau (TP) and Mesoscale Convective Systems (MCS) embedded in these cloud clusters in the summers of 2010-2016 are analyzed. The results show that there are 120 eastward propagation processes accompanied with precipitation over the downstream region (east of 104°E). Most of these processes occurred in June, but those with longer durations more frequently occurred in July. Cloud clusters follow three prominent tracks to propagate from the TP to the middle-lower reaches of Yangtze River basin: 1. propagating eastward directly, 2.propagating along the Yangtze River, during which the cloud clusters first move southeastward and then turn eastward, and 3. propagating along complicated paths. The cloud clusters propagating along the second track has the highest impact due to their high occurrence frequency, long duration and the most rainy days over the downstream region. The MCSs embedded in these eastward-propagating cloud clusters occur most frequently in July and more frequently over the eastern slope of TP, eastern part of Yunnan-Guizhou Plateau and the Yangtze River basin. The diurnal cycles of the Permanent Elongated Convective System (PECS) over different regions show that they propagate downstream more easily during the night. The MCSs embedded in the cloud clusters that follow the second track to propagate eastward are the most and also develop most robustly over the downstream region. They are highly associated with heavy rainfall events and areas affected by heavy rainfall.

As the latest generation mesoscale numerical weather prediction system, WRF model has outstanding performance and wide applications in simulating mesoscale precipitation. However, simulation model is unable to predict accurately every time. The biases from WRF precipitation are strongly influenced by raindrop size distribution (DSD). Through double-moment bulk schemes to simulate the DSD of 97 rainfall events and collecting surface observation data in Chilbolton, UK from 2013 to 2017, the DSD model evaluation of WRF is elucidated based on the distribution and relationship of DSD parameters and their integral rain parameters under different rain types and rainfall intensity, which realizes the uncertainty analysis of DSD simulated by WRF. According to the research results, the WRF–λ is overestimated and the other parameterizations (lg(N₀), D_m, Z and R) are underestimated. In comparisons of DSD model across different rain types and rainfall intensity, the uncertainty of WRF is related to them. The error that is due to convective and high rainfall intensity is larger than that of stratiform and low rainfall intensity. With the correlation between parameterizations of WRF and JWD, the difference of lg(N_w)–Dm relationship between WRF and JWD mainly comes from low rain intensity sample, small particle size and large particle size raindrop sample. The Z-R relationship shows that JWD precipitation is more inclined to raindrop size–control, while WRF is more inclined to raindrop number–control. In addition, by fusing the surface observation data, the Bidirectional LSTM model based on deep learning can be used to correct WRF–λ, WRF–lg(N₀). Research results of this paper is significant for understanding the rainfall microphysical process of WRF model and WRF–DSD parameterizations error provides some reference for parameterizations correction and the improvement of precipitation simulation accuracy based on WRF models.

Recent years have witnessed the increasing prevalence of machine learning, including deep learning (DL), in hydrology, particularly in hydrological modeling. Due to the lack of proper methods to interpret the internals previously, most studies concerned primarily about its predictive capability. Fortunately, DL interpretation techniques have achieved accelerated development in recent years, which motivates this study to investigate a novel usage of DL in hydrological sciences, namely, to obtain physically meaningful insights by interpreting what the machine has learned. To demonstrate this prospect, we employed DL interpretation techniques, which can trace model decisions onto a certain fraction of input features and time-wise information contribution, to inspect the underlying input-output patterns within an LSTM-based hydrological model. The results show that the identified input-output relations can be associated with three primary catchment-wide flooding mechanisms. The spatial distribution of feature importance based on 36 thousand flood peaks across the U.S. presents a clear and physically-interpretable regional pattern of dominant flooding mechanisms. Comparisons with existing methods highlight the proposed approach’s competence in accurately presenting the variables’ temporal dependencies. Overall, the reliable capability of interpretative DL in hydrological inference suggests a promising start for new avenues in artificial intelligence-involved hydrological research.

Precise estimation of reservoir sediment inflows and opting suitable sediment management strategy is a challenge in water engineering. This study put forward a two-stage complementary modeling approach for extensive reservoir sedimentation management. The first stage comprised of machine learning based models’ application for reservoir sediment inflow predictions using reservoir hydraulic parameters. The parameter estimation method for RESCON model is applied in second stage to calculate hydraulic flushing framework for the reservoir. The flushing operation parameters estimated by this approach include reservoir water elevation during flushing (El_f), frequency (N), duration (T), and discharge (Q_f) for flushing. This approach was applied to the Sangju Weir (SW) and Nakdong River Estuary Barrage (NREB) in South Korea. The annual sediment inflow volumes were estimated to be 398,144 m³ and 159,298 m³ for the SW and NREB sites, respectively. Results from the parameter estimation of RESCON model revealed that hydraulic flushing was effective strategy for sediment management at both the SW reservoir and the NREB approach channel. Effective flushing at the SW required achieving a flushing discharge of 100 m³/s for 6 days and 40 m of water head. Efficient flushing at the NREB approach channel required a flushing discharge of 25 m³/s, to be maintained for 6 days with 1.8 m of water-level drawdown. The flushing operation must be applied on annual basis in order to achieve better sediment management and also to avoid armoring of sediment deposits. The proposed approach is expected to be useful in achieving better sediment management and sustainable use of reservoirs. Acknowledgement: This research was supported by a grant(2020-MOIS33-006) of Lower-level and Core Disaster-Safety Technology Development Program funded by Ministry of Interior and Safety (MOIS, Korea)

In water resources management, peak rainfall prediction is an important issue particularly for flash flood forecasting with flood hazard and risk assessment. The present study used multilayer perceptron (MLP) neural networks to analyze and predict peak rainfalls at six rain-gauge stations in Seoul, Korea, which consider daily rainfall data from 2003 to 2017. Here, rainfall time series with their statistics from five stations were used to predict missing peak rainfalls on 21 September 2010 (Case 1) and 27 July 2011 (Case 2) at station #2. For compiling a MLP network model, the Adam algorithm and mean squared error (MSE) were considered for an optimizer and loss function, respectively. The results show that a proposed model predicts peak rainfall data with an accuracy of 86% for Case 1 and 99% for Case 2, respectively. Also, it was examined whether changes in training data periods (e.g., 10 years, 20 years, etc.) influence predictive nature of peak rainfall data or not.

The river water temperature (RWT) directly affects the river's physical, biological, and chemical characteristics and determines the fitness and life of all aquatic organisms. Machine Learning (ML) has been increasingly adopted due to its ability to model complex and nonlinearities between RWT and its predictors compared to process-based models requiring rigorous data. The present study demonstrates how the new ML approach, Support Vector Regression (SVR), can be coupled with Wavelet Transformation (WT) to predict accurate RWT estimates with the most appropriate form of AT. Further, the proposed ML approach has been combined with the WT and Ensemble Kalman Filter (EnKF), data assimilation (DA) technique (WT-SVR-EnKF) to improve the predicted values based on the measured data. The proposed modelling framework's effectiveness is demonstrated with a tropical river system of India, the Tunga-Bhadra river, as a case study. Results indicate that the combination of WT and EnKF model (WT-SVR-EnKF) yields a better model than the conventional SVR and hybrid model of air2stream for RWT prediction. The study demonstrates how ML methods can be coupled with WT and DA techniques to generate accurate RWT predictions in river water quality modelling.

Reservoirs are essential infrastructures in human life. It provides water supply, flood control, hydroelectric power supply, navigations, irrigation, recreation, and other functionalities. To provide these services and resources from the reservoir, it’s necessary to know the reservoir system's inflow. The Machine Learning (ML) techniques are widely acknowledged to forecast the inflow into the reservoir system. In this paper, the popular ML technique, Gradient Boosting Regressor (GBR), is used to predict the reservoir system's inflow. This technique has been applied to the Bhadra reservoir of India at a daily time scale. In this study, the effect and complex relationship of climate phenomenon indices with inflow has been considered. The considered climate phenomenon indices are (1) Arctic Oscillation (AO), (2) East Pacific/North Pacific Oscillation (EPO), (3)North Atlantic Oscillation (NAO), (4)Extreme Eastern Tropical Pacific SST (NINO1+2), (5)Eastern Tropical Pacific SST (NINO3), (6)Central Tropical Pacific SST (NINO4), (7)East Central Tropical pacific SST (NINO34), (8)Pacific North American Index (PNA), (9)Southern Oscillation Index (SOI), (10) Western Pacific Index (WP), (11)Seasonality. In this paper, different parameter settings have been discussed on the models’ performances. The analysis of the GBR method for the Bhadra reservoir includes the number of estimators, maximum depth. The results indicate that the GBR model can capture the inflow's peaks and droughts into the reservoir systems. The study demonstrates how ML methods can be used to generate accurate reservoir inflow predictions.

Evaporation is a vital component of the meteorological-hydrological processes. Potential evaporation (PE) is an important parameter for evaluating regional evaporation capacity. This study aims to investigate the evolution characteristics of potential evaporation over the Three-River Headwaters Region (TRHR), which is regarded as China’s main source of water, based on the observed evaporation data recorded at 14 sites from 1960 to 2014. First, the spatial distributions and temporal changes of the PE were analyzed at both annual and seasonal scales, and the results indicated that: 1) the central part had the lowest annual mean PE, while the northeastern and southwestern parts had relatively higher annual mean PE; 2) the mean PE values in spring and summer were much higher than those in autumn and winter; and 3) the PE firstly decreased from 1960s, reached the lowest value in 1980s, and then increased after that. Second, the monthly PE values over the TRHR for the next 30 years were predicted using the BPNN (Back-Propagation Neural Networks) and LSTM (Long Short-Term Memory) model, and the results indicated that: the predictions from the LSTM model had a more significant increasing trend (252.9 mm/30a) than those from the BPNN (5.3 mm/30a), mainly due to that the LSTM model could extract more effective features of the PE in this region. Overall, the outcomes of this study can help to better understand the future meteorological-hydrological conditions in the TRHR, which would be valuable for better protection of the ecological environment of this region.

Check dam construction is one of the most effective and popular methods for sediment trapping in erosion-prone areas. Quantitative estimation of the sediment trapping by check dams is necessary for evaluating the effects of check dams. In this study, we proposed a new framework, SWAT-DCDam (Soil and Water Assessment Tool-Dynamic Check Dam), for modeling sediment deposition caused by check dams by integrating the widely-used SWAT model and a newly developed module, DCDam. We then applied this framework to a typical loess watershed, the YanRB (Yan River Basin), to assess the time-varying effects of check dam networks along past 60 years (1957-2016). The DCDam module generates a specific check dam network to conceptualize the complex connections at each time step (monthly), and streamflow and sediment load simulated by the SWAT model were used to force the sediment routing in the check dam network. The evaluation results showed that the SWAT-DCDam framework performed satisfactorily in simulating sediment trapped by check dams. In the YanRB, our study suggested that the designed structural parameters of check dams have evolved during the past 60 years, with higher dam but smaller controlled area in recent years. Sediment trapped by check dams increased with the intensity of soil erosion, but their relationship varied in different time periods. Further, annual amount of sediment deposition increased with the available storage, and their relationship is clearer when the available storage is less than 115Í10⁶ m³, which may be a critical storage for the YanRB, and sediment trapped by check dams could be restricted when the available storage is below the critical level. Besides, our simulation results showed that more than 75% check dams are almost full, indicating the demand for new check dams in this watershed. In brief, our developed framework can be a promising tool for check-dam effects study.

Understanding and identifying pathways and processes affecting sediment, nutrient and faecalcontaminant inputs from agricultural catchments to streams can improve environmental management strategies and provide a base for estimating the performance of various edge-of-field mitigations, such as riparian buffers and constructed wetlands. It can also provide estimates of the time lag between when changes in land use practices occur are implemented and when water quality effects that result from these changes are likely to be observed. The objective of this study was to characterise watersheds according to the major flow pathways:  overland flow, shallow sub-surface flow, a mix of overland and shallow subsurface flows, or deep ground water flow. Our goal was to characterise these flow pathways using publicly available spatial and temporal data for New Zealand, such as digital elevation maps, fundamental soil layers, rainfall maps, stream flow records and other physical characteristics of catchments.  In this study, a novel, combined data and modelling approach was employed to partition stream flow. The approach comprised a digital filtering technique to separate baseflow from total stream flow, machine learning to predict a baseflow index for all streams with Strahler 1^st order and higher, and hydrological modelling to partition the flow into five flow components: surface runoff, interflow, tile drainage, shallow groundwater, and deep groundwater. We further developed a web-based tool called Hydrological Flow path Explorer to visualize different flow pathways for all streams with Strahler 1^st order and higher for New Zealand rivers. The flow pathway analysis results can support the development of recommendations for riparian buffer design.

Eucalyptus is one of the most planted trees world-wide for hardwood production. In Australia, E.globulus (blue gum) represents 51.7% of all plantations trees for hardwood production, and the largest planted areas are in South Australia and Victoria. The E. globulus plantations expansion concerns governments because of their high water use. Especially in semi-arid regions, factors including population growth and limited precipitation rates result in pressure for regulating water allocation for commercial plantation activity. Water accounting models for plantation establishments have been developed in South Australia over an 11-years management cycle. The models are based on limited experimental evidence on mature plantations. There is insufficient information regarding the water use and growth of stands in the early years after establishment and, thus, management practices are difficult to be defined over the entire management cycle. This study aims to quantify the trade-offs between water use and CO₂ assimilation in a blue gum plantation in the first few years after establishment. The study site is located in southwestern Victoria, Australia, where energy and CO₂ fluxes as well as environmental variables were continuously measured above the tree canopy during the first 3 years after the plantation establishment. The results reveal the effect of tree growth on the water use efficiency (WUE) of a young plantation. During the first three years after establishment, understory vegetation and ecosystem respiration had a major impact on the net ecosystem exchange (NEE). After that period, the trees grew enough to dominate the contributions to NEE, with the plantation becoming a more consistent carbon sink during the entire year, and not only during growing season. Consequently, annual increases in the gross primary productivity (GPP) and WUE were observed.

Current and potential risks to the overall ecological integrity of freshwater ecosystems due to changes in environmental conditions and impacts of anthropogenic activities require exigent and well‐informed actions. Up to now, most of the efforts undertaken have focused on evaluating the physicochemical properties of water, whereas biological evaluation determining the health of a river ecosystem is less attended to. Therefore, this study has aimed to apply a macroinvertebrate-based index to the biological assessment of Lai Chi Wo. The resulting candidate metrics have then been evaluated in terms of redundancy, sensitivity, and responsiveness to environmental changes, using stepwise procedures.  Then five candidate metrics were selected out of 41 for M-IBI development after evaluating their sensitivity and appropriateness. The results of M-IBI showed that human interferences may lead to macroinvertebrate variance. After studying the relationship between monthly M-IBI and environmental factors, M-IBI was found that could comprehensively reflect river health, human intervention, and environmental change. The M-IBI will be a referable river health assessment criterion for supporting long-term monitoring and protecting ecological integrity of streams in Hong Kong and mainland of China.

Understanding the climate change impacts on water and carbon cycles is of great importance for comprehensive watershed management. Although many studies have been conducted on the future climate change impacts on either water cycle or carbon cycle, the potential impacts on water-carbon coupling cycles are still poorly understood. This study used an integrated hydro-biochemical model (SWAT-DayCent) to quantitatively investigate the climate change impacts on water-carbon coupling cycles with a case study of typical loess hilly-gully watershed-the Jinghe River Basin (JRB) on the Loess Plateau. We used climate scenarios data derived under the three Representative Concentration Pathways (RCPs2.6, 4.5 and 8.5) by five downscaled Global Circulation Models (GCMs) and set two future periods of 2020–2049 (near future, NF) and 2070–2099 (far future, FF). It was projected that the annual precipitation would generally decrease slightly during the NF period but increase by 4–11% during the FF period, while the maximum/minimum air temperatures would increase significantly. The average annual streamflow would decrease (with up to 20.1% under RCP8.5) and evapotranspiration (ET) would remain almost unchanged during the NF period; however, both of them would increase during the FF period. The net primary production (NPP) would be generally higher due to the CO₂ fertilization, whereas the soil organic carbon (SOC) would decrease across all scenarios due to the warmer climate. The decrease in SOC was primarily nonlinearly controlled by the increased air temperature and soil water content. The NPP-ET was projected to be closely coupled across all scenarios, and this coupling was mainly controlled by the inter-annual variability (IAV) of precipitation. Moreover, the precipitation IAV combined with NPP-ET coupling could also jointly control the NPP variability in the JRB. 

Variation in streamflow is subjected to variability in climate and anthropogenic activities. Accurate computation of relative contribution these factors involving variation in the streamflow remain an issue of debate. This study computes the influence of climate variability and anthropogenic activities on streamflow at a watershed scale, using streamflow time series, in combination with break point recognition, trend analysis, and hydrological sensitivity analysis. A conceptual framework has been adopted to investigate the relative proportion of effects. The Innovative trend analysis test and Pettit test were applied to examine trend and break point in the time series for a period of (1965-2016). After detecting the breck point in the year 1996, the time series was separated into two sub-series, pre-change or natural period (1965-1996) and postchange or anthropogenic-induced period (1997-2016). The hydrological model was initially calibrated with pre-change period data as input and operated for reconstruction of streamflow in the post-change period. The relative contribution of climate variability and anthropogenic activities were quantified individually using a framework. An Upward trend observed in both precipitation and streamflow time series. The climate variability was the dominating component with influencing the variation in the streamflow contributing 74.27% and the contribution of anthropogenic activities was reported 25.8% to total variation in the watershed streamflow. Although, the contribution anthroponomic active were comparatively less with respect to climate change but it was found significantly increasing in post-change period. The outcomes of this study suggest the climate variability is leading factor associate to variation in streamflow, However, anthropogenic activities were also found sensitive to streamflow variation in the watershed after break point. This knowledge gives a peer insight and would be useful to initiate any project in the watershed in future.   Acknowledgment: This work was supported by the National Research Foundation of the Korean government (Grant No. NRF-2020R1C1C1014636).

Cloud seeding, which is the most popular artificial rainfall technology, is costly and may be inefficient in some situations. Therefore, due to its particular characteristics of environmentally friendly and low cost, acoustic induced precipitation has drawn widely attentions from researchers in recent years. Low-frequency acoustic field can be used to stimulate rainfall by evoking wavy motion of air particles in the cloud which will significantly promote the process of collision coalescence and lead to the volume increase of cloud droplets. Nevertheless, there is still a lack of effective methods to evaluate the effect of acoustic rainfall enhancement in field experiments. A nearly two- month acoustic rainfall experiment with 43 trials was carried out by our research team in Linzhi City, Tibet Province. Based on the comparative analysis of the rain-gauge data, it can be concluded that the stimulation of sound waves on rainfall depends on the duration of precipitation. The promoting effect of acoustic field is more significant in the long duration rainfall process. Meanwhile, there are obvious differences between the precipitation process under acoustic wave and that of natural rainfall in the initial stage.

We present the development and application of a (~1 km) distributed hydrological model, wflow_sbm, with global spatial data and parameterization for the upper region of the Greater Chao Phraya River (GCPR) basin in Thailand. Our main aim was to test the competence of global data to overcome in situ data scarcity often occurring in Southeast Asia. The model was then used for estimating daily streamflow and further assessing effects of reservoir operation. We forced the model with the MSWEP V2 precipitation and eartH2Observe potential evapotranspiration datasets. Seamless distributed parameter maps based on pedotransfer functions (PTFs) and literature review were applied, leaving only the KsatHorFrac parameter, determining the lateral subsurface flow to be calibrated. A target storage-and-release-based reservoir operation module (ROM) was implemented to simulate reservoir releases. The model can reconstruct daily streamflow in the upper GCPR basin, especially for natural flows (KGE = 0.78). The ROM can capture the seasonal variability of reservoir releases, but not very accurately at the daily timescale (KGE = 0.43) since the actual reservoir operations are too complex. Different PTFs and KsatHorFrac values only introduce little uncertainty in the streamflow results. Therefore, the proposed model provides an opportunity for streamflow estimation in other ungauged or data-scarce basins in Southeast Asia. Further model application to quantify reservoir effects revealed that while reservoirs in the upper GCPR basin mitigated many historical extreme flow incidents in terms of both magnitudes and frequencies, their timing became more variable and difficult to predict. Altogether, the results highlighted the difficulty in representing the reservoir system in hydrological models and the importance of effective decision making for real-time reservoir operation, which remain challenging in both modeling and practice. This abstract is based on our recently published 2-part articles entitled 'Daily flow simulation in Thailand'.

In the past several decades, the Pearl River Basin (PRB) has experienced rapid urbanization, and, as a result, water pollution from the point source (PS) has resulted in poor water quality in some reaches of the river. Meanwhile, non-point source (NPS) pollution from large agricultural lands is still a main factor of causing water pollution at large. To get an insightful understanding of water quality in the PRB, it is important to identify the influence of PS and NPS on water pollution in different subbasins. In this study, PS pollution data including urban and industrial sewage from 36 main cities over the PRB in 2011 and 2017 are collected. The hydrological model, SWAT (Soil and Water Assessment Tool), is used to simulate the instream nutrients transport including nitrogen (N) and phosphorus (P) in the West River, North River and East River of the PRB. The study would help to assess the primary source and type of water pollution in different watersheds and contribute to provide suggestions for local land use management and trends of eutrophication in the Pearl River Estuary (PRE).

Development of technology for artificial stimulation of precipitation needs more attention in order to optimize water resources management. As a promising technology, acoustic-induced precipitation has received wide attention due to its low operating cost and free pollution. The main principle is to emit directional low-frequency sound waves to target cloud layer, causing cloud-droplet to collide and agglomerate into large-sized partials and form rainfall drops. However, it is difficult to systematically investigate acoustic agglomeration optimization of cloud droplet only relying on physical experiments. With wide application of numerical simulation in the field of multiphase flow, numerical modeling can be adopted to analyze aerosol particle dynamics and acoustic agglomeration process for the lack of experimental research. In this research, a multi-physics coupling model, COMSOL, was adopted to simulate the process of acoustic agglomeration. The results show the acoustic parameters, such as acoustic frequency and intensity, significantly influence the agglomeration behavior of aerosol droplets through changing the acoustic pressure structure in an agglomeration chamber and changing the acoustophoretic force exerted on the droplet parcels. The environmental parameters such as operating pressure and ambient temperature indirectly affect the interaction processes of air flow and aerosol droplets. It is expected that the preliminary simulation model will be applied to obtain a comprehensive understanding of the process of acoustic-induced precipitation.

The Tibetan Plateau (TP), as the Asian water tower, is the highest in the world and it represents one of the most complex terrain of the earth which has undergone significant warming during the past five decades. In the same period, Indian Summer Monsoon (ISM), which has a great impact on the climate over TP especially over Yarlung Zangbo river basin, has seen a weakening trend. In this context, it is significant to investigate the regional climate change over southern TP and the relationship between climate here and ISM. In this study, spatial and temporal distribution of temperature, precipitation and meridional wind are analyzed, and base on the analysis, we use Weather Research Forecasting model to simulate the impact of meridional wind on regional climate change by increasing/decreasing V-component wind by 10%, 20% and 30% in the driving data. Furthermore, a case was selected to study the impact of meridional wind on the regional rainstorm. The results show that the decreasing of meridional wind can make the most region warmer and reduce the precipitation significantly and meridional wind plays an important role in the location and duration of rainstorm.

Hydroclimatic time series analysis focuses on a few feature types (e.g., autocorrelations, trends, extremes), which describe a small portion of the entire information content of the observations. Aiming to exploit a larger part of the available information and, thus, to deliver more reliable results (e.g., in hydroclimatic time series clustering contexts), here we approach hydroclimatic time series analysis differently, i.e., by performing massive feature extraction. In this respect, we develop a big data framework to facilitate complete hydroclimatic variable behaviour characterizations. This new framework is fully automatic (in the sense that it does not depend on the hydroclimatic process at hand) and relies on approximately 60 diverse features that are mostly sourced from scientific fields beyond geoscience and environmental science (e.g., the fields of neuroscience, biology, biomedicine and forecasting), thereby constituting a new concept for our fields. We empirically prove the high practical relevance of this new concept in hydrological and hydroclimatic contexts by applying our framework to three global hydroclimatic datasets, which together contain 40-year-long time series originating from over 13 000 stations. Our big data analyses provide a useful basis for extracting interpretable knowledge (e.g., on seasonality, trends, autocorrelation, long-range dependence, entropy and on feature types that are met less frequently in the geoscientific literature, as well as on the relationships between all the computed features) at the global scale, and for comparing the examined hydroclimatic variable types in terms of this knowledge. Overall, we feel that, by moving a step further from the traditional approach to feature extraction in hydroclimatic research (as made in this work), we might gain additional insights into the nature of hydroclimatic regimes and changes.

Debris flow initiates from the shallow landslide can develop by eroding surface materials. If numerous debris flows occur concurrently in a single catchment, each debris flow can join each other and increase its effect on the downstream area. Under such conditions, the topographic change affects the inundation of the debris flow itself and the following floods. The debris flow's initiation location may have a high effect on the damage distribution in the catchment. However, the predicting method of such points has not been established. In this study, we introduced statistical landslide prediction to generate such point data artificially. Cell-by-cell logistic regression model estimated the possibility to be the debris-flow initiation point from the terrain and precipitation data. This possibility distribution and pseud-random number sets generated artificial landslide location. On the other hand, we have also developed the 2D simulation based on an existing stony debris flow model. The code has been parallelized by introducing the OpenMP and MPI hybrid parallelization to enable application on supercomputers. This simulation only requires the location of debris flow sources (i.e., landslides) and topographical conditions (DEM), and several physical parameters. By using the numerical model, firstly, we have conducted the simulation employing actual location data. The results showed high reproducibility of the actual affected area. Artificial landslide data are also used instead of the actual initiation points To evaluate source locations' effect. Multiple simulation results revealed that the downstream area has low variability compared to the upstream area under the landslides. This result also indicated that accurate landslide location data is not necessary to predict the downstream area's damage.

The slope at Huafan University is recorded as a dip slope on the Dalun Mountain in the northern Western Foothills of Taiwan. The lithology of the dip slope is mainly composed of intercalation of sandstone and shale and the thickness of the sandstone varies from thin to massive interbedded with shale of Miocene age. By interpolating the thickness of colluvium as the cover material derived from the borehole data and analysing the contouring of the interpolation result in the surfer software, it is revealed that debris accumulates at the slope foot toward the southwest in the direction of movement. Because of the influences of tectonic activities, especially, according to previous investigations, two faults pass through the study area: the one (Fault A) extending perpenticular to the Nanshihkeng Fault plays an important role to change the orientation of the strata. For detailed analysis of the subsurface geological structure of this slope, this study focuses on the development of a 3D geological model by using a polynomial surface fitting equation which is aimed to compute the regressive orientation of bedding plane derived from the boreholes. In the first stage, the orientation of the dip slope is determined by calculating the regression plane passing through the elevations of the boundary between the sandstone and overlying shale. The results show that the regression plane dips southwestward with an inclination angle approximating 16°. In the second stage, several cross-sectional profiles are made to visualize and clarify the 3D geological model. The geological model will contribute significantly to the phenomenon of the slope failure and can be guidelines to minimize the disasters. Finally, numerical simulations could be performed in the future to define the best fit to the observed landslide behaviour by Finite Element Method (FEM).

Landslides were triggered in Mon State of Myanmar in August, 2019 during the monsoon season. Total 90 rainfall-triggered landslides are registered from Google Earth imageries and most of them are relatively shallow and small in dimension (500-15000 sq. m). Among these a massive one, hit Thae Phye Kone village, 30 buildings were damaged and 75 people were killed by the sliding debris. Weathered granites are major lithology of this area. A mountain extended from northwest to southeast provides orographic effect results significant variation in distribution of landslides. 77 out of 90 landslides located on the southwest side of the ridge due to the direction of monsoon wind is from the southwest to the northeast. The topographic features of 35 landslides with area >4000 sq.m were identified by using SRTM and Google eath images. The results shows that these rainfall-triggered are mainly located on the lower slope but approximately 20% of  are located on the higher slope, which is not common and sperated that with thick weathered regolith accumulated on gentle topography near the ridge, enhances the erosion. Landslides mobility is decreased (angle of reach increased) with increasing slope angle of the landslide source area reflects  on slope angle of the landslide source area correlating the friction angle of sliding debris positively. The angle of reach is controlled by other factors such as strength heterogeneity, local topography aside of the valley rather than slope gradient could obstacle the mobility.

The purpose of this study is to establish the basis for improving the skill score of early warning of landslides by identifying the characteristics of soil moisture variation based on the Noah Land Surface Model (LSM) as well as rainfall and for analyzing the soil moisture thresholds that cause the rainfall-induced landslides. Soil moisture is more directly related to slope stability than rainfall because it affects pore water pressure that causes landslides, whereas rainfall thresholds indirectly determine the likelihood of landslides through cumulative rainfall or rainfall intensity or rainfall duration. The commonly-used antecedent precipitation index (API) has a limit because it calculates the recession coefficient by reflecting only the daily average temperature to estimate the soil moisture by considering ground evaporation. Although an attempt to improve API has been made via correlation analysis with soil moisture observations, it does not reflect the fact that the maximum retentive capacity, i.e., porosity, is different for different soil texture. The Noah LSM estimates soil moisture content considering the evapotranspiration from the ground, based on various atmospheric and ground conditions, including temperature, relative humidity, vegetation cover, potential evaporation, soil texture, soil water flow, etc. Therefore, the utilization of Noah LSM has advantages of estimating the soil moisture variation for each soil texture type and for various environmental conditions and identifying integrated soil moisture and rainfall threshold information for each rainfall event, which are essentially required for the landslides early warning system. Furthermore, it is useful to recognize shallow landslides by considering the rainfall conditions, e.g., the recent 3-day cumulative rainfall, and the soil moisture's critical condition.

The 20 September 2018 Naga Landslide in Cebu Island represents a classic deep-seated, low-angle, high velocity translational slope failure in a suburban open-pit mining environment. With a total of 134 casualties, the Naga landslide is considered as the largest landslide in terms of volume and risk in the Philippines’ recorded history. Drone photo interpretation, field investigation, analysis of video footage, and back analyses gave light to the initiation, transport, depositional mechanisms and pre-failure slope stability. The Naga landslide has a peculiar low-angle slip surface, was spread over an area of 9.5 × 10⁵ m², a volume of 27 M m³ and a distal reach of 1.3 km. This complex landslide, moved predominantly as an extremely rapid translational block slide, with minor dry avalanches, and rockfalls. Slide blocks were detached along tensional fractures that formed and grew at least three weeks prior to failure. There was no apparent direct trigger (e.g., rainfall, earthquake) but preliminary back analyses, using limit equilibrium method, yielded unstable to marginally stable failure surfaces even under dry conditions. The 2018 massive failure was interpreted to be caused by progressive weakening of the cut slopes and exposure of potential failure surfaces from slope excavation. The Naga landslide event highlights the need to re-examine policies and scientific protocols in the country to avert a similar disaster in the future.

We present the occurrence tendency of rainfall prone to landslide hazards in the whole Japanese archipelago under climate change influence in the finest resolution of 1 by 1 km. In this study the proxy tool to identify the hazardous rainfall is the well-calibrated critical line method, which is currently being applied for official early warning practice by the Japanese government. The analysis output is based on the grid system in the very fine resolution of 1 by 1 km. For future climate, we analyzed the future projections under the scenarios of RCP2.6 and RCP8.5 from the famous 2-km and 5-km Nonhydrostatic Regional Climate Models, developed and published by Meteorological Research Institute of Japan Meteorological Agency (JMA). Using 15-year reanalyzed precipitation data published by JMA as the observation dataset, a bias-correction method is applied to adjust the extracted simulated precipitation at each 1-km grid. Then, with the critical line method the future changes of hazardous rainfall are successfully obtained in the nationwide and geographically regional scales. The seasonal change is also revealed. The results indicate a clear increasing trend of landslide risk in the period from July to September in the whole Japan, and mostly in the regions of Pacific Ocean side. Our analysis provides a new methodology to quantify valuable and high-resolution hazard map of future landslide risk.

Sufficient information on slope characteristics is key in detailed mapping of landslides. On-site investigations are mainly conducted to closely identify landslide features and gather relevant geomorphological data. Remote sensing is also used as a supplementary tool as it offers a different perspective in landslide investigations, allowing additional insights that are not commonly observed with conventional in situ methods. We used unmanned aerial vehicles (UAVs) to survey deep-seated landslide sites in the Philippines, and generated digital elevation models (DEMs) from the acquired aerial images. Different morphometric parameters were extracted from the DEMs producing nine derivatives. These derivatives were consolidated through principal component analysis into a composite raster image that emphasized morphologically-distinct surface features. Five morphometric parameters, namely, slope, aspect, multiple shaded relief, roughness, and surface relief ratio, were found to be the most descriptive of the surface morphology of two deep-seated landslide sites. In the village of Parasanon, Pinabacdao, Samar Island, most of the previously mapped landslide scarps and cracks were highlighted. In addition, potential new features such as the upper boundary of the landslide, extensions of cracks, and a linear feature at the right flank were identified. In Manghulyawon village in La Libertad, Negros Island, the extent of the head scarp was recognized, and depletion and accumulation zones were revealed. These features require further field verification, as would be the case with every other remotely-sourced data. In addition, it should be noted that analysis from this method is only limited to the ground surface without significant vegetative cover and aboveground structures. The study demonstrated how remote sensing through UAV-derived DEMs supplemented findings from conventional approaches, providing a better understanding of landslides.

Taiwan has risk of natural disaster due to young and complex geological condition, leading high vulnerability to landslide. Knowing more about the mechanism of the natural disaster is critical for mitigation, hence the monitoring implementation will be essential accordingly. The landslide monitoring methods would be divided into the underground, surface to the space monitoring one. Among remote sensing technologies, Synthetic Aperture Radar (SAR) is considered as a powerful tool in this recent decade, and SAR can monitor the land surface movement clearly without the distraction of the cloud or night effect. Therefore, the Interferometry Synthetic Aperture Radar (InSAR) method was proposed to accurately retrieve small displacement. Recently, some techniques of InSAR method have been further improved, such as Persistent Scatter (PS)-InSAR for long-term and robust monitoring. However, there is few rule or guideline especially for the landslide monitoring in practice. Thus, the parametric study was proposed to examine the appropriate ranges of each parameter during PS-InSAR processes, and Ali-Mt. was chosen as the verified case with in-field GNSS observations. First, SNAP software was suggested to be employed at the beginning and combined with STAMPS method for PS-InSAR. Then one significant parameter in SNAP was revealed as the degree of flat earth polynomial which depends on the site location, and in STAMPS step we found the capable range for: (1) filter_grid_size is 15-50; and (2) unwrap_time_win is 20-100 in landslide monitoring case. Further discussion will be proceeded with different case study in near future.

Speleothem d¹⁸O records have extensively been used to study Asian monsoon changes. However, less attention has been paid to the spatial distribution of speleothem d¹⁸O values. Despite some caveats, we advocate an approach to reconstruct spatial and temporal transects (“maps”) of speleothem d¹⁸O, thus time series of precipitation d¹⁸O distribution over the region. We obtained three speleothem d¹⁸O records from caves along a SW-NE transect from coastal Myanmar to southwestern China. All the three records cover the whole or a major portion of the past 40,000 years, particularly the last glacial maximum and present day. The comparisons between the records show a broadly decreasing trend in speleothem d¹⁸O values along the transect, consistent with an overall continental rainout effect of water isotopes when surface moisture is transported further inland. A much larger d¹⁸O gradient however exists during the last glacial maximum than in the late Holocene. A stronger water isotope fractionation during the glacial period is likely caused by a larger temperature gradient and suppressed plant transpiration along the transport pathway. Caution therefore is needed when interpreting the speleothem d¹⁸O records from a monsoon downwind region.

Since the late 19th century, it has been understood that lakes of the western United States reached their high stands after the last maximum of mountain glaciers (e.g., Russell, 1889). This interpretation is consistent with absolute age data obtained since the mid-20th century (e.g., Broecker and Orr, 1958). More recent studies of the last three decades show evidence to support lake high stands occurred during the last deglacial interval (~18 to 12 ka), with Heinrich Stadial 1 (~18 to 15 ka) encompassing a window when nearly all lakes had reached their maximum sizes (Munroe and Laabs, 2013). Efforts to understand the mechanisms that enhanced regional wetness depend strongly on age determinations for lake high stands. However, significant intra- and inter-lake basin disagreements on high stand age permit different interpretations of the climate dynamics that led to greater regional wetness. Our extensive stratigraphic, geomorphic, and geochronologic data from the Mono Basin leads us to suggest that the deglacial high stand of Mono Lake occurred in a very brief interval at about 16 ka. The time spanning the lake rise to its high stand cannot be exactly determined with the available data because the age constraints at hand across a 45 m elevational range are overlapping (16.07 ± 0.08 a to 15.94 ± 0.05 a). These observations require that the rise was sudden and achieved in less than 300 years. The timing of this sudden rise of the level of Mono Lake correlates with changes in tropical climate proxy records that are interpreted to reflect an abrupt southward diversion of the tropical rain belt. The correlation between tropical rainfall records and Mono Lake level is consistent with the hypothesis that changes in the position of the tropical rain belt result in modifications to the hydroclimate of the western US.

In the Fiji Islands, late Holocene environmental change is generally better understood for coastal and lowland situations than for the interior uplands of high volcanic islands. Lake Tagimaucia, a montane volcanic crater lake on Taveuni Island, is Fiji’s only high-elevation lake. It therefore potentially represents a very important site for preserving an environmental record in the highlands through the late Holocene. Physiographic factors expected to promote fast sedimentation rates are the large annual rainfall (>9000 mm), frequent passage of intense tropical cyclones, young geomorphology with erodible volcanic soils, steep catchment slopes, and rapid organic productivity in the surrounding cloud forest. The lake’s remote location means that its catchment is unlikely to have been anthropogenically affected during early human occupation in Fiji after 3000 BP. At present, however, it is not known whether Lake Tagimaucia’s deposits are able to provide a detailed, interpretable, environmental archive through the late Holocene. How fast is sedimentation occurring? Can any disturbances be identified, such as fire events, strong episodes of ENSO-driven drought or exceptional storms? Is there any evidence of the posited significant regional climatic shift called the ‘AD 1300 event’? Results are presented from the analysis of a shallow lake core, charcoal fragments, age-dating, stable isotopes δ¹³C and δ¹⁵N, and observed sedimentary anomalies. Possible influences of volcanic activity, catchment fire and the growth of unusual floating lake islands of sedge peat are discussed.

Differentiating between natural earthquakes and quarry blasts is a labor-intensive task. Recent studies show that artificial neural network (ANN) can achieve good accuracy for these two types of seismic events based on a variety of engineered waveform features. Here, we use convolutional neural network (CNN) to achieve automatic classification with waveform inputs. The training and test datasets consist of 25100 blast recordings from 2010 to 2020 and 31542 earthquake recordings from 2019 to 2020, recorded by the Southern California Seismic Network (SCSN). We input the normalized waveforms to the CNN model and apply the grid search method to determine the optimal model configurations and hyperparameters. Our preliminary results reveal that the CNN can differentiate between these two event types. Next, we will focus on enhancing the accuracy of the CNN model and compare it with that of other methods. Updated results will be presented in the meeting.

Earthquakes generated from different mechanisms could have different rupture processes and thus potentially different moment release histories. While the generation of deep earthquakes (origin depth 100-700 km) is supposed to be different from shallow ones (0-100 km), it remains enigmatic whether intermediate-depth (100~300 km) and deep-focus earthquakes (400~700 km) have different mechanisms. Here, we train machine learning models to test the possibility of distinguishing shallow, intermediate-depth, and deep-focus earthquakes with their source time functions (STFs). Our results show that deep and shallow earthquakes are distinguishable with STFs at an accuracy of 87%±1.1%, and intermediate-depth and deep-focus earthquakes are distinguishable at an accuracy of 68%±2.7%. We find that two STF features, i.e., scaled duration and scaled variance, are critical in both classification tasks, which is consistent with previous findings that rupture duration of same-size earthquakes is generally shorter at deeper depth. Our results indicate that at least part of intermediate-depth and deep-focus earthquakes have different mechanisms; the indistinguishable portion of events could either have the same mechanisms, or have different mechanisms but no recognizable STF differences.

Central Taiwan is a seismic active region that also experiences landslides and typhoons. 5 devastating earthquakes, the 2009 M = 6.2 Nantou, 2010 M = 6.4 Jiashian, 2013 M = 6.2 Nantou in March, 2013 M = 6.5 Nantou in June and 2016 M = 6.6 Meinong occurred in central mountainous area after (3 - 78 months) the 2009 Typhoon Morokat hit the same area. The identified close proximity in space and time between the 2009 Typhoon Morokat and earthquakes suggest the occurrence of cascading hazards. Triggering relations between typhoor or landslide induced surface erosion and earthquakes remain poorly understood. We propose to test the hypothesis that typhoon or landslide induced surface erosion resulted in surface unloading which may promote the rupture of earthquakes. We also probe the contribution of other sources of erosions, including interseismic erosion and large earthquake induced erosion to earthquake triggering. In this study, we present a comprehensive analysis of stress perturbations induced by four sources of erosional unloading (background, a large earthquake, and two typhoons). Our results indicate that surface erosion promoted the initiation and rupture propagation of the 2016 Meinong event, rupture propagation of the 1999 Chi-Chi mainshock, and future failure on the Chukou fault, Chelungpu fault, and flat decollement of Central Taiwan at ~ 4 – 15 km in depth. The cumulative stress perturbations due to surface erosion suggest a dominant role of background erosion with an order of 0.1 bar and secondary effect from earthquakes or typhoons with an order of 0.01 bar. Our study demonstrates a prominent earthquake triggering mechanism related to short-term background, large earthquakes, or wet typhoons induced surface erosion.

Delineation of physical factors that contribute to earthquake triggering is a challenging issue in seismology. We analyze hydrological modulation of seismicity in Taiwan using groundwater level data and GNSS time series. In western Taiwan, the seismicity rate reaches peak levels in February-April and drops to its lowest values in July-September, exhibiting a direct correlation with annual water unloading. The elastic hydrological load cycle may be the primary driving mechanism for the observed synchronized modulation of earthquakes, as also evidenced by deep earthquakes in eastern Taiwan. However, shallow earthquakes in eastern Taiwan (<18 km) are anti-correlated with water unloading, which is not well explained by either hydrological loading, fluid transport or pore pressure changes, and suggests other time-dependent processes. The moderate correlation between stacked monthly trends of large historic earthquakes and present-day seismicity implies a modestly higher seismic hazard during the time of low annual hydrological loading. Our analysis of interannual time series of earthquakes and water loading in 1994-2018 also shows more frequent small earthquakes in the dry years.

Coseismic landslides represent a major cascading hazard associated with high-magnitude earthquakes in mountainous regions. Although recent evidence suggests that landslide hazard can persist and even increase in the years immediately after an earthquake, our understanding of how patterns of landsliding and specifically how runout from rainfall-triggered reworking via debris flows, evolves through time and space remains limited. To address this, we established a systematic multi-temporal landslide inventory covering the full rupture area of the 2015 M_w 7.8 Gorkha, Nepal earthquake, extending across pre-, co- and post-seismic periods (2014-2020). We map landslides bi-annually from satellite imagery to record changes to existing landslides and new failures. We use the mapped landslides as source locations for a spatially distributed empirical runout model, Flow-R, that routes debris downslope simulating plausible ‘worst case’ scenarios. Our results show that even 4.5 years after the earthquake, the number and area of mapped landslides remains higher than on the day of the earthquake. Whilst coseismic landslides persist through time, we also document spatial shifts in the density of landsliding that develop from new but dispersed post-seismic landslides. Comparing modelled runout predictions to our sequential mapping of landslides, we find that 14% (>80 km²) of the total modelled coseismic runout hazard area is realised within 4.5 years of the earthquake, and so represents a portion of post-earthquake landslide hazard that can be foreseen. More broadly, we demonstrate that the persistence of coseismic landslides combined with the occurrence of new post-seismic landslides means that the potential runout hazard also remains well above coseismic levels by the end of the time series. These findings are particularly important for informing a comprehensive and precautionary approach to building into earthquake preparedness planning the likely nature of post-earthquake landslide hazard and risk.

Detailed image of subsurface structure is needed to understand the dynamics of tectonic plates and the processes that occur in the Earth's interior such as convection currents. Seismic tomographic techniques can be used to produce images that describe the structure of the 3D seismic wave velocity in the Earth's mantle globally. The phase data such as P, pwP, pP, S, and sP can be used to image the structure of crust, lithosphere, and Earth's mantle. One of the complex subduction zones resulting from plate tectonic dynamics is the Banda Arc in the eastern part of Indonesia. The Banda Arc is the result of the collision between the volcanic arc and the Australian continent. The Banda Arc region is marked by active seismicity in the eastern part of Indonesia.  This study used the catalog data of the International Seismological Center-Engdahl, van der Hilst, Buland (ISC-EHB) from 1964 to 2015. During this period, 5,243 earthquake events were obtained from 314 global seismic stations with a total of 19.533 phases ( P (16.941 phases), pP (30 phases), pwP(26 phases), S (2.516 phases), and SP (30 phases)). The preliminary result of our travel time tomographic imaging provides a good description of subsurface structure in the crust and mantle down to a depth of 650 km beneath the Banda Arc. More detailed subsurface structure information is being used as input for mapping disaster-prone areas and will be presented during the meeting.

Earthquakes in oceanic subduction zones are closely related to dehydration of subducting slabs. Here we present an integrated study on retrograded eclogites in Yezhai village of the Dabie ultra-high pressure (UHP) metamorphic belt, China. The eclogites have experienced amphibolite facies retrograde metamorphism and partial melting, and developed recumbent folds, tectonic boudins and fault breccias. Quartz veins were accumulated at the fold hinge zone, in which migmatitic eclogites appear as breccias. Zircons from host migmatitic eclogites, eclogite breccias and quartz veins are euhedral and have a core-rim structure. Their rare earth element (REE) distribution is characterized by light REE depletion, heavy REE enrichment, positive Ce anomaly and negative Eu anomaly. The U-Pb ages of 755–722 Ma for magmatic core of zircons indicate their origin of Neoproterozoic protoliths, whereas the ages of 242–221 Ma of metamorphic zircon rims from quartz veins yield timing of fluid flux and earthquakes. The Ti-in-zircon thermometer suggest equilibrium temperature from ~763 ° C and 814 ° C. In addition, EBSD analyses reveal that quartz in both eclogite migmatite and quartz veins show prism <c> slip and prism <a> slip, representing deformation temperature at 650–750℃ and 400–450℃. After high-temperature deformation, rapid healing of the fractures by crystallization of quartz veins will allow overlapping of mid-temperature ductile deformation in both migmatitic eclogites and quartz veins. Breakdown of phengite during exhumation of UHP metamorphic rocks could release water and facilitate partial melting and folding of eclogites. We propose that Si-rich fluids precipitated during melt crystallization and accumulated at the fold hinge, leading to a rapid increase in pore pressure. Therefore, the pulsed fluid flux of UHP rocks during exhumation can trigger shallow to intermediate-focus earthquakes in subduction channels. Such melting-associated hydraulic embrittlement process could also occur during subduction and dehydration of slabs.

Because of the emission of heat-trapping greenhouse gases by human activities, the natural energy flows have been interfered and currently there is an energy imbalance in the Earth’s climate system. More than 90% of the excess heat is accumulated within the global oceans thus leading to an increase of ocean heat content (OHC). Therefore, OHC is a fundamental indicator of global warming and causes sea level rise via thermal expansion. This presentation will assess the state of knowledge in estimating and understanding OHC changes in recent years. Also, we will provide knowledge gaps and suggested actions to better monitor OHC changes, for example, improve the quantification of the uncertainty in OHC record. We will provide gaps and suggested community actions in understanding the ocean heat uptake and its link to sea surface temperature or global surface temperature, i.e. identifying and addressing the regional hot spots and extremes, better understanding of the temporal variations from seasonal, semi-annual, inter-annual, to decadal scales.

Vertical land motion (VLM) is the connection between absolute sea-level (ASL) from a satellite altimeter and relative sea-level from a tide gauge (TG). VLM is often sparsely observed yet required for understanding and interpreting sea-level rise. Altimeter and TG data have been combined to infer VLM, yet regionally-correlated systematic errors in altimetry are not considered and remain to be fully understood. We develop a Kalman filtering and smoothing framework to simultaneously estimate location-specific VLM and residual mission-specific systematic errors in a common reference frame. We evaluate the performance of the method using along-track data from the Jason-series missions (1992-2020) in the Baltic Sea, where glacial isostatic adjustment is the dominant driver of VLM, and then further apply and extend the method to Australia. In the Baltic Sea region, our approach improves estimates of VLM and ASL at TG locations. We successfully estimate significant local land motion at TGs of up to ~4.5 mm/yr which is otherwise not obtainable through interpolated GPS velocities. Our estimates suggest regional systematic errors within the altimetry can be as large as ~±0.5-2.5 mm/yr, presumably due to regional orbit errors as well as geophysical and environmental mis-modelling. In Australia, we extend the technique to also include data from ERS-2, Envisat, SARAL/AltiKa and Sentinel-3A missions and test our ability to estimate time-dependent VLM and altimeter systematic errors. We estimate that Australia is generally subsiding over the altimeter period but find that any post-seismic deformation or surface loading deformation is below the noise level – noise which appears to be dominated by residual oceanography between the altimeter comparison point and the tide gauge. Overall, our approach advances our ability to estimate local VLM and regional systematic errors using TG and altimeter data and further clarifies uncertainties in such studies.

An improved sea-level budget closure has been found on global mean scale since 1900 and at regional mean scale since the 1960s by the intercomparisions between various reconstructions based on tide-gauge records. However, the local sea-level budget at individual tide gauges has not been critically closed. Here, we consider a hybrid sterodynamic sea-level (SDSL) representing ocean dynamic process, glacial isostatic adjustment (GIA), changes of land ice mass, terrestrial water storage, and residual vertical land motion to evaluate the local sea-level budget at tide gauges over 1958-2015. We find the observed trends at 166 of the total 170 tide-gauge stations distributed globally agree with the sum of contributors within 90% confidence level, with matching mean trend (1.3 mm yr^-1 vs. 1.2 mm yr^-1) and spatial variability (equivalent standard deviation of 2.1 mm yr^-1). The SDSL is the dominant contributor to the trend and spatial variability at tide gauges, except individual stations close to previous melting source where GIA is important.

Before the gravity solutions from the observations of Gravity Recovery And Climate Experiment (GRACE) and GRACE Follow-on (GRACE-FO) satellite missions are used to estimate the Global Ocean Mass Change (GOMC), spatial filtering method must be applied due to the strong noise over the oceans, different filtering methods will cause different signal leakages. Besides signal leakage, many other factors also impact the GOMC estimate, specifically including (1) Restoring the AOD1B background model, (2) Geocenter motion corrections, (3) C20 and C30 corrections, (4) Pole tide corrections, (5) GIA correction, (6) C00 correction, etc. Considering the GRACE gravity solutions from different institutes also caused different GOMC estimates we adopt four recently released GRACE/GRACE-FO models (CSR RL06, GFZ RL06, JPL RL06 and Tongji-Grace2018) to quantitatively investigate the impacts of those factors on GOMC estimates. We confirm that Geocenter motion, C20 and GIA corrections have large impacts on the GOMC estimates, especially for the GIA correction model. Normally the C20, C21, S21 and C30 coefficients are replaced by satellite laser ranging measurements. Note that the AOD1B RL06 model has been contained in the background time variable gravity model when inversing these coefficients. Therefore one should not add the GAD product back again to these replaced coefficients to avoid the ‘‘double counting’’ problem. Besides, if one use the recent GRACE Technical Note 13 product for Geocenter motion correction, whose GIA has been corrected with ICE6G-D, which means that one can only use ICE6G-D for GIA correction to estimate GMOC. Thus it is valuable for analyzing and determining the “best” match GIA model, C20 correction, GC correction, etc, for the most recent GRACE products to improve the accuracy of estimated GOMC. 

Mass changes of land ice (i.e., glaciers and ice sheets) lead to geographically variable patterns in regional sea level, often referred to as “sea level fingerprints”. Current sea level fingerprint products are generally limited to coarse resolutions due to their high computational cost and generally do not consider the uncertainties associated with the underlying ice sheet projections. In this study we use the sea level fingerprint module of the Ice Sheet System Model (ISSM) to provide high-resolution sea level fingerprints for the 21^st century with a particular focus on the uncertainties in fingerprints due to ice sheet projection uncertainty. These are based on large-ensemble simulations of the Antarctic Ice Sheet (AIS) generated by perturbing physical parameters within the Parallel Ice Sheet Model. The ISSM sea level fingerprint module is configured with an unstructured mesh grid, with the flexibility of increasing resolution near melting sources and coasts. Our results show that uncertainty in the description of physical processes within ice sheet models causes large uncertainties in both the global mean sea level contributions and future sea level fingerprints during the 21^st century. Understanding local coastal sea level uncertainty requires an understanding of uncertainty at drainage basin level in ice sheet projections, not just the uncertainty of the entire ice sheet.

Global sea level is rising primarily because global temperatures are rising, causing ocean water to expand and land ice to melt. However, sea-level rise is not uniform; it varies from place to place. Singapore and Southeast Asia show significant variability that depends on the combination of global mean sea-level rise and regional factors, such as ocean and atmospheric circulation patterns, the gravitational and deformational effects of land ice mass changes, and tectonic vertical land motion. The relative influence of these regional factors determines whether rates of local sea-level change are higher or lower than the global mean, and by how much. Understanding the physical processes driving global and regional changes is key to predicting the impact of rising seas and extreme events. Determining the rates, mechanisms and geographic variability of sea-level change is a priority science question for the next decade of ocean research. The SouthEast Asia SEA-level program (SEA2) will integrate instrumental, historical and geological sea-level datasets in Southeast Asia with sophisticated modeling capabilities to improve the accuracy of projections of sea-level rise and extreme sea levels, and to communicate the results to the scientific community, governmental agencies and the public. SEA2 will assemble a multi-disciplinary team of leading experts in the fields of reconstructing past and present sea-level change, polar ice-sheet history, oceanography, geodesy, glacial isostatic adjustment (GIA) modeling, and the statistical analysis and modeling of sea-level data. Through training, the SEA2 team will build a home-grown scientific community that can respond to Singapore and Southeast Asia’s need for future sea-level projections and their interpretation.

Sea level is changing due to climactic factors, and tidal range may also change due to sea level change. To understand how tidal behavior (range) changes with the sea level changes, we analyzed the freely available hourly sea-level data, GESLA (Woodworth, 2017), focused on the coast of Southeast Asian Sea where a wide range of tidal behaviour and tidal ranges have been shown. This observed sea-level is a combined effect of a tide component and a storm surge component. Therefore we analysed the sea-level data separately for understanding the causation of the sea level change. We used the tidal harmonic and the correlation analysis methods to quantify the tidal evolution related to the sea level changes. Here we focused along the Malay Peninsula and showed how tidal evolution e.g. the form factor calculated as (K1+O1)/(M2+S2), MSL (mean sea level), have been changed temporally and spatially. From this result, we assume that the sea level around this area has been changed mainly by the tidal behavior which has changed by the surge. This conclusion is confirmed by the tide-only and the surge simulations using a NEMO numerical model. The water density driven baroclinic effects were not considered in this study.

Most of the excess energy stored in the climate system is taken up by the oceans leading to thermal expansion and sea level rise. Future sea level projections allow decision-makers to assess coastal risk, develop climate resilient communities and plan vital infrastructure in low- elevation coastal zones. Confidence in these projections depends on the ability of climate models to simulate the various components of future sea level rise. In this study we estimate the contribution from thermal expansion to sea level rise using the simulations of global mean thermosteric sea level from 15 available models in the Coupled Model Intercomparison Project Phase (CMIP) 6. We calculate a global mean thermosteric sea level rise of 18.8 cm [12.8 - 23.6 cm, 90% range] and 26.8 cm [18.6 - 34.6 cm, 90% range] for the period 2081–2100, relative to 1995-2014 for SSP245 and SSP585 scenarios respectively. In a comparison with a 20 model ensemble from CMIP5, the CMIP6 ensemble mean of future global mean thermosteric sea level rise (2014-2100) is higher for both scenarios and shows a larger variance. By contrast, for the period 1901-1990, global mean thermosteric sea level from CMIP6 has half the variance of that from CMIP5. Over the period 1940-2005, the rate of CMIP6 ensemble mean of global mean thermosteric sea level rise is 0.2 ± 0.1 mm yr^-1, which is less than half of the observed rate (0.5 ± 0.02 mm yr^-1).  We further discuss the difference in global mean thermosteric sea level sensitivity to the changes in global surface temperature over the historical and future periods.

In this study, we developed two high-resolution future ocean regional projection datasets for coastal applications in Japan, in which we made use of dynamical downscaling via regional ocean models with atmospheric forcing from several climate models participating in Coupled Model Intercomparison Project Phase 5 (CMIP5) under historical, representative concentration pathways (RCP) 2.6, and RCP8.5 scenarios. The first dataset is an eddy-resolving 10-km resolution product covering the North Pacific Ocean area and ranging continuously from 1981 to 2100, in which the Kuroshio current and mesoscale structures were reasonably resolved. The second dataset is a 2-km resolution product covering the regional domain surrounding Japan and comprising several 15-year time slices, in which the coastal geometry and current structure were resolved even more realistically. An important feature of these datasets is the availability of reference datasets based on atmospheric and oceanic reanalysis data for cross-validation during the historical run period. Utilizing the high-resolution property of the downscaled data, possible future impact analyses regarding coastal phenomena such as coastal sea level variability are demonstrated.

This study examines long-term assessment for sea level rise based on SROCC and MIROC6 ensemble experiments for IPCC AR6. We analyze trends, seasonal to decadal variabilities of sea surface height (SSH) for modeled SSH and observed long-term SSH in the regional scale. The natural variability of SSH has a variety of spatial pattern and time scale, and is significant in comparison with the long term trend of low emission scenario such as RCP2.6/SSP1-26. The probabilistic characteristics of regional SSH are also discussed both natural variability and GCM based variability which correspond to epistemic and aleatory uncertainty.

Sea level rise presents an acute threat to the natural and human systems of low-lying coastal areas and small island states. Future exposure and vulnerability of these coastal systems will be determined by the interaction of high-frequency local climate variability with long-term trends in sea level rise, coastal urbanization, and economic development. Consideration of the interaction of these multiscale processes in coastal planning presents a major challenge, since until recently, coastal risk assessments have been restricted to using global sea level projections, alongside trends from short-duration (and often unreliable) tide gauge records. Here, we present Met Office work aiming to address the gaps in the provision and use of local sea level rise projections through coastal climate services in Asia, Oceania, and the Caribbean. We discuss the new regional sea level projections that were produced for these projects using the methodology developed for the national UK climate projections in 2018. We describe how these projections can be used to communicate information on the physical drivers of sea level change and the sources of uncertainty in sea level projections for these contrasting regions. We also compare how stakeholder engagement and capacity development has varied across the different projects, highlighting where changes to the common science outputs have been required and where new research will be required to address limitations.    

Sea-level change is a key aspect of climate change, because human interference in the system leads to a gradual warming and expansion of ocean water, melting of glaciers and ice sheets and changes in landwater storage. Process-based models can provide an estimate of the central distribution of change, including mean change. However, many users of sea-level rise information also need information on the tails of the distribution. Here, we build on a framework of building blocks leading to storylines generating an estimate of high-end sea-level change. It aims to provide practioners with actionable information on low likelihood, high consequence cases. We focus on two climate scenarios at two time scales and describe the storylines shaping the high-end estimates of the different components contributing to sea-level rise. For a +2K scenario we estimate 0.8 m global mean sea level in 2100 and 3.4 m in 2300. For a +4K scenario we estimate 1.7 m in 2100 and 10 m in 2300. These large differences emphasize the long time scales of the problem and the long-term benefits of mitigation. However, even a modest warming may lead to a large sea-level rise on long time scales, reflecting the large uncertainty in the Antarctic sea-level contribution. Hence adaptation implications must be considered.

The rapid intensification (RI) of tropical cyclones (TCs) associated with global warming is a matter of concern worldwide. This study examines how the RI across the western North Pacific is related to the so-called 'efficiency of intensity' (EINT) environment induced by global warming. The EINT condition has been characterized by a strong anomalous high over an unstable tropical atmosphere, which supports efficient intensification. Here, we show that global warming significantly increases the proportion of RI-experiencing TCs through EINT environment. Global warming explains up to 51.3 % of the variation in the proportion of RI-experiencing TCs with 93.0 % of that related to EINT. Even the influence of El Niño and Southern Oscillation on the proportion of RI events, though small (16.1 %), is mostly through an EINT environment (73.9 %). Despite the increasing proportion of RI events among TCs, the number shows no trend over time as the EINT condition inhibits the number of overall TC occurrences. The findings are confirmed by the observational consensus between U.S. Joint Typhoon Warning Center and Japan Meteorological Agency.

Marine Heatwaves (MHWs) are extreme climatic events that last for days to months and can extend up to thousands of kilometers, causing higher substantial ecological, social, and economic impacts. Climate models is a key tool to study and predict the MHWs. However, it remains a challenge for climate models to simulate MHWs accurately. In this study, we evaluate 29 models from the Coupled Model Intercomparison Project Phase 6 (CMIP6) and 8 models from CMIP5 to simulate MHWs from the aspects of spatial patterns and temporal variation, and then we estimate future changes to the end of the 21st century under three socioeconomic pathways (SSP1, SSP2, and SSP5). Results show that the CMIP6 ensemble mean is more skillful in capturing the features of MHWs than CMIP5.The bias for MHWs intensity is within ±0.5℃ over most of the ocean, except in the west boundary current region and eastern tropical Pacific where the models are up to 1.5℃ less than observation, while the results from CMIP5 are more than ±1.5℃ in most area. Both CMIP5 and CMIP6 models underestimate the long-duration MHWs in the eastern tropical Pacific, where are nearly 20 days less than the observation. In most areas, CMIP5 overestimate the duration of MHWs (> 25 days), while CMIP6's bias is within 10 days. The future MHWs are projected to increase significantly both in intensity and duration, reach maximum intensities of 4℃. The largest changes are projected to occur in the tropical and North Pacific, and North Atlantic. The socioeconomic pathways affect the increasing trend of MHWs, the most extreme MHWs occur under SSP5, with intensity nearly doubling and near-permanent MHW state occurring since the 2070s. 

As the global sea surface temperature (SST) increases, the frequency and intensity of marine heatwaves (MHWs), persistence of a significant high SST over a certain period, are also increasing. MHWs have been intensified and are projected to increase in the future. MHWs contribute to substantial socio-economic damages by changing the marine ecosystem such as a decrease in catch production and species diversity; and increases in the occurrences of mass mortality of farming fishes and harmful algae blooms. Future changes in global MHWs have generally been projected by global earth system models such as CMIP6 (Coupled Model Project Intercomparison Phase 6) models. In this study, we evaluate marine heatwaves in the historical simulation of 14 CMIP6 models by comparing the CMIP6 simulation with the OISST (Optimum Interpolation Sea Surface Temperature) reanalysis data for 34 years (1982 to 2015). Most of the 14 CMIP6 models show longer duration of MHWs by about 20 days in the Bering Sea compared to OISST. On the other hand, the intensity of MHWs in the North Pacific Ocean was underestimated by about 0.3℃ for 80% of models compared to OISST. The underestimated intensity appears to be associated with a smoothing effect due to the low spatial resolution of the CMIP6 models. We also plan to present future changes in the MHWs projected by the CMIP6 models and their relationship with the biases of the CMIP6 models.

Long-term variability of ocean temperature in the western North Pacific was investigated by using the ScenarioMIP experiments which are integrated under the shared socio-economic pathway (SSP) scenarios: SSP1-2.6, SSP2-4.5, and SSP5-8.5. CMIP6 models including KIOST-ESM are involved in this study. The analysis of KIOST-ESM suggests the evident rising of sea surface temperature (SST) over the 21st century in the SSP2-4.5 and SSP5-8.5, while the warming trend is not significant in SSP1-2.6. The amount of SST change is also dependent on regions. SST difference between 2081-2100 and present (1995-2014) is maximum in the separation points of western boundary currents, the Kuroshio and East Korea warm current. Especially, the maximum SST change between two periods is more than 4°C in the SSP5-8.5 experiment. This is probably due to both the warming effect and northward shift of the western boundary currents. The increase of ocean temperature is maximum at the surface and it decreases with depth. At least in the western North pacific and East/Japan Sea, ocean temperature increases at all depths in 2081-2100 compared to the present (1995-2014). We will also compare the results of the ScenarioMIP experiments from other CMIP6 models to estimate the uncertainty of the long-term variability of the ocean temperature.

Indonesia, a tropical maritime continent between the Pacific Ocean and the Indian Ocean, experiences extreme rainfall more frequent in a changing climate. This is leading to a major disaster such as floods and landslides. These disasters are disrupting economic activity and impacting human daily life, and the future change projection, therefore, is important to reduce the impact of extreme rainfall in Indonesia. In this study, we examine the linking of the annual maximum of daily rainfall series with climate variability phenomena by optimizing statistical extreme value analysis (EVA) using 30 years (1985-2014) recorded daily rainfall series from 10 meteorological stations around Java and Makassar Island. Maximum likelihood estimation was used to find parameters of Generalized Extreme Value Distribution (GEVD). Four non-stationary models corresponded to climate variability imposed to the annual maxima series and the best-fitted model in each station selected based on the smallest corrected Akaike Information Criterion (AICc) and likelihood ratio test. Using the trend-free prewhitening (TFPW) Mann-Kendall test, the daily precipitation annual maxima had increased significantly over the country by 29.5 mm/day over 30 years period. Only Surabaya station shows the increasing trend significantly. Furthermore, based on the best selected non-stationary model, Waingapu and Luwuk covariate significantly with El Nino Southern Oscillation (ENSO), while Perak and Jakarta station covariate insignificantly to Indian Ocean Dipole (IOD). On the contrary, the Madden-Julian Oscillation signal in annual maxima was less prominent in all stations thus not improving the stationary GEV model. A composite analysis reveals that the annual maxima are more robust during La Nina and negative IOD phase compare to El Nino and positive IOD phase. These results imply that the properties of extreme rainfall on sea-air interaction phenomena vary throughout all stations geographically and show phase-locking behavior.

The East sea (Japan Sea) (EJS here after) experienced the surface warming slowdown from 2000 to 2014 (-0.05 ℃ yr^-1 ) but had inversely subsurface (100-300 m) temperature increase (0.03 ℃ yr^-1). To find the causes of two different processes, the trend changes in sea level anomaly, isopycnal depth, and wind pattern were analyzed using monthly mean Ocean Reanalysis System 4 (ORAS4) data from 1980 to 2017. During this period of surface warming slowdown, the strengthened northerly wind enhanced the positive and negative wind stress curl in the western and eastern north EJS, resulting in forming the cyclonic and the anticyclonic ocean circulation accordingly. Consequently, the former and the latter induce oceanic divergence and the convergence at the same time there, respectively. Overall, these two processes cause lower the sea surface temperature, resulting in a surface warming slowdown in the EJS.

Fragmentation is a common processing for the majority of meteoroids, and has been recorded by photography, videotaping, and radar remote sensing. To recognize the meteoroid fragmentation with radar remote sensing, high angular and range resolutions are helpful. In this study, multireceiver and multifrequency observation of meteor echoes using a high-power-large-aperture (HPLA) VHF atmospheric radar, operated at the central frequency of around 46.5 MHz, was carried out. The radar beam was steered to the geographic north and at 51^o zenith. Receiving was done using 20 receivers and 5 carrier frequencies (46.250, 46.375, 46.500, 46.625, 46.750 MHz) for executing angular and range imaging of the meteor echoes, respectively. Adaptive constrained methods such as Capon’s method and its modified version-norm-constrained Capon method were employed in the imaging process. As a result, the angular and range resolutions were improved greatly. Both meteor head echoes and long-duration range spread trail echoes (RSTEs, also known as non-specular meteor echoes) were observed simultaneously. It showed that range imaging was capable of resolving the evolution of RSTEs in the radar volume clearly, in which the branched RSTEs could be evidence of meteoroid fragmentation. On the other hand, angular imaging with single point of raw data (~0.015s) identified multiple echo centers of the meteor head echoes, which was also related to meteoroid fragmentation.

     Asteroids having perihelion distance q < 1.3 AU and aphelion distance Q > 0.983 AU are classified as near-Earth objects (NEOs), which are divided into different groups: Atira, Aten, Apollo, Amor. One of 23 known Atiras, 2020 AV2, the first Vatira (its orbits totally inside Venus' orbit) is discovered by the Twilight project of the Zwicky Transient Facility (ZTF) on January 4, 2020. Upon the discovery of the first Vatira-class asteroid, a couple of orbital studies of the short-term orbital evolution of 2020 AV2 have been performed and published (C. de la Fuente Marcos et al, 2020). In this present work, we performed an assessment of the long-term orbital evolution of known near-Earth objects and known Atiras under Yarkovsky effect by using the Mercury N-body code. In addition, we will evaluate the lifetime of NEOs. and present the assessment of the relationship of orbital dynamical evolution between Atira-class and Vatira-class asteroids.

Photopolarimeter measurements of airless bodies like the asteroids can be used to construct the phase-polarization curves characteristic of individual compositional classes. It means that fitting of the polarization data can be used to infer the physical properties of the surfaces like the albedos and the chemical compositions which provide additional information not readily achievable by other methods. The asteroidal polarimetric measurements require relatively high accuracy because the corresponding polarization values could be on the order of 0.5%. In this study, the Triple Range Imager and Polarimeter (TRIPOL) on the Lulin Observatory was carefully calibrated by observations of a number of unpolarized and polarized standard stars from which the instrumental precision can be characterized. Statistical analyses of the experimental data demonstrated that TRIPOL is suitable for asteroidal polarimetric observations. Some examples of the phase-polarization curves obtained for different types of asteroids are shown to support this conclusion.

We have analyzed MAVEN observations of fields and plasma signatures associated with an encounter of fully-developed Kelvin-Helmholtz (K-H) vortices at the northern polar terminator along the martian induced magnetosphere boundary. The signatures of the K-H vortices event are: (i) quasi-periodic, “bipolar-like” sawtooth magnetic field perturbations, (ii) corresponding density decrease, (iii) tailward enhancement of plasma velocity for both protons and heavy ions, (iv) co-existence of magnetosheath and planetary plasma in the region prior to the sawtooth magnetic field signature (i.e. mixing region of the vortex structure), and (v) pressure enhancement (minimum) at the edge (center) of the sawtooth magnetic field signature. Our results strongly support the scenario for the non-linear growth of K-H instability along Mars’ induced magnetosphere boundary, where a plasma flow difference between the magnetosheath and induced-magnetospheric plasma is expected. Our findings are also in good agreement with 3-dimensional magnetohydrodynamics (MHD) simulation results. MAVEN observations of protons with energies greater than 10 keV and results from the Walén analyses suggests the possibility of particle energization within the mixing region of the K-H vortex structure via magnetic reconnection, secondary instabilities or other turbulent processes. We estimated the lower limit on the K-H instability linear growth rate to be ~5.84 x 10^-3 s^-1. For these vortices, we estimated the instantaneous atmospheric ion escape flux due to the detachment of plasma clouds during the late non-linear stage of K-H instability to be ~5.90 x 10²⁶ particles/s. Extrapolation of loss rates integrated across time and space will require further work.

Using Mars Atmosphere and Volatile EvolutioN (MAVEN) observations from 2014-2019, we characterize how the structure and composition of the nightside ionosphere varies on solar cycle and seasonal timescales. At fixed altitudes between 150-200 km, plasma densities vary substantially on these timescales in response to variations in fixed thermospheric pressure levels, which cause the ionosphere to rise and fall in altitude. Additionally, solar cycle and seasonal trends in the electron impact ionization (EII) rate affects nightside densities; higher densities are observed near solar maximum and Mars perihelion (when EII rates are largest), and lower densities are observed near solar minimum and Mars aphelion (when EII rates are smallest). Lastly, densities in the high-altitude (>200 km) nightside ionosphere vary significantly over the solar cycle: topside O⁺ densities vary by a factor of 50 and topside O₂⁺ densities vary by a factor of 40. Topside ion densities were relatively stable throughout the solar minimum of 2018-2019

Measurements of Energetic Neutral Atoms (ENAs) provide information about both the plasma and neutral environments along the line-of-sight for any ENA instrument, though the individual influences of the plasma and neutral components are convoluted due to the nature of the charge-exchange ENA generation process. We combine ion flux and magnetic field measurements from the Mars Atmosphere and Volatile EvolutioN (MAVEN) orbiter at Mars with models for the Martian exospheric components to estimate the average observable oxygen and hydrogen ENA distribution from various vantage points in the near-Mars space environment. By constraining the plasma environment in this manner, the neutral component can be deconvoluted from past or future ENA measurements, enabling suitably equipped orbiters to probe the Martian exosphere.

In order to determine the extent to which a global magnetic field is required for a planet to be habitable at its surface, expertise is required from diverse communities, some of which have diverged from each other over the past several decades. For example, modelers and observers of the terrestrial magnetosphere have limited overlap and interaction with modelers and observers of unmagnetized planets or the giant planets in our solar system. There is relatively limited interaction between any of the above communities and those who study exoplanets, though efforts are increasing to bridge the solar system and exoplanet communities.  We describe a NASA Heliophysics DRIVE Science Center selected to answer the central question of this session: “Do Habitable Worlds Require Magnetic Fields”. This Center, named MACH (Magnetic Fields, Atmospheres, and the Connection to Habitability) includes scientists who study atmospheric escape from Earth, unmagnetized planets, and exoplanets. Over the next several years MACH will construct a framework that enables the evaluation of atmospheric loss from an arbitrary rocky planet, given information about the planet and its host star. The MACH Center will host a community-wide workshop in June 2021 centered around this topic, and is seeking to grow their interactions with interested scientists from relevant disciplines.

While the two unmagnetized planets Venus and Mars have many similarities regarding the solar wind-atmosphere interactions, they vary in mass, size, and atmosphere density and temperature. In addition, Mars has localized crustal magnetic fields. Venus is closer to the Sun, where the solar radiation, solar wind, and interplanetary magnetic field (IMF) are all stronger. It is not well understood yet how the different upstream conditions and the different intrinsic characteristics separately affect the two planets' respective induced magnetospheres. To answer this question, we analyze the ion and magnetic field data from the NASA Mars Atmosphere and Volatile EvolutioN (MAVEN) mission and the ESA Venus Express (VEX) mission to study the plasma environments and ion escape at Mars and Venus. We first examine the upstream solar wind and IMF measurements from MAVEN and VEX to select data under similar upstream conditions at the two planets. With these selected data, we will examine the spatial distributions of magnetic field, solar wind plasma, and planetary ions, and identity the plasma boundaries at the two planets. The induced magnetosphere morphology, different ion escape channels, and ion loss rates will be compared between the two planets under similar solar wind conditions. These comparisons will help us to better distinguish between the effects of external drivers and planets’ intrinsic characteristics on the formation of induced magnetospheres and ion loss from unmagnetized planets.

The induced magnetosphere and magnetotails on Mars and Venus are considered to arise through the interplanetary magnetic field (IMF) draping around the planet and the solar wind deceleration due to the mass loading effect. Thus, the induced magnetosphere morphology should be controlled by the IMF’s direction. However, the large-scale magnetic fields observed over the north polar region on Venus have a bias in the dawnward direction and seemingly unresponsive to the IMF's direction. Based on the long-term observations of VEX and PVO, and a joint observation of VEX and Messenger, we show that the induced magnetosphere contains a second type of global magnetic field and the large-scale dawnward fields are only a part of it. This global field, referring to as a looping field, has a shape of a cylindrical shell around the magnetotail and a direction of counterclockwise looking from the tail toward the planet. The same global looping field has also been found on Mars with MAVEN observation; therefore, this type of global looping field is a common feature of unmagnetized planetary bodies with ionospheres and it should also exist on Titan and near-Sun comets. The comparison of the looping fields on Mars and Venus shows that the looping field is stronger on Mars. The solar wind azimuthal flows around the magnetotail towards the -E magnetotail polar region are observed by MAVEN. We illustrate that the looping field can be formed by bending the draped field lines with these azimuthal flows and that these azimuthal flows are associated with heavy ion plumes along the +E direction that are expected to be stronger on Mars than Venus. The current system associated with the looping field and its possible connection with the nightside ionosphere formations and ion escapes on Mars and Venus are discussed.

The ESA-JAXA joint mission BepiColombo is now on the track to Mercury. After the successful launch of the two spacecraft for BepiColombo, Mio (Mercury Magnetospheric Orbiter: MMO) and Mercury Planetary Orbiter (MPO), commissioning operations of the spacecraft and their science payloads were completed. BepiColombo will arrive at Mercury in the end of 2025 after 7-years cruise. The long cruise phase also includes 9 planetary flybys: once at the Earth, twice at Venus, and 6 times at Mercury. Even during the interplanetary cruise phase, the BepiColombo mission can contribute to the heliospheric physics and planetary space weather in the inner solar system. In addition, NASA’s Parker Solar Probe was launched in 2018 and it is orbiting around Sun (~0.05 AU at perihelion). ESA’s Solar Orbiter was launched in February 2020 and will have a highly elliptic orbit between 1.2 AU at aphelion and 0.28AU at perihelion. These multi spacecraft observations provide us great opportunities to investigate the inner heliosphere. The Earth flyby and the first Venus flyby were successfully completed on 10 April 2020 and on 15 October 2020, respectively. Planetary flybys are great opportunities not only for scientific motivation but also for instrument calibrations. Especially ion sensors onboard MPO (SERENA/MIPA and PICAM) and Mio (MPPE/MIA and MSA) can detect ions only during the planetary flybys because of constraints on spacecraft attitude and field of views. During the two flybys in 2020 science observations are performed and plasma instruments successfully measured both the Earth’s magnetosphere and Venus’s induced magnetosphere. The second Venus flyby and the first Mercury flyby will happen on 10 August 2021 and on 1 October 2021, respectively. Here we present the updated status of BepiColombo mission, initial results of the science observations during the interplanetary cruise and planetary flybys, and the upcoming observation plans.

We examine the effects of solar wind dynamic pressure and Alfven Mach number on the solar wind plasma interaction with the magnetosphere and surface of Mercury. We use the Amitis model, a three-dimensional GPU-based hybrid-kinetic model of plasma (particle ions and fluid electrons). We use a wide range of solar wind dynamic pressure (~5-50 nPa) and Alfven Mach numbers (~1-10) to investigate the effect of different plasma environment on the shape and structure of the magnetosphere. Our main objective is to characterize the plasma condition that results in disappearance of the dayside magnetopause. We also use our model to predict plasma and magnetic field observations by ESA's/JAXA's mission BepiColombo during its Mercury flybys.

The idea of an “Outer solar system probe: to be aimed away from the Sun in the plane of the ecliptic” dates from a report of the “Simpson Committee” of the Space Science Board of the National Academy of Sciences in March of 1960. What is now known as “Interstellar Probe” has matured as a concept for making new discoveries that can be made in no other way, by going places yet to be explored. “Near-future” propulsion capabilities have always been taken as the backdrop for defining the mission requirements, but the real issue is to unite compelling science with engineering and technical reality. With that perspective in mind, the Johns Hopkins University Applied Physics Laboratory has been tasked by the NASA Heliophysics Division to (re-)study the mission and provide a Technical Report to be delivered late 2021 for input to next Solar and Space Physics Decadal Survey. This “pragmatic Interstellar Probe” of the study is a mission through the outer heliosphere and to the nearby “Very Local” interstellar medium (VLISM), uses today’s technology to take the first explicit step on the path of interstellar exploration, and can pave the way, scientifically, technically, and programmatically for more ambitious future journeys (and more ambitious science goals). To enforce these goals the broadly-based engineering requirements include (1) be ready technically to launch no later than 1 January 2030; (2) be able to transmit useful scientific data from 1000 au; (3) require no more than 600 W (electric) at the beginning of the mission and no more than half of that at mission’s end; and, (4) be capable by design of functioning for no less than 50 years. We provide a top-level summary of the current study status. “It isn’t about where we are going.  It’s about the journey out there.”

During the course of its evolution, our Sun and its protective magnetic bubble have plowed through dramatically different interstellar environments throughout the galaxy. The vast range of conditions of interstellar plasma, gas, dust and high-energy cosmic rays on this solar journey have helped shape the solar system that we live in. Today, our protective bubble, or Heliosphere, is likely about to enter a completely new regime of interstellar space that will, yet again, change the entire heliospheric interaction and how it shields us from the interstellar environment. An Interstellar Probe is a mission concept to explore the mechanisms upholding the heliospheric boundary and take the first step beyond our home, into the interstellar cloud to understand the evolutionary journey of our Sun, Heliosphere and Solar System. An international team of scientists and a team of engineers at the Johns Hopkins University Applied Physics Laboratory (APL) are funded by NASA to study pragmatic mission concepts that would make a launch in the 2030’s a reality. The ground breaking science enabled by such a mission spans not only the discipline of Solar and Space Physics, but also Planetary Sciences and Astrophysics. Here, we give an overview of the science discoveries that await along the journey, including the physics of the heliospheric boundary and interstellar medium, the potential for exploration of Kuiper Belt Objects, the circumsolar dust disk and the extra-galactic background light. We will discuss the details of the study, the example payloads, subsystems and mission architectures that would allow humanity to explore where no one has gone before. 

In the Solar system，there are many astronomical objects owning the magnetosphere structure generated by the interaction between their intrinsic magnetic field and Solar wind, including Mercury，Earth，Jupiter，Saturn Uranus，Neptune and some of their satellites. Heliosphere is the Sun’s magnetosphere，which is filled with Solar wind and surrounded by the interstellar medium. According to the data obtained by the existing detectors，the interaction between the Solar wind and the interstellar medium，the distribution of energy neutral atoms and the relative spatial density changes of picked-up particles，the formation mechanism of abnormal cosmic rays，and possible changes in the shape of the heliosphere are introduced. The marginal exploration plan of China’s Solar system exploration mission is given. Two detectors in opposite directions are designed. One will fly towards the nose tip of the heliosphere to conduct comprehensive exploration of the marginal Solar system and its adjacent space; and the other will fly in the opposite direction to fill the gap at the tail boundary of the spherical layer. The knowledge of the space environment of the heliosphere can provide reference for the design of the probe.

In the long journeys to the heliospheric boundary and the interstellar space as envisaged in several ambitious mission concepts of several space agencies, it is imperative to include planetary bodies in the outer solar system as observational targets to enhance their scientific values and appeal to the general public. A good example is the New Horizons mission to Pluto and the Kuiper belt. Such "targets-of-opportunity" are the Uranisan and Neptunian systems, Centaurs, and a few large Kuiper belt objects like 20000 Varuna. This also means that a miniaturized imaging system should be an integral part of the scientific payload on an interstellar spacecraft to the heliospheric boundary. The flyby observations of any of the above targets could be used as a building block of a long-term outer planet exploration program.

In terms of the scientific objectives of Chinese Solar System Boundary Exploration Mission which is being under discussion, scientific payloads of Magnetometer, Particle Package, Dust Analyzer, Imaging Camera, Ultraviolet Imaging Spectrometer and Visible and Infrared Imaging Spectrometer are proposed. The performance requirements and engineering requirements such as mass and power are given. Because of the tight schedule, heritage information of these payloads is also given. For this super far away exploration, preliminary solutions to common key technologies such as miniaturization and low power, high reliability and long lifetime, science data processing and compression are given.

Energetic Neutral Atom (ENA) imaging provides an essential way to remotely probe distant plasma regions in space, especially for imaging energetic protons. Under the support of NSFC major scientific instrument development grant, we have been developing a grid-modulated ENA imager with high sensitivity and resolutions in Peking University (PKU). This ENA imager utilizes thin-window, low-noise, pixelated silicon semiconductor detectors to detect hydrogen (oxygen) atoms at energies downs to ~5 keV (~10 keV). It also adopts a novel ENA imaging technique that combines Fourier-transform imaging and coded-mask imaging, to enable high-sensitivity imaging with about an order of magnitude less resource requirement. Using these new technologies, the PKU ENA imager will be able to measure ENAs produced in the ring current during terrestrial magnetic storms/substorms, with high temporal and spatial resolutions. Furthermore, this ENA imager can be adopted for the interstellar and deep space missions.

This study shows that a supersonic moon shadow of a total solar eclipse can steepen the ionospheric total electron content (TEC) wave on August 21, 2017. A data-adaptive method named Hilbert-Huang transform is employed to examine the nonlinear and non-stationary evolution of the waves. The results show that the TEC wave behaves as a traveling ionospheric disturbance before the totality appearance, turns later into steepening, and breaks eventually. A TEC wave with a period of ~40min and wavelength of ~1,000km propagates mainly in an east-southward direction before the totality appearance. The wave amplitude and scales, respectively, increases and reduce by near ~50% as the moon shadow approaches the western coast of the continental United States. The short-period TEC waves (period ~2min) reveal that the wave may break eventually when the wave gets steeper. The steepness of the TEC wave is reconstructed according to the constructive interference.

St. Patrick’s geomagnetic storm is an interesting geomagnetic storm due to intense solar wind dynamics allowing the study of the ionospheric properties in various regions. This geomagnetic storm event taking place on 17^th March 2015, the onset time occurred at 04:47 UT. The minimum value of SYM/H index reaching -234 nT occurred at 22:47 UT. The ionospheric variations during the storm time on a global scale can be explained via the ionospheric properties. We study the total electron content (TEC) data obtained by the ground-based GPS receivers (GNSS data), JASON-2 satellite, and the SAMI3/RCM simulation. In addition, the O/N₂ data obtained by GUVI/TIMED satellite are compared with the TEC results. Before the storm time, the TEC is high at a subsolar location in approximately equatorial to low latitude regions during the quiet phase of the solar wind. The average values of the O/N₂ ratios were found at low to middle latitudes, while the lower O/N₂ ratios were found at high latitude regions. However, near the onset time on 17^th March 2015, the TEC increased in equatorial to middle latitude regions. The TEC observations showed high values in northern and southern latitudes near the equatorial region after the SYM/H index reached the minimum value. We intend to compare the TEC data with new SAMI3/RCM simulations, which can be applied for other regions that we do not have the data. For the O/N₂ ratios, the region with low value expanded from high to middle latitudes starting from approximately 12:00 UT, while the O/N₂ ratios clearly increased in low latitude regions. The connections between TEC and O/N₂ ratios and the implication from the simulation in this event could be an important key to explain the ionospheric dynamics.

Nighttime plasma irregularities and scintillations in the low-latitude ionosphere are probed by ROCSAT-1, DEMETER, and FORMOSAT-3/COSMIC (F3/C) during the solar maximum of 1999-2004, solar quiet of 2006-2010, and 2007-2010, respectively.  The occurrence probability and the instantaneous total amplitude of Hilbert-Huang transform are used to examine the irregularities probed by ROCSAT-1 and DEMETER.  Generally, the global distribution of the occurrence probability is similar to that of the total amplitude, except the probability of DEMETER yielding anomalous enhancement over the South American sector during May-August, and however cannot be detected by F3/C S4 index.  A detailed study reveals that the extremely low ambient density can cause the anomalous region in May-August during the solar quiet period.  To resolve the discrepancy, we setup a noise level of the total amplitude to define the irregularities, and compute a new global occurrence probability of irregularity of DEMETER.  The results well agree with the S4 index of F3/C.  Thus, irregularity associated with ionospheric space weather can be investigated.  To examine the ionospheric morphology response to lithospheric activities, we study the global location preference of irregularities and S4 persisting continuously for longer than 24 h at middle and low latitudes (within ±60◦ N geomagnetic latitudes) during the occurrence of large earthquakes.

We examine the variation of VFM measurements on board Swarm satellite and associated ULF magnetic field perturbation in the Pc3 range during local night time around two months of the great Gorkha earthquake (M=7.8 on 25 April 2015). It is interesting to note that the VFM geomagnetic data and their first difference indicate abrupt changes prior to 10 days of the earthquake. These abrupt changes are associated with a peak-to-peak amplitude ≥0.3nT/s, occurrence during very magnetic quiet night-times and occur within the Dobrovolsky circular area around the epicentre of the earthquake. Corresponding Pc3 anomaly are seen to increase in amplitude of Pc3 on 16/04/2015 with an absence of signature on the day of the earthquake. On 25/04/2015. Anomalous Pc3s lasts for more than a month post-earthquake. This earthquake in the seismically active terrain of Himalaya resulted in many aftershocks. It is a challenge to associate the changes in the Pc3 anomaly with the actual and or the result of the aftershocks. Attempt is made to elucidate and understand the coupling process among the different regions of the Earth.

Recently, ionospheric anomalies related to earthquakes  are considered promising. In Japan, the previous statistical study of GPS-TEC shows a significant positive anomaly 1-5 days before the earthquakes with M≥6, depth D≤40 km, epicenter distance of 1000 km Also we have reported that the statistical ionosonde NmF2 analysis during 1958-2017 shows also a significant anomaly 1-10 days before the earthquakes with M≥6, depth D≤40 km, epicenter distance R≤350 km, which indicates the maximum electron density anomaly in the F2 layer. However, the sensitivity of NmF2 anomalies for earthquakes is not clarified. Therefore, we performed statistical analysis to investigate the magnitude, depth, and epicenter distance dependences for earthquakes in which there is a significant positive anomaly in NmF2. This study used ionosonde data observed at Kokubunji, Japan, operated by the National Institute of Information and Communications Technology. We defined the anomaly as the value in excess of median +1.5 IQR of the NmF2 at the same hour in the previous 15 days and the anomalous day as ten or more hours of the anomalies appear in one day. We performed the Superposed Epoch Analysis (SEA) to investigate statistical significance in the correlation between NmF2 anomalies and earthquakes. To evaluate the statistical significance, we examined the random SEA test and we found that there is a significant NmF2 anomaly 6-10 days before the earthquakes. NmF2 anomalies are sensitive to earthquakes with M≥5.8, depth D≤40 km, epicenter distance R≤350 km. Furthermore, we performed Molchan’s Error Diagram analysis to evaluate the efficiency of NmF2 anomalies for earthquake forecasting. These results indicated that NmF2 anomalies are a precursor of earthquakes and are more precursory for shallower, larger, and closer earthquakes. The result indicated that the forecast is most efficient when M≥6.4, D≤20 km, R≤200 km, Δ=10, L=1. and detected about 46% of targeted earthquakes.

The China Seismo-Electromagnetic Satellite (CSES) was successfully launched on February 2, 2018. It is a sun-synchronous orbit satellite with an inclination angle of 97.4° at the altitude of 507 km and with an observation range between -65° to 65° of geographical latitudes. The scientific payload, i.e., plasma analyzer package (PAP) onboard the CSES is designed to detect in-situ ionospheric ion parameters. The observation data of PAP include hydrogen ion density, helium ion density, oxygen ion density, ion temperature, ion drift velocity, and ion density fluctuation.Unfortunately, the in-flight commissioning test indicated that the sensors of PAP were contaminated approximately one month after launch, leading to the ion density values are greatly reduced compared with that in the early period, and the ion drift velocity data are larger than the typical values in the orbit position.    However, the long-term data validation shows that the PAP still has ability to discern the ionospheric disturbances through its relative variation trend or feature. Firstly, from the perspective of overall distribution, the global distribution of PAP data in daytime during an entire revisited period explicitly reflect that the ion contents distribute along the magnetic equator. Further, we analyze the ionospheric disturbance phenomenon caused by high-power terrestrial VLF transmitters, the Ms7.3 Venezuela earthquake on 21 August 2018, and the geomagnetic storm event on 26 August 2018, which are observed by PAP. In all, it is confirmed that PAP data can be selectively used to scientific research through analyzing the relative variation. Furthermore, China and Italy are presently building the second satellite, i.e., CSES-02. Based on the current experience, the PAP onboard CSES-02 has been taken a lot of protective measures to prevent contaminations, in order to offer even greater detection potential for ionospheric studies.

In this study, we investigate the characteristics of pre-earthquake ionospheric effects related to the M7.7 Lucea earthquake (19.46°N, 78.79°W) in Jamaica on January 28, and the M7.0 Aegean Sea earthquake (37.92°N, 26.79°E) on October 30 in the year of 2020. To investigate the temporal and spatial distributions of ionospheric anomalies, we first studied the grid total electron content (TEC) data provided by Center for Orbit Determination in Europe (CODE). A 15-day running median of TEC values and the associated inter-quartile range (IQR) are utilized as a reference for identifying abnormal signals. The results exhibited significant positive anomalies in the south of epicenter on January 26 and 27, which were one and two days prior to the Jamaica earthquake, lasting for more than 6 hours. Then, further study is conducted by using the electron density (Ne) observed by Langmuir probe (LAP) onboard the China Seismo-Electromagnetic Satellite (CSES). By adopting the moving median method (MMM), remarkable enhancements were detected on the same days. By comparing the disturbed orbits with their corresponding four nearest and four revisiting orbits as well as the predicted values from the International Reference Ionosphere 2016 model (IRI-2016), the results strongly illustrate that there were prominent ionospheric anomalies preceding this earthquake. Concerning the Aegean Sea earthquake in Turkey, although positive anomalies were also detected on October 26, 4 days before this earthquake, the seismic-related ionospheric anomalies became ambiguous due to the disturbed space weather lasting for one week. Therefore, how to distinguish the global disturbances related to a storm/substorm and local anomalies caused by a seismic event will be a further study in our future work.

The ionospheric disturbance called plasma bubbles that occurs in the equatorial ionosphere has an irregular plasma density structure, so it degrades radio wave propagation from various satellites. Although plasma bubbles have been observed for more than 80 years, the generation mechanism has not been clarified and the prediction of plasma bubble occurrence is quite difficult. In this study, we have developed a new simulation model for studying plasma bubbles. Models that simulate the ionosphere can be roughly categorized into two types: the global ionosphere model and the local ionosphere model. There is a trade-off between computational domain and resolution. The High-Resolution Bubble (HIRB) model, which is one of the local ionospheric models, can reproduce plasma bubbles in 1 km resolution, but the simulation domain is limited to a narrow wedge region. The model developed in this study is a multi-scale numerical model which covers the whole longitude with a high resolution domain in the dusk region. The new model has the advantages of both global and local models and compensates both disadvantages. In the multi-scale simulation model, plasma bubbles are generated in the high-resolution domain and penetrate into the topside ionosphere. Although the resolution is not as high as the HIRB model, the generated plasma bubbles contain irregular plasma density structures. Plasma drift velocity simulated in the new model are consistent with observations in the all local time region. It indicates that the global simulation is well performed as well as the plasma bubble generation. In this study, the new simulation model has been developed to simulate the plasma bubble generation and global plasma drift velocity in the whole longitude with a multi-scale grid system.

This study presents collaborative observations of the equatorial plasma bubbles (EPBs) by L-band scintillation, density fluctuation, vertical plasma drift, and airglow emission at various altitudes in the F layer using the COSMIC-2, SWARM, ICON, and GOLD data. The result shows that locating the EPBs by in-situ measurements highly dependent on the orbit inclination, thus the EPB occurrence detected by COSMIC-2, SWARM, and ICON display distinct pattern in both temporal and spatial aspects. These in-situ detections are well collocated with the 135.6nm EIA emission gaps in the GOLD monitoring images at the Atlantic-Brazilian longitude sector. The constitution of the COSMIC-2, SWARM, ICON, and GOLD missions provides us a detailed observation of the three-dimensional structure of EPBs. The preliminary results of the vertical drift velocity measured by the ion velocity meter (IVM) at/within the detected EPBs are also compared with the SAMI-3 model.

The ionospheric delay derived from the dual-frequency GPS observations is sometimes not available under the severe plasma bubble event due to the weaker L2 signal,  making it difficult to observe the entire evolution and impact of plasma bubbles. In this study, the ionospheric delay is estimated by the single difference (SD) method, which combines the single-frequency carrier phase (L1) and pseudo-range (C1) measurements between two ground-based receivers. However, using the single-frequency algorithm, the relatively robust L1 signal is still available to investigate the time evolution and spatial distribution of plasma bubbles. As the methodology involves carrier phase observations, solving the phase ambiguity is essential for retrieving the correct ionospheric delay. The ambiguity is solved by applying the Kalman filter for preliminary estimation followed by the well-known LAMBDA (Least square AMBiguity Decorrelation Adjustment) algorithm to approach the best integer solution. The developed algorithm is applied to a hundred stations over Taiwan, located at the low latitude ionosphere. The ionospheric gradient will be larger here when the plasma irregularities occurred that could degrade the positioning accuracy. We examine the ionospheric gradient during a period of magnetic storm and plasma irregularities in March 2015 to understand the evolution of plasma bubbles and their impact on the application of differential-based positioning (such as DGPS and RTK) that requires reference stations.  The results capture the evolution of plasma bubbles and show good consistency with the all-sky airglow observation while the loss of L2 signal, demonstrating the benefits of this algorithm.  The maximum ionospheric gradient reaches ~200 mm/km, indicating the assumption of the same ionospheric condition even within the short-baseline is no longer valid when the plasma bubbles are present. Furthermore, the SD ionospheric delays can be used to mitigate the ionospheric errors for the differential-based positioning.

The day-to-day variability of global low-latitude electron density distributions is investigated by using Global Ionosphere Specification (GIS) electron density profiles derived from the radio occultation measurements by FORMOSAT-7/COSMIC-2 (F7/C2) satellites during a one-year period from August 2019 to July 2020. These daily electron density profiles reveal significant day-to-day changes over dayside low latitudes that vary with seasons, with standard deviations of about 10-20% in equinoxes, 20-30% in solstices, with 40-50% in winter. At night, the percentage standard deviation increases to about 30-60%, with largest values in solstices. Over latitudes of the equatorial ionization anomaly (EIA), the average deviation ranges around15-30% at 1400 LT when the density is usually at a maximum. The period investigated in this study, under deep solar minimum conditions, has remained mostly geomagnetically quiet except for some occasional minor-to-moderate disturbances, and thus much of this variability is likely to be attributed to vertical coupling with the lower atmosphere. To better understand possible driving forces that contribute to this observed day-to-day variability, tidal analysis of the GIS electron density distribution is carried out. Unlike in earlier studies, the results reveal the presence of strong DW1 response over the EIA crest latitudes. The reconstructed amplitudes by using migrating tide components amount to about 50-75% of the overall electron density variation.  Conversely, the non-migrating DE2, DE3, SPW3, SPW4, SE1, and SE2 components induce significant day-to-day variations in the observed wave-3 or wave-4 longitudinal structures in a fixed local-time frame. The magnitude of the net contribution to the overall longitudinal wave structure depends on the relative amplitudes and phases of these non-migrating tidal components. The results further show that, besides these non-migrating components, contribution from other tidal modes add to the complexity of the daily longitudinal patterns in electron density.

This study presents atmospheric lunar tide simulations at mesosphere-lower-thermosphere heights performed by a coupled ocean-atmosphere primitive equation model. The atmospheric model is a non-linear, time-dependent and high-top spectral model. In the atmospheric model, the ocean and load tides are forced by incorporating the ocean and load tide elevation fields from the Finite Element Solution 2014 (FES2014) global ocean atlas model. In addition, the gravitational components of the M2 and N2 lunar tides are incorporated by specifying the geopotential perturbations arising from the lunar gravitational potential field, the earth tide, and the tidal-induced redistribution of mass of the earth’s crust. To ensure realistic tidal propagation conditions, the modeled mean zonal winds and temperatures are nudged to data from the Navy Global Environmental Model - High Altitude (NAVGEM-HA) meteorological analysis system up to thermospheric heights (~95 km altitude). We present simulation results of longitudinal and latitudinal lunar tide variations, as well as simulations of inter-annual variability based on four years of simulations between 2014 and 2017.

Rocket launches carrying satellites into orbit become more frequently nowadays, and their effects to the ionospheric electron density draw attentions with increasing available observations. Observations showed that various traveling ionospheric disturbances (TIDs) could result from the rocket-triggered shock acoustic waves (SAWs) or gravity waves (GWs). Their characteristics can be identified from the shape, period, and phase velocity of TIDs. The reported TIDs generally have a V-shape signature with propagating velocity over the sound speed for SAWs. On the other hand, the TIDs generated from GWs usually reveal a circular- or arc-shape with the period and wavelength in the range of 8-13 min 200-500 km. In this study, we summarize the characteristics of TIDs triggered by several rocket launches, particularly from SpaceX between 2017 and 2020 in America. The ionospheric total electron content (TEC) retrieved from ground-based Global Navigation Satellite System (GNSS) receivers are used to extract the rocket-triggered TIDs by a band-pass filter with a period of 8 to 15 mins. Our results indicate that the behaviors of TIDs triggered by the rocket are highly dependent on the launch conditions, e.g. vertical or horizontal trajectory. In addition, the characteristic of TIDs and their relationship to the background wind field are also discussed.

Launched on 12 Aug. 2018, NASA’s Parker Solar Probe is venturing closer to the Sun than any other spacecraft, mapping the last unvisited regions of the solar system. PSP completed seven of its planned 24 elliptical orbits around the Sun. The perihelia realized so far are 35.7 Rsun (orbits 1-3), 27.8 Rsun (orbits 4-5), and 20.3 Rsun (orbits 6-7). On February 20, 2021, PSP flew by Venus for the fourth time setting the mission for another record of 15.97 Rsun from the center of the Sun. The spacecraft incorporates cutting-edge technology to attain new science: PSP crossed a technological barrier by protecting sensitive spacecraft and payload components from intense solar photon radiation. Parker is primarily an exploration mission, and the data returned so far is a treasure trove that holds the potential for breakthrough discoveries. It is breaking new boundaries of space exploration by flying halfway between Mercury and the Sun. Parker is writing a new chapter of space research by revolutionizing our understanding of this mysterious region by answering long-standing questions that puzzled scientists for decades: how the solar wind plasma is heated and accelerated and solar energetic particles accelerated and transported throughout the heliosphere. The analyses of science data show new phenomena and plasma properties not seen before in the solar wind. Several major discoveries have been so far, most of which are mystifying (e.g., magnetic field switchbacks, solar wind tangential flows, solar energetic particles, and the dust-free zone). Some other discoveries concerning the heliospheric dust are also very insightful. I will provide an overview of the mission's scientific findings after two and a half years of operation and the outlook for the upcoming solar encounters.

FIREBIRD-II is a United States National Science Foundation funded CubeSat mission designed to study the scale size and energy spectrum of relativistic electron microbursts. The mission consists of two identical 1.5 U CubeSats in a low earth polar orbit, each with two solid state detectors that differ only in the size of their geometric factors and fields of view. Each detector returns high cadence (10’s of ms) measurements of the electron population from 200 keV to >1 MeV across six energy channels. FIREBIRD-II has been in orbit for over 6 years and one unit continues to return high quality data. The long lifetime of the FIREBIRD-II mission has allowed for all primary science objectives to be achieved as well as a variety of additional science beyond the scope of the original mission. We present a summary of the FIREBIRD-II mission, the spacecraft design, and the data products. We then highlight some of the science achievements and ongoing projects enabled by FIREBIRD-II.

Photometric monitoring is a method for characterizing stars with variable brightness, like active stars, young stars, and stars with transiting exoplanets.  Space telescopes are ideal tools for continuously observing variable stars, avoiding the drawbacks of ground-based observations. We propose to build an infrared CubeSat-type space photometer working with SPIRou and SPIP, which are ground-based infrared spectropolarimeters/velocimeters at the Canada-France-Hawaii Telescope (Hawaii, in operation), and the Télescope Bernard Lyot (France, to be commissionned in 2022).  The goal of the SPIRou/SPIP CubeSat, nicknamed MARSU (for 'Millimag Astrophotometry of Red SPIRou/SPIP stars as a University space mission'), is to achieve continuous (duty cycle >90%) photometric monitoring in the YJH bands (1-1.8um) for stars up to H~11, at a precision better than 1mmag for up to 10min exposure times, over continuous periods of up to 3months and simultaneously with SPIRou/SPIP observations. With such specifications, MARSU will provide unique opportunities to study young and active dwarfs hosting transiting close-in exoplanets (like the newly discovered K2-33, V1298Tau and Trappist-1) in a way that can compete or even outperform current photometric space probes working at optical wavelengths such as TESS, and for a much smaller cost.  MARSU is managed by IRAP/OMP in France, with financial contributions from the French Space Agency CNES for the design study of the science payload; options are open for broadening the collaboration to Chinese partners, in particular regarding the platform to host the payload, within the framework of the JEWEL Franco-Chinese scientific cooperation programme. Ultimately, the goal is to aim for a fleet of ~10 MARSU-like CubeSats so that a few hundreds of targets can be monitored over the lifetime of the probes, with obvious synergies with large exoplanet missions like ARIEL.

Korea has the lunar exploration program including Korea Pathfinder Lunar Orbiter (KPLO) which will be rescheduled to launch on 2022 recently and future Lunar Lander near 2030s. Korea Astronomy and Space Science Institute (KASI) and NASA HQ Science Mission Directorate agreed to initiate the exploration working group to develop and support joint science project. some science instruments from Korean community will be provided for US Commercial Lunar Payload Service (CLPS). KASI has selected four instruments, based on scientific merit and technology readiness. In this talk, the scientific justification of successful instruments and conceptual design will be presented.

Following up on the successful SELENE (Kaguya) mission, JAXA decided to launch the Smart Lander for Investigating the Moon (SLIM) mission, a demonstration of precision landing technology in FY2022. The SLIM carries one scientific instrument (MultiBand Camera; MBC), which will observe boulders on the lunar surface in 10 bands from visible to infrared wavelength with high spatial resolution (1.3 mm/pixel at 10 m). Target of the MBC observation is the olivine-rich lithology found by SELENE (Kaguya) spectral observation, which is possibly originated from the lunar mantle. To directly investigate this unexplored lithology, one of the small fresh craters named as “Shioli” just outside of the Theophilus crater is selected as a landing site for the SLIM. Engineering model of the MBC has been developed and tested to confirm its capability to investigate mineralogy and chemical composition of the boulders. After the SLIM mission, JAXA is planning a lunar polar exploration mission. Recently, multiple datasets indicate presence of water condensation at the lunar polar region. The goal of this mission is to obtain information for evaluating possibility to use the water as a resource. ISRO and JAXA have been jointly studied this mission, in which each agency will develop a lander and a rover respectively. The rover has a drilling system which can drill the lunar surface regolith up to 1.5 m and bring up regolith samples. In 2020, JAXA selected Japanese mission instruments for the mission. One of the instruments is called resource investigation water analyzer (REIWA). REIWA consist of mainly four subsystems, namely, lunar thermogravimetric analyzer, triple-reflection, aquatic detector using optical resonance, and ISRO sample analysis package (this is a candidate instrument). Also, advanced lunar imaging spectrometer (ALIS) was selected to observe the lunar surface. In this presentation, we discuss objectives, current mission status of these two missions.

 For the purpose of investigating the presence (and amount) of the water (ice) molecules in the regolith 1 to 1.5 m below the lunar surface, a compact neutral particle mass spectrometer is under development. This neutral particle mass spectrometer is designed to be installed on a Moon rover for performing mass analysis of neutral gas generated in the heating chamber. This mass spectrometer not only aims to measure the amount of water molecules included in the lunar regolith but also identify the atoms, molecules and their isotopes up to mass number 200 with mass resolution as high as 100.The mass spectrometer under development is a reflectron that is a Time-Of-Flight mass spectrometer. In order to increase the mass resolution as much as possible within the allocated volume, we have decided to modify the standard reflectron by adding a second reflector that enables triple reflections and doubles the flight length. This newly designed triple-reflection TOF mass spectrometer also has an additional function to select the mass range of the measured particles by changing the temporal pattern of the pulsed high voltage applied to the first and second reflectors. This function is useful, for example, not to measure the carrier gas the amount of which is much larger than that of the target gas. The triple-reflection TOF mass spectrometer can be operated also as a standard reflectron by changing the voltage applied to the analyzer. Triple-reflection mode is suitable for high mass resolution measurement and standard single reflection mode is suitable for high sensitivity measurement.

We present a preliminary study on the multi-parameter analysts of transient phenomena observed in the Earth's atmosphere-ionosphere environment plausibly associated with the latest New Zealand (NZ) Earthquake (EQ) and Tsunami sequence of March 4, 2021. The M8.1 EQ in the Kermadec Islands region was about 1,000 kilometers from NZ and was the largest in a series of tremors on the same day, including the two earlier M7.4 and M7.1 quakes. The NZ National Emergency Management issued tsunami threats for large Pacific parts. We collect operational data from two satellites, ground data, and models probing the atmosphere, such as 1. Outgoing long-wavelength radiation (OLR obtained from NPOESS) on the top of the atmosphere (TOA); 2. Cloud formations and pattern from NASA EOS and HIMAWARI-8; 3. Weather Data -Temperature, Atm. Pressure and Relative humidity form GOES-5 model; and 4. The electron density variations in the ionosphere via GPS Total Electron Content (GPS/TEC). On Feb 6, 2021, NOAA satellite thermal observations show an increase of OLR over the Kermadec Islands with a maximum near the future epicenter of M8.1 of March 4, 2021. A similar anomaly but with lower intensity was revealed on Feb 26 over Northern Islands. Unusual cloud patterns start appearing on Feb 24 onward. GPS/TEC data-based on the IGS network indicated an increase of electron concentration in the ionosphere twenty-four hours before the beginning of the swarm. We demonstrate that by integrating data from multiple sensors, we could observe the pre-earthquake evolution patterns in the atmosphere-ionosphere environment starting up to 3 weeks before the March 4th EQ swarms.  The temporal and spatial characteristics of pre-earthquake anomalies were developed in the atmosphere three weeks in advance, typical for M8+ types of EQ and associated with the large area but inside the preparation region estimated by Dobrovolsky-Bowman.

In recent years, radon anomalies preceding large earthquakes have been reported, which are interpreted as a modulation of Rn gas emanation due to stress changes in the earth’s crust. And it is considered one of possible source of Lithosphere-Atmosphere-Ionsphere Coupling. For this verification, we are conducting continuous observations of underground radon concentration (GRC) in Asahi, Chiba Prefecture (June 2014-) and Miho Village, Ibaraki Prefecture (September 2020-), Japan. We have developed the method to estimate the underground Rn flux (GRF) by using the MSSA (Multi-channel Singular Spectrum Analysis) to remove effects of weather factors of temperature and atmospheric pressure. GRF indicates the upward flow of Rn gas near the ground surface. However, GRF may be affected by heavy precipitations. We conducted a statistical analysis of the relationship between the fluctuation of GRF and precipitation. As a result, we found that GRF significantly increased after heavy rainfall events with 20 mm or more in 2 hours. This is caused by both the increase in load due to rainwater and the infiltration of rainwater near the station. Similar tendency is given for Miho station even though the data are very short. Excluding the influence of the above precipitation effects at the Asahi station, we compare the variation of GRF with the seismic activity near the station, we found there are cases where the GRF increases for reverse fault type earthquakes within an epicenter distance of 50 km from the station. This result suggests the possibility of GRF fluctuation due to the earthquake. In future, it is necessary to quantitatively evaluate the relationship between the fluctuation of crustal stress fields and that of GRF at Miho and Asahi stations.

 Increases in the electromagnetic pulse in the LF band have been reported as one of the electromagnetic phenomena preceding large earthquakes. Before the 1995 Hyogo-ken Nanbu Earthquake (M7.2), Oike et al. reported an increase in the number of pulses, and this phenomenon is considered to be the precursor for the earthquake. On the other hand, it has been suggested that some of these pulse increases are strongly affected by lightning. The issue is to distinguish between electromagnetic pulses caused by lightning and electromagnetic pulses that are precursors to earthquakes. Therefore, we developed the observation system for LF band electromagnetic waves, which can record detailed pulse waveforms, and investigated the relationship between the number of pulses and earthquakes, and analyzed their waveforms to extract the characteristics of the earthquake precursor pulse.
The observation system consists of a capacitive fast antenna with a circular flat plate, a 500 kHz low-pass filter, a 16-bit AD converter, and a PC for data recording. 100 ms data before and after the pulse waveform exceeding the trigger level (V_pp = 6000 [du]) is registered at 4 MHz sampling. The system was installed on the top of the roof of Science Building No. 5, Chiba University. The analyzed period is from May 1, 2018, to May 31, 2019. The details will be shown in the presentation. 

The China Seismo-Electromagnetic Satellite (CSES) with a sun-synchronous orbit at 507 km altitude was launched on 2 February 2018 to observe seismo-ionospheric precursors (SIPs) and ionospheric space weather.  The CSES probes two manifest longitudinal features of 4-peak plasma density and 3 plasma depletions in the equatorial/low-latitudes as well as midlatitude troughs.  CSES plasma probing and the total electron content (TEC) of global ionospheric map (GIM) are used to study SIPs associated with a destructive M7.0 earthquake and its M6.5 and M6.3/M6.9 aftershocks in Indonesia on 5, 17, and 19, August 2018, respectively, as well as to examine ionospheric disturbances induced by an intense storm on 26 August 2018.  Anomalous increases (decreases) in the GIM TEC and CSES plasma density (temperature) appear specifically over the epicenter day 1-5 before the M7.0 earthquake and aftershocks, and however similar TEC and CSES anomalies occur globally in the southern hemisphere during the storm days of 26-28 August 2018.  The CSES ion velocity shows that the seismo-generated electric fields associated with the M7.0 earthquake are 0.06-0.21 mV/m eastward and 0.13-0.14 mV/m downward on 1-3 August 2018, while the penetration electric fields during the storm periods of 26-28 August 2018 are 0.17/0.60 mV/m westward/downward at post-midnight of 02:00 LT and 0.26/0.34 mV/m eastward/upward at post-noon of 14:00 LT.

Solar flares suddenly emit strong multi-wavelength electromagnetic emissions. Among these emissions, X-rays and extreme ultraviolet (EUV) emissions rapidly change the physical composition of the Earth's ionosphere, thereby causing space weather phenomena such as the sudden ionospheric disturbance etc. (Dellinger 1937).  We verify the extent of reproducing the flare emission spectra and their profiles using a newly developed simple method based on the physical process of the flare loop (Kawai et al., 2020). In this method, we convert the soft X-ray light-curves observed during flare events into EUV emission spectra using a one-dimensional hydrodynamic calculation and the CHIANTI atomic database (Dere et al., 2019). We examined the “EUV flare time-integrated irradiance” and “EUV flare line rise time” of the EUV emissions for 21 events by comparing the calculation results of the proposed method and observed EUV spectral data. The proposed method succeeded in reproducing the EUV flare time-integrated irradiance of the Fe VIII 13.1 nm, Fe XVIII 9.4 nm, and Fe XX 13.3 nm, as well as the 5.5-35.5 nm band. For the EUV flare line rise time, there was acceptable correlation between the proposed method estimations and observations for all Fe flare emission lines. In order to examine the effect of flare EUV emission on the ionosphere, we input our calculated flare EUV spectra that mentioned above to the Earth's atmospheric model GAIA (Ground-to-Topside Model of Atmosphere and Ionosphere for Aeronomy; Jin et al., 2011). We compared the total electron content (TEC) variation in the ionosphere reproduced by GAIA with observations for 21 events. We examined in detail the temporal changes in ion densities of major thermosphere species (O⁺, O₂⁺, N₂⁺ and NO⁺ ) to clarify which wavelengths in the solar emission spectrum are ionize the atmosphere at which altitude in the ionosphere.

The composition in the Earth's ionosphere changes due to X-ray and Extreme ultraviolet (EUV) radiation associated with solar flares. When these radiation reaches the ionosphere D region at lower than 100 km, the ionization and molecular dissociation of atmospheric components in the ionosphere, thereby causing the Dellinger phenomenon (Dellinger 1937). Generally, the Dellinger phenomenon is considered to be caused by the occurrence of M-class or higher solar flares and predicted by using the magnitude of the solar flares. However, reportedly, the Dellinger phenomenon sometimes occurred even in during C-class flares; however, it did not occur even in during X-class flares (e.g. Tao et al., 2020). From these results, it is considered that the flare emissions contributing to the occurrence of the Dellinger phenomenon may also be affected by other emissions. The occurrence of the Dellinger phenomenon can be known by using the minimum reflection frequency (fmin) from vertical incident ionograms. Therefore, we checked the fmin observed in the ionosonde held by the National Institute of Information and Communications Technology at Kokubunji. And then, we statistically compared with the solar flare emission (X-rays and EUVs). When the fluctuation of fmin (about 4,000 events) between 1996 and 2018 was compared with the Geostationary Operational Environmental Satellites (GOES) X-ray intensity, a relationship was seen that was almost in agreement with the results of previous studies (Sato, 1975; Tao et al., 2020). In this paper, we will report the results of statistical comparison of the Dellinger phenomenon (fmin fluctuation) that occurred from 1996 to 2018 with X-ray data. We also report on the results of comparisons between fmin and EUV data which are observed by the Solar and Heliospheric Observatory/Solar EUV Monitor, Project for On-Board Autonomy-2/LYman-alpha RAdiometer, and GOES/EUV Sensors, and discuss the effects of EUV emissions on the Dellinger phenomenon.

There are numerous observations of fast and dense plasma streams, so-called jets, propagating inside the magnetosheath. It was found that large-scale jets with duration of minutes can effectively interact with the dayside magnetopause. The interaction is followed by an increase of auroral electrojet (AE) index by up to 100 nT with a time delay of several minutes. The magnetic disturbances are detected first on the dayside and then propagate toward the night side. The jet-related auroral activity is pronounced during quite geomagnetic conditions and can occur under northward orientation of interplanetary magnetic field. We interpret this phenomenon as a complex result of two effects: localized compression of the magnetopause and penetration of the magnetosheath plasma inside the magnetosphere.

Since the launch of Hinode in 2006, the X-Ray Telescope (XRT) has provided us a huge amount of coronal image data with unprecedented high spatial resolution and time cadence, which are used not only for morphological studies of active regions but for the quantitative studies of plasma properties. Hinode/XRT equips the modified Wolter-type grazing incidence (GI) mirror for collecting the lights from the full solar disk area and its neighboring region in 34 x 34 arcmin FOV. The degree of imaging quality of an optical instrument is in general getting worse as it goes away from the center and therefore it is requested to pay more attention when dealing with the data near the periphery of FOV. In this presentation we focus on the issues related to the imaging characteristic of Hinode/XRT, particularly for the data taken from the off-axis region. In order to derive physical parameters of coronal plasma using the data in the region far off from the optical center, it is necessary to perform a series of calibration procedures such as the reduction of scattered lights and the correction of vignetting effect. The light scattered by the roughness of GI mirror surface should be restored in a proper way especially when the data are taken from the faint region over the solar limb and thus the accurate information on the PSF must be essential. It have been revealed from our analysis of over-exposed in-flight data that the scattered light has a power-law distribution and shows an energy dependence. Vignetting is also an important optical characteristics for describing the telescope's performance. We have found that the degree of vignetting varies linearly from the optical center and shows an energy dependence. More results on the interesting off-axis optical characteristics of Hinode/XRT will be discussed in detail.

In the interplanetary space, the majority of the Alfvénic fluctuations cannot satisfy the Walén relation even though the plasma and magnetic field fluctuations are correlated very well. Finding a proper de Hoffman-Teller (HT) wave frame velocity is thus important for characterizing the Alfvénic fluctuations. Recognizing that the Alfvénic fluctuations emanating from different sizes of solar wind streams have their own HT frames, we propose a new scheme called the Wave Frame with Varying Velocity (WFVV) Method by considering the local averaged HT frame to find a time-varying profile of HT frame velocity. By re-examining two Alfvénic events on 2002 October 14 and 17, we show that the WFVV Method can provide the HT frame variation in more detail with a better Walén test result and a smaller convection electric field, particularly for the large solar wind changes associated with directional discontinuities. In addition, we note that the degree of Alfvénicity tends to decrease with an increasing variance of HT frame velocity. We will demonstrate the results of Walén analysis from different schemes and discuss their differences in this presentation.

Throat auroras frequently observed near local noon have been confirmed to correspond to magnetopause indentations, but the generation mechanisms for these indentations and the detailed properties of throat aurora are both not fully understood. Using all‐sky camera and magnetometer observations, we reported some new observational features of throat aurora as follows. (1) Throat auroras can occur under stable solar wind conditions and cause clear geomagnetic responses. (2) These geomagnetic responses can be simultaneously observed at conjugate geomagnetic meridian chains in the Northern and Southern Hemispheres. (3) The initial geomagnetic responses of throat aurora show concurrent onsets that were observed at all stations along the meridians. (4) Immediately after the concurrent onsets, poleward moving signatures and micropositive bays were observed in the X components at higher‐ and lower‐latitude stations, respectively. We argue that these observations provide evidence for throat aurora being generated by low‐latitude magnetopause reconnection. We suggest that the concurrent onsets reflect the instantaneous responses of the reconnection signal arriving at the ionosphere, the followed poleward moving signatures reflect the antisunward dragging of the footprint of newly opened field lines, and the micropositive bays may result from a pair of field‐aligned currents generated during the reconnection. This study may shed new light on the geomagnetic transients observed at cusp latitude near magnetic local noon.

The ionosphere is mainly affected by space weather, including solar flares, coronal mass ejections, high-speed solar wind, corotating interaction regions, etc. Ionospheric disturbances reduce the accuracy of GNSS. In modern society, real-time monitoring of the ionosphere is an important issue. When we monitor the ionosphere in real time, the challenge is that there is a big amount of data that needs to be processed. We use artificial intelligence (AI) for quickly semantic segmentation of digital ionograms. Even the ionograms have low SNR, Deep Watershed Transform(DWT) can provide very good results. We collected 2109 ionograms to test DWT performance, it takes less than five minutes to evaluate all dataset and get more than 60% of accuracy.The work was performed as part of NCU AI group: Chang Y.-C., Dmitriev A., Hsieh M.-C., Hsu H.-W., Huang G.-H., Li Y.-H., Lin C.-H., Lin Y.-C., Mendoza M., Tsai L. C., Tsogtbaatar E.

The Ionosphere disturbance is mostly affected by space weather such as solar flares, solar energetic particles, coronal mass ejections, corotating interaction regions even high-speed solar wind from coronal holes. However, ionosphere disturbances can affect the accuracy of GNSS operation so that it's important to monitor and predict space weather in real time. Because these challenges require a huge number of data to analyze, we use artificial intelligence (AI) to help us do semantic segmentation of digital ionograms. Mask Region-Based Convolutional Neural Network (Mask RCNN) is one of the algorithms to work on digital ionograms. We use 2109 ionograms to test the performance of Mask RCNN, and even the ionograms above Taiwan have low Signal to Noise Ratio (SNR) Mask RCNN can provide good results.The work was performed as part of NCU AI group: Chang Y.-C., Dmitriev A., Hsieh M.-C., Hsu H.-W., Huang G.-H., Li Y.-H., Lin C.-H., Lin Y.-C., Mendoza M., Tsai L.-C., Tsogtbaatar E.

Low-latitude upper atmosphere is replete with the effects of various intriguing and inter-coupled phenomena that are generated over equatorial latitudes.  As a consequence of these phenomena, the upper atmosphere from the latitudes close to the magnetic equator to those that are farther away respond in varying degrees wherein neutral- and plasma densities, and gravity wave features, vary as a function of latitude.  Further, the neutral thermospheric gravity wave propagation characteristics also change with latitude.  From the analysis of thermospheric and ionospheric datasets obtained using optical, radio-wave, and magnetic techniques from strategic locations in the northern hemisphere over Indian longitudes, we have obtained several new results, corresponding to both, in the daytime and nighttime upper atmosphere.  These include influence of meridional neutral winds on the variation of nocturnal redline airglow emissions, quantification on the latitudinal extents of the response of the daytime equatorial ionization anomaly as seen in the daytime oxygen airglow emission at multiple wavelengths, and seasonal dependence of the existence of vertical propagation of gravity waves.  The results obtained from the low latitudes enhance our understanding of the ionosphere thermosphere coupling over both magnetic quiet and disturbed conditions. In this talk some of these new and insightful results will be discussed.

The purpose of this study is to comprehensively understand the evolution of global 3D current system from polar to equatorial ionosphere during substorms.There are two types of current in the polar ionosphere: the R1-current linked to the magnetospheric convection system, and the R2-current linked to the pressure gradient in the inner magnetosphere [Iijima and Potemra, 1976, 1978]. In addition to these currents, when a substorm onset is occurred by a strong plasma injection, a current wedge (CW) is generated by the plasma vorticities at the edge of the plasma flow. It has the same current polarities as the R1-current system. At the lower latitude of the CW, an R2-type current system develops by increasing the plasma pressure. It weakens the effect of ionospheric current associated with the CW system reaching low latitudes and equatorial regions. This is called a shielding effect. Furthermore, it sometimes overcomes the effect of CW, and grows of current systems in the opposite direction. This is called an over-shielding effect. (Kikuchi et al.,1996 ; Nishida.,1968). The ground magnetic field disturbances during substorms are generated by not only the ionospheric currents, but also the field-aligned currents (FACs) accompanied by the growth of the CW. These effects are particularly large in the mid- and low-latitude. It is difficult to determine from the magnetic field data alone whether the magnetic field variation is due to the ionospheric current system or to the remote effect of the CW system. A direct comparison of ionospheric electric and magnetic field data is essential for a better understanding of the causes of magnetic disturbances.  In this presentation, we report the results of a study of mid-latitude ionospheric variability during substorm using electric field data from the HF Doppler radar and magnetic field data from SuperMag and MAGDAS.

The presence of Equatorial Electrojet (EEJ) enhances the conductivity of equatorial ionosphere and enable the penetration of Interplanetary electric field through high latitudes known as prompt penetration effects (PP). Using five years (2011-2015) of geomagnetic data at a site VEN local time dependence of PP amplitude and its relation to IMF-Bz turning for both quite (Kp<3) and disturbed (Kp≥3) time is being studied; the number and amplitude of PP events are larger during local noon time for both quiet and disturbed time is attributed to the high ionization. The amplitudes of PP during quiet days are observed to be similar for both IMF-Bz north and south turnings, whereas for disturbed days PP amplitudes observed to be higher for IMF-Bz north turning, this might be due to the overshielding effects. The PP events associated with IMF-Bz northward turning during magnetically quiet time creates depression/westward current in the EEJ sometimes appears as equatorial counter Electrojet (CEJ). Few PP events are observed while equatorial electric field at VEN is already in westward direction (i.e PP within CEJ). The analysis of one year of concurrent geomagnetic data from MNC, VEN and CBY shows that PP amplitude varies significantly (10nT>) between sites which are 15° & 20° longitudes apart. The analysis also shows a trend of increase in PP amplitudes toward west of India (i.e toward MNC).

The bottomside of the ionosphere rapidly decays after sunset and develops a sharp vertical density gradient on the lower layer that triggers plasma density perturbation in the ionosphere. Equatorial plasma bubbles (EPBs) and plasma blobs (enhancements) are evidence of nighttime ionospheric plasma instabilities in the low-latitude ionosphere. This study presents plasma density (EPB and blob) structures identified using simultaneous in-situ measurement by the SWARM satellite constellation and concurrent total electron content (TEC) detected from ground-based Global Positioning System (GPS) receivers in the American low-latitude region. The ground-based GPS receivers diagnose bubbles and blobs characteristics in terms of TEC values. Basically, the space-based observations of ionospheric plasma density from the Swarm constellation were supported by the ground-based observations. The comparative ground- and satellite-based observations indicate that the ground-based data show the variability of the background ionosphere prior, during, and after the development time of the EPBs as seen by the SWARM. For this limited analysis, the plasma blob events are seen near the low and mid-latitude boundary region. Further, the zonal motion of the density structures detected by SWARM and the drift of TEC structures seen with GPS receivers are in good agreement. Based on an observational standpoint, the possible mechanism of the generation, evolution, and relationship between EPBs and plasma blobs in the F-region ionosphere will be described in detail.

The quiet time characteristics of equatorial electrojet (EEJ), counter electrojet (CEJ), and solar quiet (Sq) day geomagnetic field over two decades (1980–2002) are established using Principal component analysis (PCA) from equatorial (Ettaiyapuram) and off‐equatorial (Hyderabad) Magnetic Observatories, India, over sunspot cycles 21–23. The patterns of normal field show that the diurnal amplitudes were strong during equinox compared to other seasons. Varying contributions of abnormal field in different Lloyd's seasons were evident in different phases of sunspot cycle. The diurnal amplitudes have reduced from the 21st to the 23rd sunspot maxima following the trend of weakening of sunspot cycle. Analysis of seasonal means shows evening CEJs were more pronounced when compared to morning and afternoon in different phases of sunspot cycle. The abnormal field variations have a strong correlation with the occurrence of afternoon CEJs during solar minima; a correlation of seasonal occurrences of CEJs with phases of sunspot cycles is revealed.

We performed a superposed epoch analysis of solar wind, interplanetary magnetic field, geomagnetic index, and the rate of total electron content (TEC) index (ROTI) derived from global navigation satellite system-TEC data during 652 geomagnetic storm events (minimum SYM-H < -40 nT) for 19 years (2000–2018), to clarify the occurrence features and causes of storm-time plasma bubbles in the equatorial to mid-latitude ionosphere. In this analysis, we defined the time of the SYM-H minimum as the zero epoch. As a result, the ROTI enhancement started at the duskside magnetic equator and expanded to higher latitudes during the main phase. Approximately 1 h after the onset of the recovery phase, the ROTI values at the magnetic equator in the dusk-to-midnight sectors decreased while those in the dawn sector increased. This situation persisted for at least 12 h. On the other hand, the ratio of the ROTI during the main phase to that during the quiet period in the dusk sector is the largest in May–July. The ratio of the ROTI in the dusk sector during the main and recovery phases decreased with increasing solar activity. Considering the requirement of the Rayleigh-Taylor instability, the difference in the magnetic local time of the ROTI signature, between the main and recovery phases, can be explained by a local time distribution of storm-time electric fields associated with a prompt penetration electric field and disturbance dynamo. This implies that the occurrence feature of the plasma bubble is different from that during quiet times when the input of solar wind energy to the magnetosphere and ionosphere increases significantly.

The quasi-6-day wave (Q6DW), one of the atmospheric waves, is excited in the lower atmosphere and propagates into thermosphere. Using CHAMP, Swarm and Aura satellites, Yamazaki et al. showed that the quasi-6-day oscillation in the EEJ occurs when the Q6DW in the mesosphere is enhanced. This suggests that the quasi-6-day oscillation in the EEJ is caused by the Q6DW propagating from below. We analyzed that the magnetic field data on 210°geomagnetic longitude chain of global geomagnetic observation network (MAGDAS) and an atmosphere-ionosphere coupled model (GAIA). Our results indicate that the quasi-6-day oscillation in the Sq-EEJ current system more strongly developed in the mid-latitude Sq current system than in the EEJ, and more strongly developed in the day side. Also, the quasi-6-day oscillation of the GAIA and MAGDAS have similar seasonal variation and latitudinal structures. The quasi-6-day oscillation is strongly developed in equinoxes, which is consistent with the seasonal dependence of the excitation source, the Q6DW.However, how the Q6DW effects on the electrical conductivity and the electric field is not well known. The excitation mechanism of the quasi-6-day oscillation in the Sq-EEJ current system is examined using GAIA. That leads to understand coupling processes in the atmosphere-ionosphere system.

Abstract: The Energetic Particle Instrument (EPI), proposed by the Peking university (PKU) team, consists of three dual double-ended foil/magnet semiconductor telescopes. The magnet telescope side utilizes three layers of semiconductors, respectively, with a 50-micron thickness, 500-micron thickness and 500-micron thickness to measure protons at energies from 30 keV to 12 MeV. The front of the 50-micron thick detector is surrounded by a magnet to sweep away electrons below 400 keV but let protons pass. This paper describes the design and GEANT4 simulations of the proton detection side of the PKU EPI.