Precipitation extremes (PEs) are significant consequences of global climate change that substantially affect the entire region’s lives and livelihood. PEs are not only the global challenge to meet but also is the regional scale vagary. India is also affected by these extremes to a great extent especially during the monsoon. Monsoon is the principal rainy season of the region that brings 70-80% of annual rainfall over the region. The natural and anthropogenic activities are responsible for abnormal behaviour, leading to either tremendous rainfall or very scanty rainfall, causing several fatalities. Therefore, it is necessary to identify the different precipitation types over India, focusing on the central region lying in the core monsoon zone in three-time period past, present and future, using both global and regional models. Here, we quantified extremes using the suite of GCMs (Global Climate Models) and RCMs (Regional Climate Models) along with the high resolution regional coupled ocean-atmosphere model (ROM) having 0.22 X 0.22ᵒ resolution and air-sea interaction. ROM shows greater skill in simulating the PEs due to its enhanced resolution and better representation of regional air-sea interaction. The study highlights the importance of resolution and air-sea interaction in capturing the extremes and provides an insight into Pes behaviour by the end of the century to have a better preparedness plan.

We conducted radiative convective equilibrium (RCE) experiments with varying domain size and sea surface temperature (SST) using the global cloud-system-resolving model NICAM (Satoh et al. 2014) to investigate the dependence of the maximum horizontal scale of the convective cluster on SST.The experiments were conducted with the NICAM simulations with switching off convective parameterization over a non-rotating spherical domain over the area of the region by varying the radius (the Earth radius R, R/2, R/4, R/8, and R/16). The horizontal uniform constant SST was changed as 290-310K every 5 K. The threshold for the transition between multiple convective clusters and a single convective cluster is found to be between R/4 and R/2. Physical variables such as vertical profiles of temperature and humidity gradually changes as the radius becomes larger and converged at the radius R/2. For the SST dependency, the result robustly indicates that the maximum horizontal scale of the convection cluster is not monotonic with SST and it was largest for SST 300K. As the domain size increases, the domain average moistens, and the boundary layer wind speed increases. Because the diabatic radiative cooling is constrained by the temperature and humidity structure, the surface evaporation and thus the surface wind speed must also be constrained with an upper limit; this is why the maximum horizontal scale exists and there are multiple convective clusters for the domain size larger than R/2. The horizontal scale dependence of the convective cluster is related to two factors: the effect of the horizontal pressure difference in the boundary layer and the circulation structure of free troposphere. The energy budget analysis also explains the SST dependence of the maximum horizontal scale of the convective clusters.

This study investigates the impacts of eastern-Pacific (EP) El Niño and central-Pacific (CP) El Niño on decaying summer extremes over East Asia (EA). 95^th percentile value represents the extreme event. The result indicates that extreme frequency, intensity, and seasonal mean precipitation show a similar pattern over EA during a particular El Niño event. Specifically, during EP El Niño, more intense extremes over the south of Yangtze River (SYR), and suppressed extremes over the Mei-Yu rainband in China, Baiu in Japan, Changma in South Korea (MBC) are observed. During CP El Niño, weaker (stronger) extremes over SYR (MBC) are found. Namely, the influence of EP and CP El Niño events on summertime intense precipitation over SYR and MBC regions appears to be opposite to each other. We have also stratified the observational data into TC and non-TC precipitation. Reduced frequent TC occurrences over Northwest Pacific Ocean basin and less intense TC-extremes over EA are found during both two types of El Niño; however, TCs have little effect on the overall extremes compared to non-TC precipitation. Further analysis shows that southward (northward)-displaced Western Pacific subtropical high (WPSH) is the main reason for the distribution of non-TC extreme precipitation during EP (CP) El Niño. When EP (CP) El Niño occurs, the westerly jet (WJ) tends to be displaced southward (northward) in relation to the positioning of WPSH, contributing to stronger vertically integrated moisture flux convergence over SYR (MBC) and hence higher probability of intense extremes there, while at the same time there is moisture flux divergence over MBC (SYR). The different flow patterns associated with El Niño diversity appear to be forced by different SST warming signals in either tropical Indian Ocean or Maritime Continent regions, which can induce anomalous regional atmospheric circulation that affects the behaviors of WPSH and WJ.

Human-induced climate change imbalances the hydrological cycle, which results in an increasing potential risk of precipitation extremes that threaten human society and environment. However, pre-monsoon precipitation over the South China Pearl River Delta (PRD) region becomes less intense in face of anthropogenic influences, as projected by global models from the Coupled Model Intercomparison Project Phase 5 (CMIP5). Possible reasons for such human impacts on a pre-monsoon extreme precipitation event, that occurred on 15 May 2016 in PRD with a total rainfall amount reaches 435 mm, are explored with the help of the Weather Research and Forecasting (WRF) model. The extreme rainfall was reproduced by WRF at a 2km resolution, forced by ERA5 reanalysis as the initial and boundary conditions (denoted as CTL). Two counterfactual simulations were conducted for attribution of this event, in which we removed human influences on 1) temperature, humidity, and horizontal winds, and 2) the first two variables from ERA5. These anthropogenic forcings are derived from the difference between historical and natural runs from the CMIP5 seven-models ensemble mean for 1986-2005. The results show that human activities have increased mean surface temperature by ~1 K in May over PRD and thus low-to-mid level water vapor amount by ~0.7 g/kg (~5%), which is approximately CC scaling of 7%/K. In spite of the increased moisture, extreme rainfall in CTL run is reduced through comparison with counterfactual simulations. This precipitation suppression is mainly resulted from the human-forced dynamic effects of strong descent, together with increased convective inhibition due to decreased relative humidity. Further comparisons between two counterfactual runs illustrate that rainfall reduction is slightly alleviated in consequence of human-related strong wind shear and enhanced northward moisture transport. The above results clearly suggest the dominance of human-influenced dynamic contributions to this pre-monsoon extreme precipitation event.

Turbulence dissipation rate (TDR) indicates the rate at which turbulence kinetic energy cascades down from larger-scale eddies to smaller ones. Cube root of TDR is defined as eddy dissipation rate (EDR), and is a standard metric of turbulence intensity by the International Civil Aviation Organization. Characteristics of low-level turbulence were investigated using observations at Boseong Meteorological Observatory (BMO). BMO is one of testbeds of the World Meteorological Organization, and is located at the southern coastline of the Korean Peninsula. Four high-frequency 3D sonic anemometers that measure wind velocity with 20 Hz rate are installed at BMO. Wind measurements from Jan 2015 to Dec 2019 were used after excluding the records at which precipitation exists. Three EDR calculation methods were tested: (i) inertial dissipation method (IDM) using structure functions (SFs), (ii) IDM using power spectra, and (iii) maximum likelihood estimation using von Kármán spectral models. Time series of EDRs showed various fluctuations with dominant diurnal variations corresponding to the diurnal evolution of the planetary boundary layer (PBL) at BMO. It was found that the diurnal variations in the EDRs are stronger in summer than other seasons because of enhanced incoming solar radiation. Probability distribution functions (PDFs) of the EDRs were calculated by only using the EDRs estimated from IDM using SF. As a result, PDFs of the EDRs in summer time only show a distinct feature of diurnal transition from log-Weibull (daytime) to ognormal (nighttime) distributions when stability is determined by the Obukhov length. Such a transition was not observed in winter, which might be related to the change of background conditions that could drive different forcing to PBL at BMO. Acknowledgement: This research is supported by the Korean Meteorological Administration Research and Development Program (KMI2020-01910), and by the National Research Foundation of Korea Research and Development Program (NRF- 2019R1I1A2A1060035). 

Jet stream is modulated by climate change, so that prediction of clear air turbulence (CAT) becomes more difficult. We investigated the spatial and temporal distributions of the CAT occurrence in Northern Hemisphere (NH) by using more than 30 years of the European Centre for Medium range Weather Forecast Reanalysis version 5 (ERA5) data on 00, 06, 12, and 18 UTC with 0.25° x 0.25° horizontal grid spacing. We used the Turbulence Index version 1 and 2 (TI1 and T2) because it is widely used for predicting the CAT caused by shear instability and emission of inertia gravity waves near upper level front and jet system. To understand spatial and temporal distributions of Moderate or Greater (MOG)-level CAT that is hazardous for safe air-travel, values of the top 5 percentile of the TI and component indices [TI1, TI2, vertical wind shear (VWS), deformation (DEF), divergence (DIV)] were used as the thresholds for strong CAT. In NH, frequency of MOG-level CAT revealed in all indices was high in the northern side of jet stream in both summer (June, July, August) and winter (December, January, February). In winter, strong VWS was found in East Asia, which is entrance region of the East Asian jet, and the region with strong upper-level front was matched well with high TI1 values. DEF and DIV appeared strong in the Northeastern Pacific, Northeastern America, and Northern Atlantic regions near the exit region of jet stream, which was consistent with high TI2 values. In summer, the frequency of MOG-level CAT decreased due to the weakening of mid-latitude jet stream with poleward shift. Increase of annual frequency was found in some regions, which might be due to climate change. Acknowledgement: This research is supported by the National Research Foundation of Korea Research and Development Program (NRF-2019R1I1A2A1060035). 

We developed the in-flight aircraft icing algorithm using the Korean Meteorological Administration (KMA)’s global operational Numerical Weather Prediction (NWP) model. The Simplified Forecast for Icing Potential (SFIP) algorithm is implemented to the Unified Model (UM) forecast outputs that is currently operational in the KMA. The SFIP algorithm is a fuzzy logic-based icing diagnostic system that is composed of membership functions for temperature (T), relative humidity (RH), vertical velocity (W), and cloud liquid water content (CLWC). Five versions of the SFIP having different weights for each membership function were tested. For objective verification, we used large samples of pilot reports (PIREPs) provided by the National Oceanic and Atmospheric Administration/Aviation Weather Center (NOAA/AWC) for the period from 1 October 2015 to 31 July 2018. Due to the lack of PIREPs in East Asia, PIREPs near the United States were mainly used in this study. For improving the current version of the SFIP, we also investigated the climatology of icing by constructing the probability distribution functions (PDFs) of model variables (T, RH, W, CLWC) matching with observed icing PIREPs. It is found that the PDFs are generally similar to the current version of the membership functions for each variable with minor discrepancies in lower values of RH. Statistical verifications of the current and updated versions of the SFIP using the receiver operating characteristic curves showed that updated version has slightly better performance against observed PIREPs. Acknowledgement: This research is supported by the Korean Meteorological Administration Research and Development Program (KMI2020-01910), and by the National Research Foundation of Korea Research and Development Program (NRF- 2019R1I1A2A1060035). 

A low sea surface temperature (SST) region extends southward in the central part of southern South China Sea during boreal winter, which is called the South China Sea cold tongue (SCS CT). This talk presents an analysis of the factors of interannual variation of SST in the SCS CT region and the individual and combined impacts of El Niño-Southern Oscillation (ENSO) and East Asian winter monsoon (EAWM) on the SCS CT intensity. During years with ENSO alone or with co-existing ENSO and anomalous EAWM, shortwave radiation and ocean horizontal advection play major roles in the interannual variation of the SCS CT intensity. Ocean advection contributes largely to the SST change in the region southeast of Vietnam. In strong CT years with anomalous EAWM alone, surface wind-related latent heat flux has a major role and shortwave radiation is secondary to the EAWM-induced change of the SCS CT intensity, whereas the role of ocean horizontal advection is relatively small. The above differences in the roles of ocean advection and latent heat flux are associated with the distribution of low level wind anomalies. In anomalous CT years with ENSO, low level anomalous cyclone/anticyclone-related wind speed change leads to latent heat flux anomalies with effects opposite to shortwave radiation. In strong CT years with anomalous EAWM alone, surface wind-related latent heat flux anomalies are large as anomalous winds are aligned with climatological winds.

We conduct a case study of the Madden-Julian Oscillation (MJO) event observed during January and February 2017 to understand its propagation through the Maritime Continent (MC) region. Ensemble cloud-permitting numerical simulations are performed to test the effects of the islands over MC on this MJO event. The control simulation reasonably captures the large-scale mean state, eastward propagation and diurnal cycle over islands of this MJO event. Sensitivity experiments are conducted to test the impact of topography, friction and land-sea contrast on this MJO. Eliminating the topography around the MC region leads to reduced precipitation over the islands while changes in eastward propagating precipitation are small. When the friction is also removed, the results are similar except that the low-level wind is further strengthened, and the precipitation propagation of MJO is not essentially different with that in control simulation.  Land-sea contrast is further eliminated by replacing land with ocean, and the MJO is stronger and more coherent in the propagation as a result. Diagnosis of moist static energy budget indicates that both the surface flux feedback and horizontal advection (especially the zonal advection) are greatly strengthened without land-sea contrast, which enhance the convection over the sea and facilitate the eastward propagation of the MJO. The results suggest that the processes related to the low heat capacity of the islands may have a profound impact on the propagation of the MJO through MC.

Information on future changes in early-summer precipitation around Japan is crucial for future disaster preventions. Using the method developed by Yokoyama et al. (2019), we project future changes in precipitation characteristics by combining GPM satellite-borne precipitation radar and simulations with 19 CMIP6 climate models, and examine their multi-model variations. We classify rainfall events into three types, according to GPM-observed precipitation characteristics. One is “small” type that includes localized heavy showers. Another is and “organized” type, which often brings heavy rainfall in the later stage of Baiu season. Contributions from each type of precipitation are tabulated with sea surface temperature (SST) and mid-tropospheric large-scale ascent, obtained from OISSTv2 and JRA55 reanalysis data, respectively. Based on the precipitation-environment relationships, we then reconstruct each type of precipitation with CMIP6 large-scale environments for current and future climates. Small-type precipitation is projected to increase around Japan due to an overall increase in SST. Organized precipitation is projected to expand northward in all models, suggesting an elevated risk of heavy rainfall mainly in eastern Japan, where its present amount is relatively small. In western Japan, multi-model ensemble mean change in organized precipitation is slightly negative with large multi-model variations. Further analyses show that Baiu fronts tend to be weakened (intensified) associated with a weakening (an enhancement) of the subtropical jet around western Japan in models with negative (positive) changes in western Japan. Patterns of heavy rainfall have a range of projections attributed to different changes in large-scale environments. 

Reference: Yokoyama et al. 2019, J. Climate, 32, 5251–5274.
Acknowledgment: This study was supported by the University of Tokyo through a project ‘‘Research hub for the big data analysis of global water cycle and precipitation in changing climate,’’ and the Environment Research and Technology Development Fund (JPMEERF20192004) of the Environmental Restoration and Conservation Agency of Japan.

Madden Julian Oscillation (MJO) is the low frequency eastward propagating variability, which has an enormous impact on other tropical variabilities as well as global weather and climate. MJO is one of the dominant modes of slowly moving equatorial moisture variability, which was discovered nearly half a century ago and had a large section of theories associated with its observed features. Based on the observational results, MJO’s major convection region is controlled by its planetary-scale boundary layer moisture convergence. An underlying mechanism is proposed here to model the most fundamental characteristics of MJO, such as its eastward propagation and its preferable planetary-scale wavenumber. The dynamical framework formulated here is a 1.5 layer linear shallow water model with equatorial beta-plane approximation and momentum damping; the horizontal structure consists of a simple first baroclinic mode in the free troposphere in addition to its barotropic boundary layer dynamics. The hypothesis of the proposed dynamical framework is that the moisture dynamics in the tropics is completely governed by the moisture relaxation time scale. Our dispersion relation gives rise to an eastward propagating moist mode, which has similar large-scale characteristics of MJO. The results show that the strength of boundary layer moisture convergence feedback makes this mode unstable, particularly the large values of moisture relaxation time decrease the frequency and growth rate of this low-frequency moist mode. Here we also investigated the role of evaporation wind feedback (E-W) under the influence of Rayleigh damping. The strength of E-W feedback makes the eastward propagating MJO mode slow-down at a planetary scale and increases the growth rate. The model also demonstrates the effect of dissipation on the properties of the resulting MJO mode under the same framework. The sensitivities of these parameters on the model are also discussed. 

Moisture transport from the tropical Atlantic to the tropical Pacific is important for inter-basin freshwater exchange. Although the climatological tropical Atlantic-to-Pacific moisture transport (TAPMORT) has been well investigated, few studies have focused on its variability. Here we investigate the interannual variability of the TAPMORT using three atmospheric reanalysis data sets. The TAPMORT interannual variability shows two seasonal peaks in late boreal summer and late boreal winter, respectively. The late winter events, however, damp rapidly, only occurring in February. By contrast, the late summer events are persistent, peaking in August but lasting from July to September. These summer events are forced by the see-saw pattern of sea surface temperature anomalies associated with ENSO and Atlantic Niño. The see-saw pattern influences the low-level jet across Central America and hence modulates the TAPMORT interannual variability. We further demonstrate that the persistent TAPMORT variability in late summer dominates the moisture divergence over the northwestern tropical Atlantic and modulates freshwater flux there. Thus, our study improves the understanding of how TAPMORT interannual variability and the related see-saw pattern regulate the northwestern tropical Atlantic freshwater budget and the related salinity variability.

In this study, we examine the resolution dependence of convective spectrum in CAM5 (Community Atmospheric Model version 5) simulations, focusing on the transition from shallow to deep convection and the associated cloud radiative effect (CRE) change. We first apply the bin method (percentile binning) on precipitation intensity to obtain the convective spectrum in the tropics and the same approach is also used in the column-integrated moist static energy (MSE) budget analysis. The binning results show that over the light-rain regime, the convective structure is dominated by shallow convection which acts to destabilize the atmosphere by importing column-integrated MSE; while the heavy-rain regime shows the coexistence of deep and shallow convection which inclines to stabilize the atmosphere through exporting the column-integrated MSE. Moreover, we also note that the longwave component of CRE (LWCRE) is more sensitive to the change of model spatial resolution compared to the shortwave component of CRE (SWCRE), characterized by a stronger response in the coarser resolution run over the heavy rain regime. The resolution dependence of convective spectrum and CRE changes presented in this study points out the importance of scale-aware cumulus parameterization design in climate models, which is not yet implemented in CAM5.

The continental configuration as a primary feature of the Earth's surface, plays important roles in determining the spatial and temporal structure of monsoons. The classic picture views monsoon as a system driven by land-sea thermal contrast. Here, we examine how continental drift modify the characteristics of regional and global monsoons systematically, using the Community Atmosphere Model version 3 coupled to a slab ocean. The global monsoon (oceanic ITCZ) here is considered to cover the entire latitude zone, and regional monsoons are limited to the continental regions. As the zonally confined rectangle continent moves from high latitudes to low latitudes, the continental monsoon establishes and strengthens. The global monsoon area has an increasing trend both in the northern and southern hemispheres. In addition, we investigate the interaction between two continental monsoons locating at each hemisphere. The continent in the winter hemisphere pushes global monsoon further to summer hemisphere and enhances the zonal asymmetry of the continental summer monsoons.

Within the broader development goal of sustaining and, where possible, improving the food security of Pacific islander smallholders and their communities, the primary aim of this research was to examine how to enhance existing agricultural production through the provision of seasonal climate information in a form that allows rural communities to respond to unfolding seasonal climatic conditions. The research has examined using social network analyses as a way of determining: (1) how climate information is disseminated effectively amongst rural communities and government agencies; (2) the type, frequency and duration of community seasonal climate information needs; (3) who are most active or effective disseminators of seasonal climate information to ensure they are included in the dissemination network; and (4) possible farming options to pursue during different seasonal conditions. The social network analysis revealed some very important insights into how seasonal climate information should be effectively communicated with PNG communities.  The overall network behaviour showed that church, community, and family were the most trusted and most central groups across all villages. These three groups also created cliques (sub-networks), meaning that they interact with each other frequently. Network nodes identified as "Government" (i.e. SCF service providers) was a highly trusted source reaching the central groups, however they were only disseminators of knowledge, not recipients. This raises questions regarding the extent to which service providers are able to access and receive feedback from the communities and adjust their information dissemination strategies.

Natural hazards present varying degrees of risk all over the world with particularly devastating impacts on vulnerable communities such as those in Small Island Developing states (SIDS) and Least Developed Countries (LDCs). Thus, the proactive, inclusive and localised management of natural hazards through Disaster Risk Reduction (DRR) approaches is key to fostering long-term climate adaptation and resilience for vulnerable communities. Investment in DRR policies and strategies has increased on a global scale, however, there remains a need to effectively manage climate change at the community level in LDCs and SIDS. In LDCs and SIDS, in-situ meteorological observations are often limited in their functionality due to budgetary and infrastructural restraints. Satellite precipitation estimates derived from space-based observations provide global spatial coverage and uniformity and offer an alternative to sparse and poorly maintained in-situ observations from local rain gauges. The proactive, localised and inclusive management of hazard and disaster can be achieved through an Integrated user-centred Early Warning Systems (I-EWS). In this study, space-based inputs were used in the development of an I-EWS for drought in vulnerable country in the Pacific - Papua New Guinea (PNG). Drought hazard indicators obtained from WMO SWCEM (the Standardised Precipitation Index and the Vegetation Health Index) were used for monitoring component of an I-EWS. These drought hazard indicators were further combined with outputs from the Bureau of Meteorology’s forecasting model - the Australian Community Climate Earth-System Simulator – Seasonal (ACCESS–S), to determine the adequate combinatory thresholds that triggered staged levels of warning for such observational and predictive data for drought in PNG. Effectiveness of the developed I-EWS for drought was investigated; case studies for the 2015-16 El-Niño and the 2020-21 La Niña are presented.

Drought is one of the most frequent natural disasters in Vietnam, and it has had many impacts on the local agriculture which accounts for about one fifth of country's GDP and employs more than half of labour force. In 2015-2016, many provinces in Vietnam were severely affected by the El Niño-induced drought. After a short period of recovery, in 2019 drought again affected provinces in Mekong River Delta and Central Vietnam. It is projected that frequency and severity of drought events will increase under anthropogenic climate change. Improving preparedness to future drought events is essential to reduce economic losses and adverse impact of drought on rural communities. Drought detection and monitoring require accurate information about precipitation. Traditionally, surface-based observations are used to obtain precipitation data, and monitor evolution of drought. However, rainfall is highly variable, and in many countries including Vietnam, low density of rain gauge networks does now allow to accurately describe its spatial variability. On the other hand, space-based observations of precipitation provide global coverage and have the potential to complement in situ rainfall measurements. Recently, the World Meteorological Organization (WMO) established the Space-based Weather and Climate Extremes Monitoring (SWCEM) which provides a wide range of satellite precipitation estimates and derived products for countries in the Asia-Pacific region. Using SWCEM satellite-derived products, we conducted drought hazard assessment for Vietnam. A case study for the 2015-2016 El Niño-induced drought is presented, and results are discussed.

It is important to ensure that climate monitoring and sub-seasonal-to-seasonal (S2S) prediction products are not only of high accuracy, but also delivered to users regularly and with short lead times, in ways that they can be readily incorporated into decision-making. Climate outlooks at the global scale are disseminated by the World Meteorological Organization (WMO), while at a regional level WMO Global Producing Centres for Long-range Forecasts (GPC LRFs) and Regional Climate Centres (RCCs) play a leading role in forecast distribution. In the Pacific (WMO Region V), WMO GPC LRFs Melbourne at the Australian Bureau of Meteorology (BoM) is tasked with disseminating outputs from the dynamical climate model ACCESS-S (the Australian Community Climate Earth-System Simulator-Seasonal) to RCCs and National Meteorological and Hydrological Services (NMHSs) in the region. However, decision makers also need to know the current conditions on the ground to assess what risks and impacts may arise given the outlook for the months ahead. As part of collaborative activities between the Climate and Ocean Support Program for the Pacific (COSPPac) and the WMO Climate Risk and Early Warning Systems (CREWS), the WMO GPC LRFs portal has been re-designed to disseminate ACCESS-S-based forecast products, Space-based Weather and Climate Extremes Monitoring (SWCEM) products, and other contextual climate information. In this presentation, we introduce some of these products, including key features of ACCESS-S S2S climate outlooks, satellite precipitation estimates, tropical cyclone multi-week forecasts, and outlooks for oceanic conditions.

The RMIT SPACE Research Centre is internationally recognised in the areas of Global Navigation Satellite System (GNSS) for position, navigation and timing; space weather and ionospheric research; space objects tracking and atmospheric density modelling; as well as climate, weather and environment monitoring. In this poster, we provide an overview of the research project and engagement activities within the RMIT SPACE Centre, grouped under four key focus areas: (1) Climate and atmospheric modelling; (2) Space weather and ionospheric research; (2) GNSS applications and remote sensing; and (4) Space situational awareness.

The 2019 flood event in Townsville, Queensland in Australia has resulted in insured property losses amounting to AUD$1.2 billion (Insurance Journal, 2020), following record rainfall totals of up to 1,400 mm. This study investigates the likelihood of such event happening in the region in light of future climate change. A stochastic weather generator, MarkSim, is utilized to derive daily precipitation and temperature data from a suite of CMIP5 GCMs for both the present and three future periods (2040-2050, 2070-2080, and 2090-2100) under the RCP 2.6 and 8.5. Simulation of river and surface water flooding for the present-day period is carried out using JFlow, a two-dimensional hydraulic model. Flood simulation for a given future period follows the same approach but with an intermediate step using PC-IHACRES rainfall-runoff model to simulate daily discharge. Results from this study will address the following research questions – 1) what are the characteristics of flood in the future, 2) how do future flood characteristics compare with the 2019 event, 3) what are the estimated losses associated with future floods – which, in turn, could shed insights on the extent (and limitations) of modelling for flood insurability. 

East Asia (EA) is one of the most vulnerable regions influenced by abnormal climate change. This study describes the long-term surface air temperature (SAT) changes across EA using a new Coupled Model Intercomparison Project Phase 6 (CMIP6) multi-model simulation. Historical simulations (twentieth century) were examined based on SAT variation responses to various external and natural forcings, and future projections were also investigated for the twenty-first century. This study mainly focuses on the influence of anthropogenic forcings on EA climate for a long period (1850-2100). SAT was increased by the forcings of greenhouse gas (GHG), carbon dioxide (CO₂), and land use (LU), while it was cooled by AER forcing. In contrast, natural and solar forcings had little impact on SAT changes. SAT increased 0.082 °C/decade in response to GHG, while it increased 0.014 °C/decade owing to ALL forcing from 1850–2014. The anthropogenic forcing rapidly increased after the third industrial revolution (after 1969). Consequently, SAT change accelerated to 0.255 °C/decade and 0.268 °C/decade owing to ALL and GHG, respectively. Throughout EA, the highest warming was observed in the region of Tibet and lowest in southeast China. Overall, human-induced GHG, CO₂, and LU were the dominant factors causing SAT warming in EA. Thus, these anthropogenic influences contribute significantly to SAT warming and promote the projection of substantial warming trends. Further, we used the optimal fingerprinting method to describe the climate change caused by anthropogenic influences in EA. Anthropogenic forcings were detected clearly and separated from natural forcings in two-signal analysis. In three-signal analysis, GHG was robustly detected and separated from the other anthropogenic and natural forcings. The shared socioeconomic pathway emission scenarios showed future projections from 2015–2100. This analysis suggests that climate change can be controlled by restricting the anthropogenic forcings in EA

The compound events are defined as two or more events occurring simultaneously which may play a much larger role than any of the individual event. In particular, the recent hot topic such as studies on compound extremes, i.e., co-occurrence of heat waves and atmospheric stagnation, demonstrate that these events may exert substantial impact on ozone pollution, which is modulated together with the changes in emissions under climate change. Moreover, the effect from compound events may show nonlinearity, inferring that the amplified effect from compound extremes may turn out to be even larger than the additive effect from both heat waves and stagnation in terms of the ozone pollution. From the health perspective, we introduce the compound events in the trace element arsenic, in which we reveal the compound influence of arsenic from the atmosphere and groundwater can greatly aggravate the carcinogenic and noncarcinogenic effect on humans.

To better understand the responses of particle number concentrations (PNCs) and new particle formation (NPF) events to the largely reduced air pollutant emissions in urban atmospheres, we investigated the particle number size distributions in Qingdao, a coastal megacity in northern China, during two separate periods, 2010–2012 and 2016–2018. The results show only an average of 5% decrease in the total PNCs in 2016–2018 relative to 2010–2012, although the PM_2.5 mass concentration decreased by over 40%. The nucleation-mode PNCs decreased by 20%, which is probably attributable to reduced primary emissions. Unexpectedly, the accumulation-mode PNCs increased by 11% in 2016–2018 relative to 2010–2012. The increased accumulation-mode PNCs were probably not attributable to NPF events because their occurrence frequencies decreased from 34% in 2010–2012 to 25% in 2016–2018. The concentrations of SO₂ strongly decreased by approximately 60% between the two periods, but there were no significant changes in the apparent formation rate of new particles or net maximum increase in the nucleation-mode PNCs in NPF events. Meanwhile, the observed maximum sizes of grown new particles decreased by 50% from 2010–2012 to 2016–2018. The contribution of grown new particles to the accumulation-mode PNCs expectedly decreased in 2016–2018 relative to 2010–2012. The increase in accumulation-mode PNCs in 2016–2018 provides insight on the inter-annual variations in satellite-based cloud fraction, cloud optical thickness, cloud effective radius, and cloud water path in the liquid phase from 2010 to 2019, which appeared to have either weak or no response to the large decrease in satellite-based aerosol optical depth.

Air quality in Korea, especially in cities like Seoul, has been a serious public health issue over the years. Accurately understanding how much of the air pollution in Korea is domestic versus transported from outside the country is critically important. In this study we conducted air quality modeling using global and regional chemical transport models to quantify contributions of domestic sources to PM_2.5 concentrations in Korea and to quantify the role of transboundary pollution transport in increasing background PM_2.5 concentrations for Korea. We used a global chemistry model (GEOS-Chem) and a regional model (CAMx) to conduct source attribution to PM_2.5 in Korea for 2015 and 2016 to account for different meteorological conditions. Up-to-date emissions inventories for Korean and international sources were prepared using the latest information available. GEOS-Chem provided initial and boundary conditions to CAMx (with meteorology driven by the WRF model). GEOS-Chem was run at a coarse resolution globally and a fine resolution for the East Asian domain for both years and conducted sensitivity simulations without domestic anthropogenic emissions and Chinese anthropogenic emissions, respectively. The regional modeling used CAMx PM_2.5 source apportionment (PSAT) to determine contributions from 5 source sectors and 6 geographic regions within Korea. Results from GEOS-Chem showed that China’s influence on PM_2.5 in Korea varies with the highest contribution during spring when the observed concentrations are the highest. China’s contributions to PM_2.5 concentrations reach a maximum of up to 60% in January and February and a minimum of about 20% in August. On an annual basis, our analysis estimated that in 2016 Chinese anthropogenic emissions contributed 45% to PM_2.5 in South Korea followed by 40% from Korean anthropogenic emissions. Our analysis will discuss the relative contributions of different sources within the regional domain to PM_2.5 in South Korea estimated using CAMx.

Anthropogenic volatile organic compound (VOC) emissions contribute to observed ozone concentrations as well as to the formation of secondary organic aerosols within the lower troposphere. Source apportionment models have been widely employed to characterize and identify the local and regional source contributions to the measured VOC and PM. We employed positive matrix factorization (PMF) to understand the long-term changes in apportioned sources contributing to the measured PM_2.5 and VOC concentrations observed in a coastal urban airshed of South Texas.  We concluded that secondary sulfates accounted for over 30% of the measured PM_2.5. The other major sources included local traffic, industries, and heavy oil combustion from operations in the port and the ship channel connecting to the Gulf of Mexico. The impact of aged as well as fresh sea salt was also noticeable. In addition, long-range transport from biomass burning in Central America and Mexico as well as sub-Saharan dust from Africa influenced the measured PM_2.5 concentrations in South Texas on selected dust event days. Major refining and petrochemical complexes located along the ship channel, along with evaporative emissions from the storage of refined products from the loading and unloading operations dockside were identified as significant contributors to the measured VOC concentrations. In addition, the influence from local traffic, natural gas pipelines, and industrial solvent usage were other minor factors. The speciated VOC along with the apportioned source profiles were employed in calculating the ozone formation potential (OFP) for the region.  Trajectory analysis showed the influence of long-range transport of ozone on high ozone days in the urban airshed. We also noted that on high ozone days, the influence of local precursor emissions including HRVOC affected the calculated OFP.  Thus a detailed analysis of the changes in air quality over time will allow air quality planners to develop effective control strategies. 

Due to the toxicity and bioaccumulation of heavy metals to marine organisms, increase attention has been paid to the atmospheric input of trace elements to the ocean. In this study, concentrations and dry deposition fluxes of three heavy metals (Zn, Pb, Cu) in PM_2.5 over China marginal seas were calculated using a WRF-CMAQ model during Jan 2018. Anthropogenic emission inventories of 3 trace metals for China were developed based on Multi-resolution Emission Inventory for China (MEIC) and Global ship emissions database (SEIM). Total anthropogenic Zn, Pb, Cu emissions over China are 5.5×10², 3.3×102Gg and 3.3×102Gg, respectively. Among these 3 trace metals, Zn showed the highest concentrations (46.09 ng m-3) , which providing 1.14 µg m-2 d-1 dry deposition fluxes to China marginal seas . While Cu showed the lowest concentrations (25.85 ng m-3), which providing 1.45 µg m-2 d-1 to the seas during the study periods. Spatial distribution showed that, atmospheric Zn, Pb, Cu concentration and dry deposition fluxes over China marginal seas show decreasing trend with increasing distance from the coastline, and show a downward trend from north to south.

Typhoons are extreme phenomena that are difficult to study because of their chaotic behaviour but the capacity to measure their intensity can help mitigate the hazards that they bring. Previous studies suggest that there is possible relation between the typhoon intensity with typhoon eye altitude. In this research, we observe Typhoon Trami’s structure by reconstructing the three-dimensional model inside its eye. An experiment was conducted under the SATREPS/ULAT project (SATREPS: Science and Technology Research Partnership for Sustainable Development, ULAT: Understanding Lightning and Thunderstorm) where images of Typhoon Trami were taken from an aircraft last September 26, 2018. Aircraft images were used to reconstruct the 3D model inside the typhoon eye because they provide closer views of the typhoon than that of geostationary satellite images, making it easier to reconstruct a 3D model. The 3D reconstruction generated covers approximately 50 km distance from the typhoon eye at 24.3 m/pixel spatial resolution. Three cross-sections of the 3D model were analyzed, and the resulting altitude distribution was compared with the cloud-top altitude estimated by mapping the brightness temperature of the Himawari Thermal Infrared Band 13 with cloud-top height as measured by NOAA sonde data. From the 3D model, the altitude distribution ranges from 5.3 km to 14.3 km while the altitude estimated from the brightness temperature ranges from 5.2 km to 14.6 km. However, regions of altitude difference can also be observed between the two methods. This study shows that a three-dimensional model could be a good mode of typhoon visualization as it shows a more detailed typhoon structure such as the stairstep structures that was detected at some regions within the typhoon eye. This research was supported by SATREPS, funded by Japan Science and Technology Agency (JST) / Japan International Cooperation Agency (JICA).

An apparent increase in the frequency of summer temperature extremes over northern Eurasia has been observed in the past decade. Some of these high-impact events were associated with amplified waveguide teleconnections embedded in the polar front jet. In this talk, we will discuss how the waveguide teleconnections can robustly and routinely cause regional temperature extremes over northern Eurasia. First, we will discuss the dominant waveguide teleconnection trapped by the polar front jet: the British-Baikal Corridor (BBC) pattern. Second, we will discuss how the abnormal activity of the BBC pattern can cause unprecedented temperature extreme over central Europe in June 2019, which is the hottest June on record for Europe. Last, we will discuss how the temperature extremes over northern Eurasia are statistically related to the amplified waveguide teleconnections along the polar front jet in observations and large-ensemble simulations from multiple climate models.

The present study investigated dominant characteristics of autumn Arctic sea ice concentration (SIC) interannual variations and impacts of September-October (SO) mean SIC anomalies in the East Siberian-Chukchi-Beaufort (EsCB) Seas on winter Eurasian climate variability. Results showed that the decreased SO EsCB sea ice is favorable for tropospheric warming and positive geopotential height anomaly over the Arctic region one month later through transporting much more heat fluxes to the atmosphere from the open water. When entering the early winter (ND(0)J(1)), enhanced upward propagation of quasi-stationary planetary waves in the mid-high latitudes generates anomalous Eliassen-Palm flux convergence in the upper troposphere, which decelerates the westerly winds and maintains the positive geopotential height anomaly in the Arctic region. This anticyclonic anomaly extends southward into the central-western Eurasia and leads to evident surface cooling there. Two months later, it further develops toward downstream accompanied by a deepened trough, making the northeastern China experience a colder late winter (JFM(1)). Meanwhile, an anticyclonic anomaly over the eastern North Pacific excites a horizontal eastward wave train and contributes to positive (negative) geopotential height anomaly around the Greenland (Europe), favoring negative surface temperature anomaly over Western Europe. In addition, the stratospheric polar vortex is also significantly weakened in the wintertime, which is attributed to decreased meridional temperature gradient and decelerated westerly winds provides a favorable condition for much more quasi-stationary planetary waves propagating into the stratosphere. Some major features of atmospheric responses to EsCB sea ice loss are well reproduced in the CAM4 sensitivity experiments.

Global warming and abnormal climate change have resulted in an increase in the frequency of severe heatwave events. Recently, a series of extreme heatwave events have occurred in South Korea, and the damage from these events has also been increasing. Thus, it is necessary to analyze the mechanisms for generating and developing heatwaves. In this study, the long-term trend for heatwave events in South Korea was investigated using cluster analysis. Heatwave events in a 38-year period in South Korea were defined, and their synoptic patterns were categorized into three clusters. The number of heatwave days of cluster 2, which is related to the anomalous positive geopotential height (GPH) over the Kamchatka Peninsula, was found to significantly increase in recent years (2000-2018) compared with the past (1981-1999). In contrast, the frequency of cluster 3 associated with a negative GPH anomaly over the Kamchatka Peninsula decreased in the same period. There were five regions, including northern China and the Kamchatka Peninsula, where the mid-level GPH significantly increased between 2000 and 2018. This change in GPH was positively (negatively) correlated with the patterns associated to long-term variability of heatwave days of cluster 2 (cluster 3).The long-term trends of the GPH anomalies over five regions showed a significant correlation with the North Atlantic Oscillation (NAO) index during midsummer. As a result, it is likely that the heatwave events related to cluster 2 (cluster 3) have increased (decreased) in South Korea because the long-term variability of the summer NAO has recently induced a favorable (unfavorable) atmospheric condition for cluster 2 (cluster 3).

Torrential rains induced by tropical cyclones (TCs) are a major trigger of flood hazards in many coastal regions of the world. Devastating TCs causing unprecedented floods in recent years were usually characterized by low translation speeds. For example, Hurricane Harvey in 2017 lingered over Texas for 4 days, leading to the unprecedented flood. The total amount of rainfall associated with TCs over a given region is proportional to rainfall intensity and the inverse of TC translation speed. This study, based on observations and Global Climate Models, found a significant slowdown of TCs translation speed from 1961-2017 over the coast of China. The analyses of long-term observations showed a significant increase in the 90^th percentile of TC-induced local rainfall totals and significant inverse relationships between TC translation speeds and local rainfall totals over the study period. This study also showed that TCs with lower translation speed and higher rainfall totals occurred more frequently after 1990 in the Pearl River Delta in southern China. The probability analysis indicated that slow-moving TCs are more likely to generate heavy rainfall of higher total amounts than fast-moving TCs. This study provided observational evidence that the slowdown of TCs tends to elevate local rainfall totals and thus impose greater flood risks at the regional scale.