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.