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This study evaluated the impact of climate change on the intensity of blowing-snow events across a wide probability spectrum including extreme events by a dynamically-downscaled meteorological dataset with a large number of ensembles called d4PDF. Focusing on four sites in Hokkaido, the hourly snow transport rate (STR) was estimated from wind speed, temperature, and snowfall. The historical experiment of d4PDF can reproduce the observed distribution of STR. The +2K experiment of d4PDF indicated that the severe blowing-snow events became rarer. Moreover, the monthly maximum STR exhibited a decrease, yet it showed significant spatial differences and seasonal variations. The monthly maximum STR and its drifting term in the mid-winter was the most significantly reduced at a site along the Pacific coast. At this site, the mean snow-covered duration (SCD) from December to February was shorter than that of the other sites. Such a decrease in STR would be due to the shortening of the SCD and the substantially related to the critical temperature at the freezing point.

A bias-corrected downscaled 1-km mesh future climate dataset across Japan called NIES2020, based on five global climate models (GCMs) selected from the Coupled Model Intercomparison Project Phase 6 (CMIP6), has been used for regional impact assessments and adaptation studies under various emission scenarios. However, it is not yet revealed what determines the scenario dependence of the Japanese precipitation changes unscaled with global mean temperature changes. Here, we disentangled the inter-scenario differences in precipitation changes averaged across Japan. In the CMIP6 GCMs, the ensemble mean precipitation increases more in the mid-21^st century under low-emission scenarios than higher-emission scenarios, consistent with NIES2020. In the low-emission scenarios, rapid reductions of anthropogenic aerosol emissions from East Asia enhance the surface downward shortwave radiation around Japan, promoting evaporation and precipitation. Such high precipitation sensitivity per degree of global warming is confirmed regardless of the season. In contrast, the precipitation increase is most suppressed under a high-emission scenario with weak air pollutant mitigation. Therefore, future precipitation changes across Japan are more constrained by aerosol emission changes than global warming levels, especially in the mid-21^st century. This suggests climate response to air pollutant mitigations needs to be considered for implementing impact assessments and adaptation strategies in Japan.

To identify and characterize the synoptic-scale precipitation systems causing widespread heavy precipitation events over Japan and to evaluate their possible future changes, annual maximum of area-averaged daily and 5-day accumulated precipitation for 720 years were analyzed for both historical and 4 K warming climates using a large ensemble dataset with 5 km horizontal resolution. According to statistical cluster analysis, the approach of tropical cyclones is the primary factor causing widespread heavy precipitation events in both the historical and 4 K warming experiments, although the Baiu front and migratory extratropical cyclones also contribute to event occurrence. The frequency of tropical-cyclone-associated events is lower in the 4 K warming climate compared with the historical experiment because the occurrence frequency of tropical cyclones is lower over the western North Pacific. The decrease in frequency of tropical-cyclone-associated events leads to a relative increase in the frequency of events associated with other precipitation systems (i.e., the Baiu front and migratory extratropical cyclones) under the warming climate. The anomalous moisture supply in the 4 K warming experiment causes the widespread heavy precipitation derived from the Baiu front and migratory extratropical cyclones to intensify to reach a magnitude comparable to that of historical-climate tropical-cyclone-associated events.

Two quasi-stationary quasi-linear convective systems caused local heavy rainfall on 9 August 2013 in the northern Tohoku region of Japan. We investigate this rare event in the region using a numerical simulation and examine airflow structures and mechanisms. The amount and locations of the simulated precipitation agree well with the observed values. The environment is favorable to convective systems, and analyses based on forward trajectories and composites of convective cells clarify airflow structures. Mountains upstream of the extreme precipitation areas trigger the back-building convective systems, whereas humid low-level inflows converging below the convective systems play a role in maintaining the convective systems downstream where there are no significant mountains.

The interannual variation in the number of heavy rainfall events in Japan in 1976-2022, extracted from 3-hour accumulated precipitation (P3H) data exceeding 130 mm, showed a relatively large relationship (correlation coefficient 0.45) with sea surface temperature (SST) around the Japanese Islands. In the Kyushu area during the rainy season (June-July), the correlation coefficient with SST became considerably smaller, while a relatively large relationship (correlation coefficient 0.45) was found with the appearance frequency of 500m-height water vapor flux above 250 g m⁻² s⁻¹, suggesting that the interannual variation could be considerably influenced by the synoptic scale pressure pattern. Diurnal variations in the number of heavy rainfall events, including long-term increasing trends, were also investigated. Although less significant diurnal variations were observed on the annual basis, the events in the Kyushu area were more frequent in the morning (7-9 JST: JST = UTC + 9 hours) during the rainy season. In the Kyushu area, the 47-year long-term trend of heavy rainfall events in 4-9 JST was a 7.47-fold increase in June and July, while it was only a 1.35-fold increase in the other months.

In this study, we quantitatively evaluated the shape and fall velocity of precipitation particles in convective clouds observed by Rainscope to better understand graupel formation processes. Rainscope is a newly developed particle imaging radiosonde that provides much clearer precipitation particle images than those obtained by a conventional videosonde. In addition, it can measure particle fall velocities in clouds. Rainscope was launched into a convective cloud with active lightning and gusts on 25 June, 2022. The particle images captured by Rainscope provide detailed information on particle shapes, surface conditions, and contours, facilitating the quantitative evaluation of particle shape. The observed circularity, defined as a function of the particle circumference, and aspect ratio* indicate that graupel just above the freezing level, which coexisted with frozen particles, differs from graupel with an ice crystal as an embryo. The particle fall velocity of graupel in the lower layer was smaller than that of frozen particles and larger than that of general graupel, which forms from an ice crystal. Therefore, graupel in the lower layer likely originated from a frozen particle, which was formed by freezing a raindrop lifted by updrafts and then rimed.

Based on the station observations and reanalysis data, this study investigates the temporal variation characteristics of winter extreme snowfall events over Northeast China (NEC) and the possible causes involved. In recent four decades, the snowfall amount over NEC has a significant increasing trend, especially during the 21st century, which is dominated by its extreme component. On the contrary, the snowfall days over NEC exhibit an opposite variation trend, showing a rapid decrease during the research period. The opposite variation trends suggest a rapid increase of extreme snowfall events in this region. Composite results of 39 extreme snowfall cases reveal that the dominant circulation pattern causing the extreme events is the enhanced local meridional circulation over the north NEC, and significant relationships can be found between the northeast cold vortex (NECV) and extreme snowfall event. During the 21st century, both the 500 hPa geopotential height and the 850 hPa air temperature present negative tendencies over the middle and high latitudes of Asian continent. This is beneficial for stronger and more frequent northerly winds behind NECV to cause more intensified low-level convergence over this region and finally trigger more extreme snowfall events.

Large-ensemble experiments with global and regional climate models enable us to assess changes in the risks of local-scale heavy snowfall due to anthropogenic global warming. We conduct 100-ensemble historical and non-warming global climate experiments forced by oceanic conditions in 2021/22 when La Niña phenomena occurred, and conduct dynamical downscaling using regional climate models with 20 km and 5 km grid intervals. The 10-year return values of total winter snowfall decrease in most of Japan due to anthropogenic global warming, while they increase at high elevations and the northern parts of Japan. The winter-maximum daily snowfall is enhanced not only over high elevations but also over low elevations in Japan. Tsunan Town is located in an inland area of central Japan where the winter-maximum daily snowfall is enhanced by anthropogenic global warming. Composite analyses of winter-maximum daily snowfall events at the Tsunan weather station indicate that the enhancement of daily snowfall due to anthropogenic global warming is related to deeper troughs at 500 hPa and warmer and more humid air in the lower atmosphere in the historical 2021/22 winter than those in the non-global-warming 2021/22 winter.

On 15 August 2023, Typhoon Lan (2023) struck the Kinki region in western Japan, bringing record precipitation to the Kinki and Chugoku regions. This study investigates a turbulent transport scheme that can predict precipitation more accurately using the Weather Research and Forecasting model. The turbulent transport schemes compared are the Yonsei University scheme, the Mellor–Yamada–Nakanishi–Niino (MYNN) scheme, and the eddy-diffusivity mass-flux (EDMF) scheme, which is a blend of the MYNN scheme and a mass-flux scheme. Simulations are performed for a domain with a horizontal resolution of 5 km. The results show that the simulated track and central pressure of the typhoon over the Sea of Japan vary depending on the turbulent transport schemes, the MYNN scheme reasonably reproduces the distribution of heavy precipitation areas, the EDMF scheme even improves the quantitative prediction of precipitation, and the formulation of the turbulent length scale is also a key factor for the better prediction using the EDMF scheme. The EDMF scheme is expected to become a leading turbulent transport scheme in operational forecast models.

 Since the end of continuous rocket-sonde observations, which had been conducted until the 1990s, direct observations at altitudes higher than 30 km have been conducted only intermittently, so there are fewer observation data than in lower altitude regions.

 In the present study, we conducted radiosonde observations with large rubber balloons to obtain vertical structures of wind velocity and temperature at altitudes higher than 30 km from 27^th September to 3^rd October 2022 at the University of the Ryukyus, Okinawa Island, Japan.

 During the observation period, temperatures from 20 to 40 km altitude basically increased monotonically, including small perturbations. However, an observation at 1730 JST on 28^th September showed a remarkable continuous decrease with altitude in temperature at 30-36 km altitude. This was also confirmed by Constellation Observing System for Meteorology, Ionosphere and Climate (COSMIC)-2 GNSS-RO temperature data observed near Okinawa Island and ERA5 reanalysis data. Using the ERA5 reanalysis and radiosonde observation data, we found that the temperature-depleted layer is caused by a planetary-scale wave and upward energy propagating inertia gravity wave.