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Under the influence of the stable snowstorm circulation situation of the typical double-resistance type warm area in northern Xinjiang, an extremely heavy snowfall event occurred in Altay, from January 6 to 12, 2024. Several meteorological stations broke the historical maximum records for the same period, resulting in avalanches in several places of the Altay Mountains. This event can be divided into three stages according to the evolution of circulation situation and snowfall characteristics. In this study, the snowfall characteristics, circulation situation, extreme causes, and model forecasting performance of the event were analyzed using the hourly observation data of national and regional meteorological stations, ERA5 reanalysis data, and CMA-GFS, CMA-MESO, CMA-TYM, ECMWF model forecast data. The results are as follows: (1) The event was characterized by several extreme features, such as long duration, large accumulated precipitation, and large hourly precipitation. The precipitation distribution was increasing from the plain areas to the mountain areas. The strong snowfall process mainly concentrated in the second and third stages. In these two stages, the increase in snow accumulation, large hourly snowfall, and high snow-to-water ratio in the mountainous areas along the northern Altay provided key meteorological conditions for the avalanches. (2) During this event, a strong polar front at 500 hPa continuously split short-wave systems, which successively moved eastward to affect Altay. The warm shear line at 850-700 hPa was maintained for a long time, accompanied by strong warm front frontogenesis. Heavy snowfall occurred in the divergence area at the exit of the polar front jet at 300 hPa, from the north of the shear line at 850 hPa to the regions near the shear line at 700 hPa. (3) In the second and third stages, the water vapor conditions in the north of Altay, especially in the northern mountains, were abnormally strong. With the effect of terrain amplification, the low-level dynamic uplift was exceptionally strong and maintained for a long time. These were the important reasons for the extremely heavy snowfall. (4) The regional model performed better than the global model in predicting heavy snowfall, but the capability to forecast extreme snowfall was still limited. ECMWF Extreme Forecast Index (EFI) forecast product and the Ensemble Average Abnormal Weather Forecast (EMAF) product were better at identifying extreme weather signals at medium-range lead time. It is suggested to strengthen the application of related products and make adjustments according to the quantitative forecast results of the model to further improve the precision service effect of forecasting and warning of extreme weather events.

Landslides have received significant attention as an important natural disturbance that maintains biodiversity, but most previous studies have focused on the early stages of succession during years or decades in sites or small watersheds. The present study aimed to determine what regional drivers influence long-term ecological succession in large, ancient landslide scarps across a mountainous region in Japan. A landscape-level analysis of 993 landslide scarps using GIS revealed that climatic factors, especially snowfall, are important regional drivers of vegetation development on landslide head scarps in the region. While vegetation has developed on ancient landslide scarps, not all of them have returned to their pre-landslide vegetation state even though hundreds or thousands of years may have passed. The relationship between the number of vegetation types and maximum snow depth shows that where the maximum snow depth is less than 100 cm, more than 50% of the landslide scarps are covered by one type of vegetation, and the percentage of scarps covered by one type of vegetation decreases with increasing snow cover. The deeper the snow, the more vegetation types tend to develop on the landslide scarps. Since forest vegetation cannot develop due to heavy snow, meadows, grasslands, and shrublands are found on the scarps. It is concluded that the combined effects of both landslide-caused disturbances and climatic factors are creating regional diversity in vegetation types. [ABSTRACT FROM AUTHOR]

Based on NCEP/NCAR reanalysis data, Micaps data and ground observation data, the physical characteristics of a heavy snowfall process in eastern Yunnan from January 31 to February 3, 2022 were analyzed. The results show that the circulation background of the heavy snowfall process was "north-ridge and south-trough" type, and the cold air accumulated in the deep East Asian transverse trough. The cold advection behind the trough moved southwards into eastern Yunnan under the movement of the transverse trough. The establishment of upper and lower air jet provided abundant water vapor, and the snowfall area coincided with the strong water vapor convergence area. The strong cold center near the ground was maintained, and the cold air moved southwards. As a result, the cold pad was lasting and deep, and the ground temperature was 0°C or below, which was conducive to snow accumulation on the ground. Seen from the spatial distribution of pseudo-equivalent potential temperature, the low layer always had certain warm and wet conditions during the heavy snowfall, which was conducive to the establishment of unstable energy. The snowfall occurred near the 0SC steep area and the warm and wet unstable area. The vertical distribution of temperature had a good indication of precipitation form. The upper layer was controlled by strong cold advection, while the middle and lower troposphere was controlled by warm advection, and there was a warm inversion layer, which was conducive to the transformation of ice crystals into snowflakes, so that ice crystals fell to the ground in the form of snowflakes. [ABSTRACT FROM AUTHOR]

Frequent heavy snowfall in Xinjiang plays an important role in the land water cycle. In this study, 18 groups of simulation experiments are conducted on the heavy snowfall event in Xinjiang during 9–13 December of 2015 using the Weather Research and Forecasting (WRF) model. In these experiments, the combination of six land surface parameterization schemes (the Noah scheme, Noah-MP scheme, RUC scheme, CLM4 scheme, PX scheme, and TD scheme) with three microphysical parameterization schemes (the WSM6 scheme, Thompson scheme, and Lin scheme) are adopted, where the observed snowfall data are used for performance evaluation. Results show that the simulated snowfall intensity and snowfall range in different areas are very sensitive to the selection of the land surface scheme. The snowfall in southern Xinjiang is overestimated by almost all six schemes, where the Noah-MP scheme performs more reasonably than the others. The Noah scheme shows its advantage in northwestern Xinjiang. The three different microphysical schemes vary significantly in producing snowfall amount. The WSM6 scheme produced the largest snowfall amount, and the Lin scheme resulted in the smallest snowfall amount. In addition, the accumulated snowfall amounts above 10 mm are generally underestimated by all six land surface schemes, while the accumulated snowfall amounts below 10 mm are overestimated by most of the schemes. The Noah-MP scheme performs the best in the simulation of the snowfall amount in the whole region. However, the Noah scheme shows an advantage in areas with a large snowfall amount. [ABSTRACT FROM AUTHOR]

Background: Out-of-hospital cardiac arrest (OHCA) is a significant global cause of mortality, and Emergency Medical Services (EMS) response interval is critical for survival and a neurologically-favorable outcome. Currently, it is unclear whether EMS response interval, neurologically-intact survival, and overall survival differ between snowy and non-snowy periods at heavy snowfall areas. Methods: A nation-wide population-based cohort of OHCA patients, registered from 2017 through 2019 in the All-Japan Utstein Registry, was divided into four groups according to areas (heavy snowfall area or other area) and seasons (winter or non-winter): heavy snowfall-winter, heavy snowfall-non-winter, other area-winter, and other area-non-winter. The first coprimary outcome was EMS response interval, and the secondary coprimary outcome was one-month survival and a neurologically-favorable outcome at one month. Results: A total of 337,781 OHCA patients were divided into four groups: heavy snowfall-winter (N = 15,627), heavy snowfall-non-winter (N = 97,441), other area-winter (N = 32,955), and other area-non-winter (N = 191,758). Longer EMS response intervals (>13 minutes) were most likely in the heavy snowfall-winter group (OR = 1.86; 95% CI, 1.76 to 1.97), and also more likely in heavy snowfall areas in non-winter (OR = 1.44; 95% CI, 1.38 to 1.50). One-month survival in winter was worse not only in the heavy snowfall area (OR = 0.86; 95% CI, 0.78 to 0.94) but also in other areas (OR = 0.91; 95% CI, 0.87 to 0.94). One-month neurologically-favorable outcomes were also comparable between heavy snowfall-winter and other area-non-winter groups. Conclusions: This study showed OHCA in heavy snowfall areas in winter resulted in longer EMS response intervals. However, heavy snowfall had little effect on one-month survival or neurologically-favorable outcome at one month. [ABSTRACT FROM AUTHOR]

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In early February 2022, the Sapporo region, north Japan, experienced record‐breaking snowfall. During this period, a mesoscale cyclonic rotation corresponding to a polar mesocyclone (PMC) was observed over the Sea of Japan by a geostationary satellite. This study investigates important processes involved in this heavy snowfall event with attention to the role of the PMC using a 100‐member regional ensemble forecast. The initial conditions for the ensemble forecast are obtained by a regional‐scale ensemble data assimilation system that assimilates conventional observations only. Several ensemble members successfully predict heavy snowfall in the Sapporo region with an 18 hr lead time. Composite analyses reveal that these better ensemble members predict that a southward‐moving PMC with a precipitation system develops from small vortices over the ocean and approaches to the Sapporo region, whereas worse members instead predict precipitation systems shifted to the north of the Sapporo region. Further composite analyses demonstrate that the better ensemble members have environmental characteristics such as a deeper and colder upper‐level trough and large low‐level baroclinicity, which are favorable for the development of PMCs. In particular, the latter is associated with reverse shear in which PMCs tend to move southward. Therefore, these environmental factors are key to predicting the heavy snowfall event in Sapporo associated with the PMC. Plain Language Summary: Heavy snowfalls have profound societal impacts; thus, their accurate prediction is important. In early February 2022, the Sapporo region (with approximately 2 million residents), north Japan, experienced record‐breaking snowfall. This study investigates important processes during this snowfall event using a series of forecasts with small differences in the initial conditions. By comparing better and worse forecasts in terms of the amount of precipitation in the Sapporo region, this study indicates that a small rotating disturbance termed a polar mesocyclone (PMC) and an associated precipitation system resulted in heavy snowfall in the Sapporo region. The better members are characterized by environmental factors that are favorable for the development of PMCs. These factors are key to accurately predicting the heavy snowfall event in Sapporo. Key Points: Record‐breaking snowfall in Sapporo, Japan, in early February 2022 is investigated using a regional ensemble forecastComposite analyses indicate that a polar mesocyclone (PMC) and an associated precipitation system caused heavy snowfallEnsemble members with better forecasting accuracy denote environmental characteristics favorable for the development of PMCs [ABSTRACT FROM AUTHOR]

A heavy snowfall event that struck Beijing during February 12-13, 2022, affected some of the training sessions and events of the Winter Olympic Games. This heavy snowfall event was simulated using the Advanced Research Weather Research and Forecasting Model with both the two-moment bulk scheme (BULK) and the spectral bin microphysics scheme (BIN), and the differences in surface precipitation, radar reflectivity, and cloud microphysics processes were compared and analyzed. It was found that surface precipitation was dominated by solid precipitation particles. The 24-h accumulated precipitation of the BULK simulation was larger than that of the BIN simulation, but both were smaller than that observed. The BIN simulation was closer to the observations in terms of the trends of variation in precipitation rate and radar reflectivity during the period of heavy precipitation. The maximum and minimum vertical velocities of the BIN simulation were notably higher than those of the BULK simulation, and the water vapor content of the BIN scheme at the heights of the −10 to −20°C levels and above the −38°C level was substantially higher than that of the BULK scheme. The contents of cloud water and snow simulated by the BIN scheme were much higher than those simulated by the BULK scheme. The nucleation of ice crystals in the middle and high layers of the BULK scheme was obvious, whereas such a process was not evident in the BIN scheme. The net production rate of ice crystals and snow simulated by the BULK scheme was stronger near the surface than that simulated by the BIN scheme, and a second peak in the conversion rate existed at heights very close to the surface below 1 km, which might account for the greater intensity of precipitation in the BULK scheme. The latent heat simulated by the BULK scheme was larger (smaller) than that simulated by the BIN scheme below (above) the height of 2 km.

Heavy snowfall is a critical part of hydrological systems and has frequently occurred over Central Asia in recent three decades. The study focuses on the dominant synoptic circulation pattern of heavy snowfall, Central Asian vortices (CAVs), to explore the multi-timescale features and possible influencing factors during cold seasons. The frequency of CAVs in cold seasons shows the "midwinter suppression-like" pattern, which is high in late autumn and early spring but low in winter. The distribution of CAVs is mainly concentrated in the north of Kazakhstan and from the Caspian Sea to the Lake Balkhash, which has caused increased intensity and affected areas of heavy snowfall since the 1980s. The background circulation of CAVs is related to various forcing factors, among which the most important are the North Pacific Victoria mode (VM) and midlatitude North Atlantic anomaly (MNA). VM could stimulate anomalous circumglobal wave train from North Pacific to Central Asia, thereby strengthening cyclonic anomalies over northwestern Central Asia and providing conducive conditions for CAV development. During this process, MNA plays a role in replenishing the wave energy for the circumglobal wave train over North Atlantic and helps the occurrence of CAV heavy snowfall as well. On the shorter timescale, CAVs are modulated by the intraseasonal variation of VM. Within 2.5 weeks before CAV heavy snowfall days, the wave train from North Pacific connects with the downstream wave train, which leads to anomalous wave energy converging in Central Asia and favors the formation of CAVs and related heavy snowfall. [ABSTRACT FROM AUTHOR]

Central Asian low vortex (CAV) is the dominant synoptic circulation, resulting in frequent heavy snowfall over Central Asia during 1983–2018. The present study investigates winter CAVs to explore their possible causes. The results suggest that the CAVs produced near the Caspian Sea (named as Caspian Sea Vortices, CSVs) are the main component of January CAVs, which account for more than 80%, exhibiting both interannual and decadal variabilities and causing stronger heavy snowfall over Central Asia since 2004. The formation of CSV is usually due to the joint effect of both low‐frequency waves and transient waves/vortices, in which the development of the latter is prior to the former, being the prophase signal of CSV enhancement and related heavy snowfall occurrences. The dominant transient waves/vortices related to CSVs not only originate from North Atlantic but also from European continent, which respectively correspond to the decadal and interannual variabilities of CSV frequency. In terms of European continent, the transient surface warming over eastern Europe enhances the atmospheric baroclinicity at lower troposphere, which on one hand excites vertical wave activity flux transporting to the upper troposphere and disturbs the transient vortex, on the other hand causes southeastward movement of North Atlantic jet. Consequently, wave energy guided by North Atlantic jet and excited over eastern Europe both disperses downstream and enhanced transient vortex evolves into the wavelike pattern, favoring the CSV formation on the next day. The transient surface warming over eastern Europe could be thereby a reference for the predictions of CAV heavy snowfall. Key Points: The Caspian Sea Vortex (CSV) dominates the Central Asian low vortex, bringing stronger heavy snowfall over Central Asia in recent decadesCSV is jointly effected by low‐frequency waves and transient waves/vortices and the latter originate from the North Atlantic and EuropeThe transient warming over Europe is one of the reasons for the enhancement of transient vortex, which thereby favors the formation of CSVs [ABSTRACT FROM AUTHOR]

Strong cold air outbreaks caused heavy snowfall over the inland areas of the Sea of Japan coast of Japan in mid‐December 2020. The 48‐hr accumulated snowfall during the term broke a snowfall record at some observational stations of the Japan Meteorological Agency (JMA). We investigated the impacts of atmospheric and oceanic temperature changes due to historical global warming since the pre‐industrial period on this heavy snowfall event. Hindcast and pseudo non‐warming experiments were conducted using the nonhydrostatic model developed by the JMA. The historical climatic differences were obtained from the database for policy decision‐making for future climate change (d4PDF). Our experiments indicated that historical global warming enhanced precipitation over the whole region and enhanced heavy snowfall over the inland areas on the Sea of Japan side. In this event, the contribution of conversion from snowfall to rainfall due to warming was limited over coastal areas. The enhancement of precipitation was mainly caused by oceanic warming, which increased latent heat flux over the Sea of Japan and made the low‐level atmosphere less stable. Historical atmospheric warming suppressed precipitation due to atmospheric stabilization. Our results indicated that the heavy snowfall was caused by the cold air outbreaks under the warm sea surface temperatures in December and enhanced by historical global warming. Plain Language Summary: Heavy snowfall occurs over the inland areas of the Sea of Japan coast in mid‐December 2020. The 48‐hr accumulated snowfall broke a snowfall record at some observational stations. The numerical simulations indicate that historical global warming since the pre‐industrial period enhanced the heavy snowfall over the inland areas on the Sea of Japan side. The oceanic warming is more important for the enhancement of snowfall than atmospheric warming only, because oceanic warming supplies more moisture to the atmosphere and makes the low‐level atmosphere less stable. Since the sea surface temperature in December is warmer than that in other month in winter, it widely enhances snowfall over the inland areas along the Sea of Japan. Key Points: Historical global warming enhanced heavy snowfall occurring over inland areas along the Sea of Japan in central Japan in mid‐December 2020Sensitivity experiments indicate that warming of the Sea of Japan mainly contributed to the enhancement of heavy snowfallOceanic warming supplies more moisture to the atmosphere and makes the low‐level atmosphere less stable, which enhances precipitation [ABSTRACT FROM AUTHOR]

Iwamizawa, situated on the Sea of Japan side of Hokkaido, is a city in Japan that experience frequent heavy snowfall events. Warm surface-layer ocean anomalies over the Sea of Japan can induce heavy snowfall over the Sea of Japan side of Japan; however, the relationship between ocean temperature over the northern Sea of Japan and snowfall events at Iwamizawa remains uncertain. This study used reanalysis data to investigate atmospheric and oceanic circulation anomalies associated with each anomalous heavy snowfall winter month at Iwamizawa. During all anomalous snowfall winter months at Iwamizawa, a cold air anomaly with northwesterly winds existed over the Far East that was associated with a dipole pattern with anticyclone anomalies over the northern coast of the Eurasian Continent and cyclonic anomalies extending zonally over the Far East and northern Pacific Ocean. The surface cold air temperature and strong wind speed anomalies are major factors for anomalous upward turbulent heat flux over the northern Sea of Japan during all anomalous snowfall winter months at Iwamizawa. Additionally, during anomalous snowfall in January, warm surface-layer ocean anomaly over the northern Sea of Japan, which preceded the heavy snowfall events at Iwamizawa by 2 months, plays an important role in the upward turbulent heat flux anomaly. This preceding warm ocean temperature anomaly was associated with a strong Tsushima Warm Current anomaly. Results showed that the warm surface-layer ocean anomaly over the northern Sea of Japan that precedes anomalous cold advection from the Eurasian Continent also has a large impact on producing heavy snowfall events over the western Hokkaido coastal regions near Iwamizawa in January. [ABSTRACT FROM AUTHOR]

Frequent heavy snowfall in Xinjiang plays an important role in the land water cycle. In this study, 18 groups of simulation experiments are conducted on the heavy snowfall event in Xinjiang during 9–13 December of 2015 using the Weather Research and Forecasting (WRF) model. In these experiments, the combination of six land surface parameterization schemes (the Noah scheme, Noah-MP scheme, RUC scheme, CLM4 scheme, PX scheme, and TD scheme) with three microphysical parameterization schemes (the WSM6 scheme, Thompson scheme, and Lin scheme) are adopted, where the observed snowfall data are used for performance evaluation. Results show that the simulated snowfall intensity and snowfall range in different areas are very sensitive to the selection of the land surface scheme. The snowfall in southern Xinjiang is overestimated by almost all six schemes, where the Noah-MP scheme performs more reasonably than the others. The Noah scheme shows its advantage in northwestern Xinjiang. The three different microphysical schemes vary significantly in producing snowfall amount. The WSM6 scheme produced the largest snowfall amount, and the Lin scheme resulted in the smallest snowfall amount. In addition, the accumulated snowfall amounts above 10 mm are generally underestimated by all six land surface schemes, while the accumulated snowfall amounts below 10 mm are overestimated by most of the schemes. The Noah-MP scheme performs the best in the simulation of the snowfall amount in the whole region. However, the Noah scheme shows an advantage in areas with a large snowfall amount.

A sequence of a snowstorm, a quasi-stationary convergence zone (Japan Sea polar airmass convergence zone, JPCZ) and a mesoscale coastal front (MCF) caused an extreme weather disaster along the Sea of Japan (SOJ) coast in northern Japan from January 7 to 11, 2021. To examine how the presence of the Changbai Mountains (CMs) affects these multi-scale successive phenomena, we conducted numerical simulations with and without modified topography of the CMs and their surrounding regions using a regional atmospheric model with a horizontal resolution of 4 km. Backward-trajectory analyses and an additional experiment that removed the sublimation process of snow were also performed to clarify the formation and maintenance processes of the MCF. The CMs lead to the structural change of the snowstorm developing over the SOJ, enhancement of the JPCZ, and formation of the MCF, affecting heavy snowfall in the SOJ coastal areas. The MCF, which is a mesoscale phenomenon smaller than the JPCZ, is formed and maintained by the monsoonal flows that detour from the north and south of the CMs. Several of the parcels that detour from north of the CMs intrude into the MCF through the boundary layer, which is thermodynamically modified by the heat and moisture supply from the sea, whereas the inland flows that penetrate the MCF from its south are composed of two major routes: one is the flow detouring from south of the CMs that crosses the high mountains on the mainland of Japan, and the other is the parcels detouring from north of the CMs that penetrate from the inland after they land on the northern coast. The difference in equivalent potential temperature between the inland flows and the monsoonal flow from the sea is responsible for the MCF formation. A cold pool near the surface also contributes to the prolonged MCF. Understanding of the CMs’ cascading effects on multi-scale phenomena from synoptic scale to mesoscale is necessary for the prediction of extreme weather disasters over Japan in winter.

Abstract To investigate future changes in snow cover and snowfall over mountainous areas in central Japan, we conducted regional climate projections using a high-resolution non-hydrostatic regional climate model (NHRCM) with 5 km and 1 km grid spacings. Boundary conditions are derived from the database for Policy Decision making for Future climate change (d4PDF) 20 km regional climate projections (d4PDF20). The d4PDF20 assumes two future climates when global mean surface air temperatures are approximately 2 K and 4 K warmer than in the preindustrial period. Experiments with 5 km grid spacing are conducted by NHRCM for 372 years in d4PDF20 in each climate. Experiments with 1 km grid spacing are performed focusing on 5 years with heavy, median, and light snow cover of mountainous areas in each climate. In the years with heavy snow cover in 2 K and 4 K warming climates, snowfall is enhanced from late December to February at more than 2000 m above sea level (mASL) in the northern parts of Japan’s Northern Alps, resulting in heavy snow cover comparable to that in the present climate. Heavy daily snowfall remarkably increases due to global warming in the years with heavy snow cover. At low elevations below 500 mASL, snowfall decreases in all ranges of snowfall intensity in the 4 K warming climate, while the frequency of heavy daily snowfall increases in the 2 K warming climate. Precipitation is enhanced around the Japan-Sea Polar-airmass Convergence Zone and the mountainous area facing the Sea of Japan, resulting in strengthened heavy snowfall at high elevations where the winter mean temperature is approximately − 10 °C in the present climate. On the other hand, remarkable reductions in snow cover and snowfall are projected in years with light snow cover. Our results indicate that global warming causes heavy and light mid-winter snowfalls at high elevations of Japan’s Northern Alps that are more extreme than those in the present climate. Graphical abstract

This paper presents a spatiotemporal analysis of the dynamics of heavy and extreme snowfalls in the Transcarpathian region during 1990-2019. Data on snowfalls are obtained from the observation points of the state hydrometeorological network of the Transcarpathian Regional Center of Hydrometeorology. Also there are data included from the Pozhezhevska snow avalanche station (Ivano-Frankivsk region) as a representative observation point for the highland zone of the eastern part of the Transcarpathian region. The analysis took into account the date of snowfall, the amount of precipitation that fell during the snowfall, and its duration. The recurrence of different indicators of snowfall distribution was calculated for each observation point separately for the specified thirtyyear period. Some results were mapped by the isolines using kriging interpolation. Spatiotemporal heterogeneities and regularities in the distribution of heavy and extreme snowfalls have been revealed. [ABSTRACT FROM AUTHOR]

This paper reviews on the trends in extremeweather events induced by global climate change. The number of tropical cyclones (TCs) making landfall on Japan and their intensity show no discernible long-term trend in the past observation record, while the translation speed of TCs shows significant decline. The intensification of heavy rainfalls and extratropical cyclones are also confirmed. Recent simulation studies indicate that the global warming would increase the maximum wind speed and rainfall associated with the TCs. The intensification of extratropical cyclones, heavy rainfalls/snowfalls, tornados, and lightning strikes are also predicted. [ABSTRACT FROM AUTHOR]

This study focused on a quasi‐stationary convergence zone over the Sea of Japan (Japan Sea polar airmass convergence zone, JPCZ) in early winter and examined how the Changbai Mountains and the Korean Peninsula play an influential role in the formation and maintenance of the JPCZ and associated precipitation amounts in the coastal regions of central and western Japan. We performed numerical simulations with and without modified topography of the Changbai Mountains and the Korean Peninsula using a regional atmospheric model. The results show that the presence of the mountains is largely responsible for the JPCZ formation and usually contributes to the reduction of precipitation in the coastal regions. If specific conditions are satisfied, however, it can trigger heavy precipitation. One condition is the rapid growth of mesoscale eddies off the Sea of Japan coast under strong low‐level wind convergence. The precipitation band involved in the enhanced eddies slowly migrates southward and reaches the coastal regions, causing heavy snowfall. Another condition is the change in background monsoonal flows associated with synoptic‐scale cyclone development due to the orographic effect. The resultant background flows may help sustain a significant amount of precipitation in the coastal regions. Under the prevailing JPCZ, the mountains play two contradictory roles in modulating precipitation amounts in the coastal regions. [ABSTRACT FROM AUTHOR]

The problem of verification of short-term numerical forecast of hazardous and adverse weather using the WRF mesoscale atmosphere model for the territory of the Middle Urals has been considered. The meteorological situations associated with the intense precipitation and convection development in Perm krai and Sverdlovsk oblast (Russia) in 2016 have been studied. The success of heavy snow forecast has been assessed by comparison with the data from weather stations. To forecast heavy snow, data from the GFS and GEM global models have been used along with the WRF model. The comparison with data from the WRF model has demonstrated that the GEM model provides the most accurate forecast. The forecasts of convective phenomena have been assessed with the help of the object-oriented approach based on the comparison of the real and forecasted positions of mesoscale convection-allowing systems. In a number of cases, the WRF model is able to forecast the place and time of adverse weather (including the local ones), which is impossible when the synoptic method is used. The main restriction for numerical forecast of convective hazardous weather is the inability to determine the spatial position of mesoscale convection-allowing systems. Understating the gust velocity of squall winds also occurs, but this problem can be solved by reducing the grid step to 2–3 km.

To investigate future changes in snow cover and snowfall over mountainous areas in central Japan, we conducted regional climate projections using a high-resolution non-hydrostatic regional climate model (NHRCM) with 5 km and 1 km grid spacings. Boundary conditions are derived from the database for Policy Decision making for Future climate change (d4PDF) 20 km regional climate projections (d4PDF20). The d4PDF20 assumes two future climates when global mean surface air temperatures are approximately 2 K and 4 K warmer than in the preindustrial period. Experiments with 5 km grid spacing are conducted by NHRCM for 372 years in d4PDF20 in each climate. Experiments with 1 km grid spacing are performed focusing on 5 years with heavy, median, and light snow cover of mountainous areas in each climate. In the years with heavy snow cover in 2 K and 4 K warming climates, snowfall is enhanced from late December to February at more than 2000 m above sea level (mASL) in the northern parts of Japan's Northern Alps, resulting in heavy snow cover comparable to that in the present climate. Heavy daily snowfall remarkably increases due to global warming in the years with heavy snow cover. At low elevations below 500 mASL, snowfall decreases in all ranges of snowfall intensity in the 4 K warming climate, while the frequency of heavy daily snowfall increases in the 2 K warming climate. Precipitation is enhanced around the Japan-Sea Polar-airmass Convergence Zone and the mountainous area facing the Sea of Japan, resulting in strengthened heavy snowfall at high elevations where the winter mean temperature is approximately − 10 °C in the present climate. On the other hand, remarkable reductions in snow cover and snowfall are projected in years with light snow cover. Our results indicate that global warming causes heavy and light mid-winter snowfalls at high elevations of Japan's Northern Alps that are more extreme than those in the present climate. [ABSTRACT FROM AUTHOR]

Weather and climate events occasionally depending on their size and occurrence can be classified as natural disaster and unexpected that they create serious problems in the process of human life. Including in around of Iran, we are witnessing such events that one of the most dangerous is heavy snowfall days, particularly in the southern part of the Caspian Sea and especially Gillan Plain. One of the heaviest snowfall events at the study region is related to 2014 (1392). This observational study attempts to determine factors responsible for the occurrence of heavy snowfall as well atmospheric circulation at the time of occurrence, also created biological problems.The heavy snowfall that continued for several days had caused a serious disaster in the area. According to the results and identification of the snowy days, synoptic maps at the time of occurrence were prepared and analyzed. The NCEP/NCAR data reanalysis was used to clarify the structure of atmospheric circulation of heavy snowfall over the studied area. Sea level pressure, Geopotential Height, Zonal (U) and Meridional (V) wind, Specific humidity, Omega and Outgoing Longwave Radiation were used to determine the atmospheric circulation of snowfall. The results show that the precipitation has continued in Gilan plane for 5 days (30JAN, 31JAN, 1FEB, 2FEB and 3FEB). Anzali station had the highest and Manjil experienced the lowest amount. The most important factor of atmospheric circulation was strong high pressure formed in the Northern parts of Europe. This high pressure was transformed over the Caspian Sea by the Southward streams. The extreme differences in temperature between the air mass and the sea water had caused the intense convection and strong arising from the area that has led to heavy snowfall. Some of the major problems depending on this natural disaster were serious issues of resident livelihood and blocked roads of towns and villages. So to improve the management of any natural disaster, predicted this natural event early, setting up a comprehensive program to create a proper operational structure with executive ability can fix problems quickly and cause the least damage and casualties.

Prior studies have shown that above-normal sea surface temperatures (SSTs) enhance snowfall over Korea. Here, we show that heavy snow is also associated with below-normal East Sea SSTs, and we investigate the dynamical response of the atmosphere to this surface condition using observations and numerical modeling. The results indicate that anomalous southeasterly/easterly winds are induced by heavy snowfall-related cold SST anomalies, and consequently, the moisture flux is converged. The existence of the southeasterly winds and the accompanied moisture flux convergence appear to be instrumental in producing the heavy snowfall events. The anomalous southeasterly/easterly winds associated with heavy snowfall-related cold SST anomalies reduce the climatological northwesterly/westerly winds, leading to relatively warm and wet conditions over the east coast of Korea that are favorable for forming and intensifying snowfall events in the region.

On 27 March 2017, a heavy snowfall associated with cyclones caused a surface avalanche in Nasu, Tochigi Prefecture, Japan. Although it is known that large amounts of snowfall in a short time are important for surface avalanches, understanding of snowfall characteristics in mountainous regions during heavy snowfall events is lacking. We conducted a case study of this event and also performed a statistical analysis of snowfall events in Nasu from 1989 to 2017, where we investigated the snowfall characteristics and meteorological conditions of each event. In the March 2017 event, low-level supercooled water clouds were formed by orographically forced updrafts in mountainous regions in Nasu as moist northerly and easterly flows intensified due to the cyclone's approach. Localized snowfall intensification and short-duration heavy snowfalls were produced by the Seeder-Feeder mechanism associated with the low-level clouds and snow from the upper clouds of the cyclone. The statistical analysis revealed that similar heavy snowfall events occur about once every 3 years, but only once every 19 years in March. The surface pressure patterns in heavy snowfall cases in Nasu were about 63 % in the typical winter monsoon pattern and about 30 % in cyclones. Although snowfall amounts became larger as snowfall duration increased in both patterns, some short-duration heavy snowfalls exceptionally occurred in cases where occluded cyclones passed near the Kanto region. [ABSTRACT FROM AUTHOR]

Abstract: This study examined 34 lightning flashes within four separate thundersnow events derived from lightning mapping arrays (LMAs) in northern Alabama, central Oklahoma, and Washington DC. The goals were to characterize the in‐cloud component of each lightning flash, as well as the correspondence between the LMA observations and lightning data taken from national lightning networks like the National Lightning Detection Network (NLDN). Individual flashes were examined in detail to highlight several observations within the data set. The study results demonstrated that the structures of these flashes were primarily normal polarity. The mean area encompassed by this set of flashes is 375 km2, with a maximum flash extent of 2,300 km2, a minimum of 3 km2, and a median of 128 km2. An average of 2.29 NLDN flashes were recorded per LMA‐derived lightning flash. A maximum of 11 NLDN flashes were recorded in association with a single LMA‐derived flash on 10 January 2011. Additionally, seven of the 34 flashes in the study contain zero NLDN‐identified flashes. Eleven of the 34 flashes initiated from tall human‐made objects (e.g., communication towers). In at least six lightning flashes, the NLDN detected a return stroke from the cloud back to the tower and not the initial upward leader. This study also discusses lightning's interaction with the human‐built environment and provides an example of lightning within heavy snowfall observed by Geostationary Operational Environmental Satellite‐16's Geostationary Lightning Mapper. [ABSTRACT FROM AUTHOR]

An artificial cloud seeding experiment was performed over the Japan Sea in winter to show how massive seeding could be effective to mitigate heavy snowfall damage. The results showed that 20 min after cloud seeding, a portion of the radar echo beneath the seeding track was weakened to divide the radar echo into two parts. In order to analyze the results, a numerical simulation was conducted by using the Weather Research and Forecasting model verion 3.5.1. In this simulation, the seeding effects were represented as phenomena capable of changing rain particles by accreting cloud ice and snow to form graupel particles and by changing cloud liquid water to snow particles. The graupel particles fell rapidly, thus temporarily intensifying the rainfall, which subsequently decreased. Therefore, the weakened radar echo in the field experiment is deemed to have been caused by the increase in rapidly falling graupel particles. [ABSTRACT FROM AUTHOR]

The results of the forecast of two heavy snowfalls registered on October 18 and 23, 2014 in the Urals using the WRF model are presented. The application of the WRF-ARW atmospheric model to the computation of weather forecasts for the conditions of heavy widespread precipitation in the form of snow is considered. The obtained estimates of precipitation forecast are compared with the estimates of the GFS NCEP global model. The results demonstrate that both models have approximately the same accuracy of precipitation forecast in the context of the process under consideration. [ABSTRACT FROM AUTHOR]