Projected changes in extreme snowfall events over the Tibetan Plateau based on a set of RCM simulations

Extreme snowfall events over the Tibetan Plateau(TP)cause considerable damage to local society and natural ecosystems.In this study,the authors investigate the projected changes in such events over the TP and its surrounding areas based on an ensemble of a set of 21st century climate change projections using a regional climate model,RegCM4.The model is driven by five CMIP5 global climate models at a grid spacing of 25 km,under the RCP4.5 and RCP8.5 pathways.Four modified ETCCDI extreme indices-namely,SNOWTOT,S1mm,S10mm,and Sx5day-are employed to characterize the extreme snowfall events.RegCM4 generally reproduces the spatial distribution of the indices over the region,although with a tendency of overestimation.For the projected changes,a general decrease in SNOWTOT is found over most of the TP,with greater magnitude and better cross-simulation agreement over the eastern part.All the simulations project an overall decrease in S1mm,ranging from a 25%decrease in the west and to a 50%decrease in the east of the TP.Both S10mm and Sx5day are projected to decrease over the eastern part and increase over the central and western parts of the TP.Notably,S10mm shows a marked increase(more than double)with high cross-simulation agreement over the central TP.Significant increases in all four indices are found over the Tarim and Qaidam basins,and northwestern China north of the TP.The projected changes show topographic dependence over the TP in the latitudinal direction,and tend to decrease/increase in low-/high-altitude areas.

Distinct Interannual Variability and Physical Mechanisms of Snowfall Frequency over the Eurasian Continent during Autumn and Winter

This study investigates the dominant modes of interannual variability of snowfall frequency over the Eurasian continent during autumn and winter,and explores the underlying physical mechanisms.The first EOF mode(EOF1)of snowfall frequency during autumn is mainly characterized by positive anomalies over the Central Siberian Plateau(CSP)and Europe,with opposite anomalies over Central Asia(CA).EOF1 during winter is characterized by positive anomalies in Siberia and negative anomalies in Europe and East Asia(EA).During autumn,EOF1 is associated with the anomalous sea ice in the Kara–Laptev seas(KLS)and sea surface temperature(SST)over the North Atlantic.Increased sea ice in the KLS may cause an increase in the meridional air temperature gradient,resulting in increased synoptic-scale wave activity,thereby inducing increased snowfall frequency over Europe and the CSP.Anomalous increases of both sea ice in the KLS and SST in the North Atlantic may stimulate downstream propagation of Rossby waves and induce an anomalous high in CA corresponding to decreased snowfall frequency.In contrast,EOF1 is mainly affected by the anomalous atmospheric circulation during winter.In the positive phase of the North Atlantic Oscillation(NAO),an anomalous deep cold low(warm high)occurs over Siberia(Europe)leading to increased(decreased)snowfall frequency over Siberia(Europe).The synoptic-scale wave activity excited by the positive NAO can induce downstream Rossby wave propagation and contribute to an anomalous high and descending motion over EA,which may inhibit snowfall.The NAO in winter may be modulated by the Indian Ocean dipole and sea ice in the Barents-Kara-Laptev Seas in autumn.

Causes of a Heavy Snowfall Process in Eastern Yunnan in 2022

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 ℃ 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 θ se 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.

Snowfall Shift and Precipitation Variability over Sikkim Himalaya Attributed to Elevation-Dependent Warming

Sikkim Himalaya hosts critical water resources such as glacial,rain,and snow-fed springs and lakes.Climate change is adversely affecting these resources in various ways,and elevation-dependent warming is prominent among them.This study is a discussion of the elevation-dependent warming(EDW),snowfall shift,and precipitation variability over Sikkim Himalaya using a high-resolution ERA5-land dataset.Furthermore,the findings show that the Sikkim Himalaya region is experiencing a warming trend from south to north.The majority of the Sikkim Himalayan region shows a declining trend in snowfall.A positive advancement in snowfall trend(at a rate of 1 mm per decade)has been noticed above 4500 meters.The S/P ratio indicates a shift in snowfall patterns,moving from lower elevations to much higher regions.This suggests that snowfall has also transitioned from Lachung and Lachen(3600 m)to higher elevated areas.Moreover,the seasonal shifting of snowfall in the recent decade is seen from January-March(JFM)to February-April(FMA).Subsequently,the preceding 21 years are being marked by a significant spatiotemporal change in temperature,precipitation,and snowfall.The potent negative correlation coefficient between temperature and snowfall(–0.9),temperature and S/P ratio(–0.5)suggested the changing nature of snowfall from solid to liquid,which further resulted in increased lower elevation precipitation.The entire Sikkim region is transitioning from a cold-dry to a warm-wet weather pattern.In the climate change scenario,a drop in the S/P ratio with altitude will continue to explain the rise in temperature over mountainous regions.

Environmental factors influencing snowfall and snowfall prediction in the Tianshan Mountains, Northwest China

Snowfall is one of the dominant water resources in the mountainous regions and is closely related to the development of the local ecosystem and economy. Snowfall predication plays a critical role in understanding hydrological processes and forecasting natural disasters in the Tianshan Mountains, where meteorological stations are limited. Based on climatic, geographical and topographic variables at 27 meteorological stations during the cold season(October to April) from 1980 to 2015 in the Tianshan Mountains located in Xinjiang of Northwest China, we explored the potential influence of these variables on snowfall and predicted snowfall using two methods: multiple linear regression(MLR) model(a conventional measuring method) and random forest(RF) model(a non-parametric and non-linear machine learning algorithm). We identified the primary influencing factors of snowfall by ranking the importance of eight selected predictor variables based on the relative contribution of each variable in the two models. Model simulations were compared using different performance indices and the results showed that the RF model performed better than the MLR model, with a much higher R^2 value(R^2=0.74; R^2, coefficient of determination) and a lower bias error(RSR=0.51; RSR, the ratio of root mean square error to standard deviation of observed dataset). This indicates that the non-linear trend is more applicable for explaining the relationship between the selected predictor variables and snowfall. Relative humidity, temperature and longitude were identified as three of the most important variables influencing snowfall and snowfall prediction in both models, while elevation, aspect and latitude were of secondary importance, followed by slope and wind speed. These results will be beneficial to understand hydrological modeling and improve management and prediction of water resources in the Tianshan Mountains.

Integrated reliability of travel time and capacity of urban road network under ice and snowfall conditions

In order to evaluate and integrate travel time reliability and capacity reliability of a road network subjected to ice and snowfall conditions,the conceptions of travel time reliability and capacity reliability were defined under special conditions.The link travel time model(ice and snowfall based-bureau public road,ISB-BPR) and the path choice decision model(elastic demand user equilibrium,EDUE) were proposed.The integrated reliability was defined and the model was set up.Monte Carlo simulation was used to calculate the model and a numerical example was provided to demonstrate the application of the model and efficiency of the solution algorithm.The results show that the intensity of ice and snowfall,the traffic demand and supply,and the requirements for level of service(LOS) have great influence on the reliability of a road network.For example,the reliability drops from 65% to 5% when the traffic demand increases by 30%.The comprehensive performance index may be used for network planning,design and maintenance.

The Cloud Processes of a Simulated Moderate Snowfall Event in North China

The understanding of the cloud processes of snowfall is essential to the artificial enhancement of snow and the numerical simulation of snowfall. The mesoscale model MM5 is used to simulate a moderate snowfall event in North China that occurred during 20-21 December 2002. Thirteen experiments are performed to test the sensitivity of the simulation to the cloud physics with different cumulus parameterization schemes and different options for the Goddard cloud microphysics parameterization schemes. It is shown that the cumulus parameterization scheme has little to do with the simulation result. The results also show that there are only four classes of water substances, namely the cloud water, cloud ice, snow, and vapor, in the simulation of the moderate snowfall event. The analysis of the cloud microphysics budgets in the explicit experiment shows that the condensation of supersaturated vapor, the depositional growth of cloud ice, the initiation of cloud ice, the accretion of cloud ice by snow, the accretion of cloud water by snow, the deposition growth of snow, and the Bergeron process of cloud ice are the dominant cloud microphysical processes in the simulation. The accretion of cloud water by snow and the deposition growth of the snow are equally important in the development of the snow.

The role of diminishing Arctic sea ice in increased winter snowfall over northern high-latitude continents in a warming environment

Large parts of North America, Europe, Siberia, and East Asia have experienced cold snaps and heavy snowfalls for the past few winters, which have been linked to rapid decline of Arctic sea ice. Although the role of reduction in Arctic sea ice in recent cold and snowy winters is still a matter of debate, there is considerable interest in determining whether such an emerging climate feedback will persist into the future in a warming environment. Here we show that increased winter snowfall would be a robust feature throughout the 21st century in the northeastern Europe, central and northern Asia and northern North America as projected by current-day climate model simulations under the medium mitigation scenario. We argue that the increased winter snowfall in these regions during the 21st century is due primarily to the diminishing autumn Arctic sea ice （largely externally forced）. Variability of the winter Arctic Oscillation （dominant mode of natural variability in the Northern Hemisphere）, in contrast, has little contribution to the increased winter snowfall. This is evident in not only the multi-model ensemble mean, but also each individual model （not model-dependent）. Our findings reinforce suggestions that a strong sea ice-snowfall feedback might have emerged, and would be enhanced in coming decades, increasing the chance of heavy snowfall events in northern high-latitude continents.

Future changes in daily snowfall events over China based on CMIP6 models

China has been frequently affected by severe snowstorms in recent years that have particularly large economic and human impacts.It is thus of great importance to increase our understanding of the underlying mechanisms of and future changes in snowfall occurrences over China.In this study,the effects of anthropogenic influences on snowfall and the associated future changes are explored using new simulations from CMIP6(phase 6 of the Coupled Model Intercomparison Project)models.Observational evidence reveals a decrease in the annual total snowfall days and an increase in intense snowfall days over the snowfall-dominated regions in China during recent decades.Fingerprints of anthropogenic influences on these changes are detectable,especially the impacts of increased greenhouse gas emissions.During the winter seasons,low temperatures still cover the regions of northern China,and the associated precipitation days show an increase due to anthropogenic warming,which substantially benefits the occurrence of snowfall over these regions,particularly for intense snowfall events.This is also true in the future,despite rapid warming being projected.By the end of this century,approximately 23%of grids centered over northern China are projected to still experience an increase in daily intense snowfall events in winters.Additionally,the length of the snowfall season is projected to narrow by nearly 41 days compared to the current climate.Thus,in the future,regions of China,especially northern China,are likely to experience more intense snowfall days over a more concentrated period of time during the winter seasons.

Analysis of the extremely cold and heavy snowfall in North America in January 2015

With global warming and declining Arctic sea ice area in autumn observed by satellites since 1979, anomalous cold snaps in recent winters have affected large parts of North America, Europe, and East Asia. In January 2015, North America suffered extremely cold and heavy snowfall events. As revealed in this paper, the NCEP reanalysis data show that the temperature decreased significantly in January 2015 in North America, including the air temperature in the troposphere and the surface air temperature. Moreover, snow cover increased obviously in January 2015 in North America, while there was a significant negative anomaly of geopotential height. The wind formed the anomalous pattern, which favored cold currents blowing to the North American continent from the polar region, and bringing plenty of water vapor. Our results suggest that the anomalous north wind and decreasing westerly jet stream, which allowed cold and moist air to easily penetrate the North American continent from the Arctic, was one of the main reasons for the extremely cold and heavysnow winter of 2015 in North America.

Possible connection between anomalous activity of Scandinavian Atmospheric Teleconnection Pattern and winter snowfall in the Yangtze-Huaihe River Basin of China

The temporal and spatial characteristics of winter snowfall in the Yangtze–Huaihe River Basin (YHRB) of China and its possible connection with Scandinavian Atmospheric Teleconnection Pattern (SCAND) anomalies are explored based on daily meteorological data contained in the Daily Surface Climate Dataset for China (V3.0) during the period 1960–2012. Results show that winter snowfall in the YHRB exhibits consistent anomalies over the whole region for the interannual variation during 1960–2012. Further analysis suggests that winter snowfall anomalies in the YHRB are closely linked to the anomalous wintertime SCAND activity. When there is more winter snowfall in the YHRB, SCAND is usually in a positive phase, accompanied by a strengthened Urals blocking high and East Asian trough, which is conducive to strengthened cold-air activity, intensified vertical motions, and more water vapor transport in the YHRB. In contrast, less winter snowfall in the YHRB usually happens in the negative phase of SCAND. Our results provide useful information to better understand the relevant mechanism responsible for anomalous winter snowfall in this area.

Diagnostic Analysis of a Snowfall Weather in Beijing,Tianjin and Hebei in 2010

[ Objective] The research aimed to analyze a local snowstorm weather process which happened in Beijing, Tianjin and Hebei during I - 4 January, 2010. [ Method] Based on routine meteorological observation data and NCEP/NCAR 2.5° ×2.5° grid data （four times every day）, a lo- cal snowstorm weather process which happened in Beijing, Tianjin and Hebei during 1 -4 January, 2010 was carried out diagnostic analysis by using composite analysis method. [Result] Circumfluence on the ground and strong cold advection in the rear of upper trough were the main weath- er system of the snowfall. The deep thick wet layer and strong water vapor convergence provided sufficient water vapor for snowfall. The divergence field of low-level convergence and high^level divergence, dynamic coupling effect of vorticity provided favorable dynamic condition upwardly for the occurrence of strong snowfall. The steep dense area of Oso, low temperature at the ground layer and inversion temperature at the high layer provided certain energy condition for the development of snowfall weather. [ Conclusion] The research provided theoretical basis for snowfall forecast in future.

Analysis of a Beijing Heavy Snowfall Related to an Inverted Trough in November 2009

This paper studies a heavy snowfall in Beijing that took place on 1 November 2009. The date of the snowfall was about one month earlier than the average. The National Centers for Environmental Prediction (NCEP) reanalysis data, conventional data, and Automatic Weather Station (AWS) data are utilized to explore the reasons for the snowfall and the influencing systems. The main conclusions are as follows: (1) It is revealed from the average geopotential height and average temperature fields at 500 hPa that the large scale circulation in November 2009 was favorable to snowfall. The cold-dry air from West Siberia and the warm-moist air from the Bay of Bengal converged in North China. In addition, it was found from the average moisture flux field at 700 hPa that the main water vapor source was in the Bay of Bengal. (2) Not only the "return current", as usually accepted, but also the inverted trough on the current had an important contribution to the snowfall. The inverted trough could produce the obvious upward motion that is an important environmental condition of snowfalls. (3) More attention should be paid to mesoscale systems such as mesolows during the cold season because of their importance, though they do not occur as frequently as in the warm season. It should be pointed out that AWS data are very useful in mesoscale system analysis during both warm and cold seasons.

Case Study on a Snowfall Event in Beijing from March 17 to 18, 2022

On March 17, 2022, a city-wide snowfall occurred in Beijing, China, with significant snowfall in Northwest China and other places. By using the surface meteorological observation data and NCEP/NCAR reanalysis data, we carried out a case study of a snowfall event in Beijing from March 17 to 18, 2022. Results show that this process had the characteristics of a wide range of influence and a large range of cooling. The temperature in the north of the middle and lower reaches of the Yangtze River changed from an obvious high to low in the previous period, and the rain and snow in northern China were obvious. The snowfall in Beijing is the result of the combined influence of warm and humid air and cold air. The warm and humid air flow from the Indo-China Peninsula all the way to the north brought abundant water vapor and unstable energy. The southward cold air and warm and humid air met and collided in the central and eastern part of China, and brought about precipitation under the combined action of atmospheric instability energy and other factors. The temperature in Beijing dropped significantly, but it still has not reached the standard of “cold spring” in the meteorological sense.

Taiwan Yushan Snowfall Activity and Its Association with Atmospheric Circulation from 1979 to 2009

Yushan is the most famous location for snow in Taiwan Willie snowIali in the subtropical zone is rare. When it is snowing in Yushan, people are experiencing unusually cold and wet weather elsewhere in Taiwan. In this study, Yushan snowfall activity from 1979 to 2009 and the related atmosphere circulation were examined with the Taiwan Central Weather Bureau＇s Yushan weather station observations and the National Centers for Environmental Prediction/Department of Energy （NCEP/DOE） reanalysis atmospheric data. To provide a quantitative measure of snowfall events, a snowfall activity index （SAI） was defined in this study. The time series of yearly SAIs shows that Yushan snowfall activity for an active year, such as 1983 （SAI =39 153） was ~118 times larger than for an inactive year, such as 1999 （SAI=331）. Our analyses show that snowfall activity is closely related to the position of the East Asian Trough （EAT） and the strength of the West Pacific High （WPH）. In active years, when the EAT shifted eastward and the strength of WPH increased, an anomalous anticyclone occurred in the West Pacific. This anticyclone introduced anomalous southwesterly flows along the southeastern cost of China's Mainland and over Taiwan, resulting in a wetter-than-normal atmosphere that favored snowfall. Alternatively, in inactive years, a drierhan-normal atmosphere resulted in sluggish snowfall seasons.

Car-following Model and Its Stability under Ice and Snowfall Conditions

In order to describe the behavior of the car under ice and snowfall conditions more realistically,a vehicle following model based on the full velocity difference model is proposed under the premise of considering the speed difference and various kinds of ice and snowfall conditions. Under various road conditions,it obtains the critical stability curve of the model,and verifies that the worse the road condition is,the less stable the traffic flow is. In addition,the method of nonlinear analysis is used to obtain the solution of the kink density wave in the space headway under the unstable region. Finally,the conclusions are verified by numerical simulation,that worse road conditions,which means the road surface friction coefficient is small,will lead to greater instability region and worse anti-interference ability of traffic flow,and even cause more congestion and accidents. The conclusions make great contributions to handling the traffic jams and security issues under ice and snowfall conditions.

Diagnosis Analysis of One Cold Airflow Snowfall in Shandong Peninsula

[Objective]One cold airflow snowfall in Shandong Peninsula was analyzed.[Method] Using conventional weather observation data,the NCEP /NCAR 1° ×1° grid point by 6 h in data analysis,the synoptic weather dynamics principle and diagnosis analysis method,the cold airflow snowfall in Shandong Peninsula on December 4,2008 to 6 th was analyzed and summarized.[Result]The results showed that the cold deep groove of large scale circulation form caused the cold airflow snowfall in Shandong Peninsula.While the 850 hPa mistral wind strengthened,cold airflow snow in Shandong Peninsula will be strengthened.During the eruption of snowstorm,the relative humidity from 925 to 750 hPa was larger than 90%.The area formed by 90% relative humidity line corresponded with the period of heavy snowfall.The changes of relative humidity line reflected the changes of warm and wet air transmitting to the higher place.The more warm and wet air being sent to the upper air,the more conductive to the formation of cold airflow snowfall in Shandong Peninsula.The cold airflow snowfall had distinct temporal and spatial distribution characteristics and corresponded with the vertical increasing movement zone.[Conclusion]The study provided reference for the preciseness of short term and incoming report of cold airflow snowfall in Shandong Peninsula.

Comparative Analysis of Two Snowfall Weather Processes at Nanjing Airport in Early 2022

In early 2022,two snowfalls of different magnitudes occurred in southern Jiangsu and Anhui,which had different impacts on the operation of Nanjing Airport.Based on NCEP reanalysis data and the WRF3.9 model,the weather condition and the physical quantity fields of two different situations were mainly compared and analyzed.The results show that the snowstorm occurred in the left front of the low-level jet stream and in the wind speed convergence area of the 700 h Pa shear line.The reasonable configuration of the convergence area of the water vapor flux divergence and the rising motion field can be regarded as an important reason for the occurrence of the snowstorm.Through the comparative analysis of these two snowfalls of different magnitudes,the focus of the short-term forecast of heavy snowfall at Nanjing Airport was preliminarily drawn:the 0℃line at 700 h Pa basically pressed southward to the south of 31°N,and the 0℃line at 850 h Pa pressed southward to the south of 30°N.Surface temperature was≤0℃,and temperature at 925-800 h Pa was≤-3 or-4℃;temperature at 700 h Pa was<0℃,and there was temperature inversion in the middle and lower troposphere.In the model forecast output field,the proportion of the mixing ratio of frozen precipitation in the near-surface atmosphere to the mixing ratio of water vapor that can condense into precipitation is very important,and can be used to determine the evolution of rain and snow boundaries and sleet areas or the south of rain and snow transition zone and precipitation phase.

Analysis of a Snowfall Process in North China during February 12-13, 2022

This research analyzed a snowfall process in north China during February 12-13, 2022. By using synoptic and numerical analysis, it is concluded that this snowfall process was mainly caused by trough, low-level vortex, shear line and Siberian High. Meanwhile, an easterly wind that transports water vapor from the Bohai to North China, was the water resource of the snowfall process. Relative humidity in the low atmosphere was above 80%, providing an excellent humidity condition for snowfall. Positive vorticity and convergence induced upward motion, which offered conditions for snowfall. Numerical reconstruction is also used to show the range and the intensity of the snowfall process.

Snowfalls of Opportunity

Two years after Zhangjiakou won its bid to co- host the 2022 Winter Olympic Games, the city in north China＇s Hebei Province has made remarkable progress in its preparations and already seen a resultant boost to the local economy. Resident Zhang Zhenlong recalls with pride the moment he heard the announcement.