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.

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.

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.

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

近年来,中国部分地区频繁遭遇极端降雪事件袭击,造成巨大经济损失和人员伤亡.因此,亟需深入理解中国地区极端降雪变化的物理机制及其未来演变趋势,为国家防灾减灾及气候变化应对措施制定提供科学依据.本文基于CMIP6模式结果,深入开展人类活动对中国地区降雪变化的影响及其未来演变趋势预估研究.观测显示,过去几十年在中国降雪频发区,其年降雪日数呈现减少趋势但强降雪日数增加;在这些变化中能够检测到人类活动的痕迹,尤其是温室气体排放的影响.对于冬季,全球变暖背景下中国北方地区降水日数明显增加,但北方地区仍为低温控制,这有利于降雪尤其是强降雪事件的发生;到了本世纪末,中国仍有约23%的区域(主要集中在北方地区)其冬季强降雪日数呈现增加趋势.此外,中国地区降雪季长度相比当前气候减少了约41天.因此,在未来持续变暖背景下,中国北方部分地区冬季将经历更多更为集中的强降雪事件.

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

伴随全球变暖和有卫星观测记录以来北极秋季海冰面积的下降,近几年,北美、欧洲及东亚地区经历了异常的冷冬。2015年1月,北美地区也遭受了严重的冷冬和暴雪事件。文中用NCEP再分析数据显示2015年1月气温的下降主要在北美地区,且降雪覆盖明显增加。此时位势高度场负异常明显,形成了从北极地区吹向北美大陆地区的寒流,携带了大量水汽。本文结果显示异常强劲的北风和减弱的西风急流,导致了极地寒流和湿空气容易入侵北美大陆地区,是造成2015年1月北美大陆地区冷冬和暴雪事件的主要原因之一。

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.

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.

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

利用中国地面气候资料日值数据集(V3.0)逐日气象资料研究了我国江淮冬季降雪的时空变化及其与斯堪的纳维亚遥相关型(SCAND)的可能联系。结果表明:江淮冬季降雪表现出空间一致的年际变化,SCAND与江淮地区冬季降雪异常关系密切。江淮冬季降雪偏多通常对于SCAND正位相,500hPa阻塞高压、东亚大槽加强,有利于冷空气活动增强,江淮地区垂直运动增强,水汽输送增强;降雪偏少则对应SCAND负位相。研究结果有助于深入理解江淮冬季降雪异常的相关机理。

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.

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.

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.

2022年初5次降雪过程分析和预报着眼点

本文采用ECMWF(European Centre for Medium-Range Weather Forecasts)细网格和NCEP(National Centers for Environmental Prediction)模式数据、NCEP 1°×1°再分析资料、降雪加密观测和常规资料,对2022年初的5次降雪过程进行对比分析,发现5次降雪过程均为雨转雪过程,且持续时间相对较短,平原为雨夹雪或小雪到中雪,山区中到大雪,局部暴雪,数值模式预报的积雪深度与实况相差甚远;大尺度环流形势为500 hPa中低纬南支槽或弱波动配合700 hPa上的暖湿气流和中低层冷空气,造成边界层浅薄的冷垫上温度骤降而在短时间内形成降雪;相较于平原地区,高山区上空温度层结与最大上升运动中心的配置,有利于降雪粒子较长时间维持在有利于枝状雪花的形成区域,且高山区云底云水含量显著偏低、整层温度足够低,故高山区更利于暴雪的形成。

气候变暖对吉林省降雪量与新增雪深关系的影响

降雪量和积雪深度的关系是降雪预报及水文气候模拟中的重要参数。本文利用吉林省50个站点1961—2021年的降水量、积雪深度、气温、风速和天气现象等气象观测资料,分析了降雪量和新增积雪深度的关系及主要气候影响因子。结果表明,在中等及以上强度的降雪过程中,吉林省新增积雪深度(D)与降雪量(S)的比值(深量比,Rds)平均为0.96 cm·mm^(-1);该比值存在空间差异,呈西部小东部大的分布特征,且存在明显的月际、年际和年代际变化特征,其中月际变化呈现不对称的抛物线型,12月和1月为大值时段;近60年来Rds呈减小趋势,变化速率为-0.01 cm·mm^(-1)·(10a)^(-1);降雪日Rds与气温呈明显反相关关系,其中在-12~0℃的温度区间,Rds随气温上升呈明显减小趋势。气候变暖、降水量增加和风速的减小是降雪过程中降雪量与新增雪深关系年代际变化的直接原因。揭示降雪量和新增雪深的关系对于认识东北亚中高纬度降雪积雪特征及其成因具有重要意义。