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.

Effect of Temperature on Frost-Free Days and Length of Crop Growing Season across Southern Ontario

Climate change has an impact on various climatic variables. In this study our focus is mainly on temperature characteristics of climate parameter. In temperate and humid regions like southern Ontario, the effect of climate change on Frost-free days in winter is distinctive. The average annual temperature is going upward but the extreme increase is in the winter temperature. Winter average temperature is going up by about 2˚C. However, extreme daily minimum temperature is going up by more than 3˚C. This climate effect has a great impact on the nature of precipitation and length of frost-free days. The snowfall over winter months is decreasing and the rainfall is increasing. However, the number of frost-free days during late fall months, early winter months, late winter months and early spring months are increasing. This result reveals an increase in length of the growing season. This research focuses on the effect of change in climatic variables on Frost-free days in Southern Ontario. Therefore, special attention should be given to the effect of change in climate Frost-free conditions on length of crop growing in winter season for potential investigation.

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.

Glacier mass balance in High Mountain Asia inferred from a GRACE release-6 gravity solution for the period 2002–2016

We provide estimates of glacier mass changes in the High Mountain Asia (HMA) area from April2002 to August 2016 by employing a new version of gravity solutions of the Gravity Recovery and ClimateExperiment (GRACE) twin-satellite mission. We find a total mass loss trend of the HMA glaciers at a rateof –22.17 (±1.96) Gt/a. The largest mass loss rates of –7.02 (±0.94) and –6.73 (±0.78) Gt/a are found forthe glaciers in Nyainqentanglha Mountains and Eastern Himalayas, respectively. Although most glaciers inthe HMA area show a mass loss, we find a small glacier mass gain of 1.19 (±0.55) and 0.77 (±0.37) Gt/a inKarakoram Mountains and Western Kunlun Mountains, respectively. There is also a nearly zero massbalance in Pamirs. Our estimates of glacier mass change trends confirm previous results from the analysisof altimetry data of the ICESat (ICE, Cloud and Land Elevation Satellite) and ASTER (AdvancedSpaceborne Thermal Emission and Reflection Radiometer) DEM (Digital Elevation Model) satellites inmost of the selected glacier areas. However, they largely differ to previous GRACE-based studies which weattribute to our different post-processing techniques of the newer GRACE data. In addition, we explicitlyshow regional mass change features for both the interannual glacier mass changes and the 14-a averagedseasonal glacier mass changes. These changes can be explained in parts by total net precipitation (netsnowfall and net rainfall) and net snowfall, but mostly by total net radiation energy when compared to datafrom the ERA5-Land meteorological reanalysis. Moreover, nearly all the non-trend interannual masschanges and most seasonal mass changes can be explained by the total net radiation energy data. The massloss trends could be partly related to a heat effect due to increased net rainfall in Tianshan Mountains, QilianMountains, Nyainqentanglha Mountains and Eastern Himalayas. Our new results for the glacier mass changein this study could help improve the understanding of glacier variation in the HMA area and contribute tothe study of global change. They could also serve the utilization of water resources there and in neighboringareas.

Canopy interception loss in a Pinus sylvestris var. mongolica forest of Northeast China

Pinus sylvestris var. mongolica is one of the main species to be afforested in deserts of China. But little work has been carried out on the canopy interception loss of this plant species. For researching the canopy interception loss of a natural P. sylvestris forest, we observed the gross precipitation, gross snowfall, throughfall and stemflow in a sample plot at the Forest Ecosystem Research Station of Mohe in the Great Khingan Mountains of Northeast China from July 2012 to September 2013. Considering the spatial variability of the throughfall, we increased the area rather than the number of collector and randomly relocated them once a week. The results demonstrated that the throughfall, stemflow, and derived estimates of rainfall and snowfall interception loss during the main rainy and snowy seasons were 77.12%±5.70%, 0.80%, 22.08%±5.51% and 21.39%±1.21% of the incident rainfall or snowfall, respectively. The stemflow didn＇t occur unless the accumulated rainfall reached up to 4.8 mm. And when the gross precipitation became rich enough, the stemflow increased with increasing tree diameters. Our analysis revealed that throughfall was not observed when rainfall was no more than 0.99 mm, indicating that the canopy storage capacity at saturation was 0.99 mm for P. sylvestris forest.

Snowstorm over the Southwestern Coast of the Korean Peninsula Associated with the Development of Mesocyclone over the Yellow Sea

This study investigates the characteristics of a heavy snowfall event over the southwestern part of the Korean Peninsula on 4 December 2005. The snowstorm was a type of mesoscale maritime cyclone which resulted from barotropic instability, and diabatic heating from the warm ocean in continental polar air masses. Based on surface observations, radiosonde soundings, MTSAT-1R satellite data and the 10-km grid RDAPS （Regional Assimilation and Prediction System based on the PSU/NCAR MM5） data, the evolution of the mesocyclone is explained by the following dynamics; （1） In the initial stage, the primary role in the cyclogenesis process of the mesocyclone is a barotropic instability in the horizontal shear zone. （2） In the developing stage, the mesocyclone moves and deepens into a baroclinic zone corresponding to the surface heating and moistening. （3） In the mature stage, it is found that the mesocyclone is intensified by the destabilization caused by enhanced low-level heating and condensation, the moisture flux convergence, and the interaction between upper and lower-level potential vorticity anomalies. We suggest that a checklist with stepwise indicators responsible for development be prepared for the forecasting of heavy snowfall over the southwestern part of the Korean Peninsula.

Airborne Measurements of the Impact of Ground-based Glaciogenic Cloud Seeding on Orographic Precipitation

Data from in situ probes and a vertically-pointing ram-wave Doppler radar aboard a research aircraft are used to study the cloud microphysical effect of glaciogenic seeding of cold-season orographic clouds. A previous study （Geerts et al., 2010） has shown that radar reflectivity tends to be higher during seeding periods in a shallow layer above the ground downwind of ground-based silver iodide （AgI） nuclei generators. This finding is based on seven flights, conducted over a mountain in Wyoming （the Unites States）, each with a no-seeding period followed by a seeding period. In order to assess this impact, geographically fixed flight tracks were flown over a target mountain, both upwind and downwind of the AgI generators. This paper examines data from the same flights for further evidence of the cloud seeding impact. Com- posite radar data show that the low-level reflectivity increase is best defined upwind of the mountain crest and downwind of the point where the cloud base intersects the terrain. The main argument that this increase can be attributed to AgI seeding is that it is confined to a shallow layer near the ground where the flow is turbulent. Yet during two flights when clouds were cumuliform and coherent updrafts to flight level were recorded by the radar, the seeding impact was evident in the flight-level updrafts （about 610 m above the mountain peak） as a significant increase in the ice crystal appears short-lived as it is not apparent just downwind of concentration in all size bins. The seeding effect the crest.

Improved Parameterization of Snow Albedo in WRF+Noah:Methodology Based on a Severe Snow Event on the Tibetan Plateau

Snowfall and the subsequent evolution of the snowpack have a large effect on the surface energy balance and water cycle of the Tibetan Plateau(TP).The effects of snow cover can be represented by the WRF coupled with a land surface scheme.The widely used Noah scheme is computationally efficient,but its poor representation of albedo needs considerable improvement.In this study,an improved albedo scheme is developed using a satellite-retrieved albedo that takes snow depth and age into account.Numerical experiments were then conducted to simulate a severe snow event in March 2017.The performance of the coupled WRF/Noah model,which implemented the improved albedo scheme,is compared against the model’s performance using the default Noah albedo scheme and against the coupled WRF/CLM that applied CLM albedo scheme.When the improved albedo scheme is implemented,the albedo overestimation in the southeastern TP is reduced,reducing the RMSE of the air temperature by 0.7°C.The improved albedo scheme also attains the highest correlation between the satellite-derived and the model-estimated albedo,which provides for a realistic representation of both the snow water equivalent(SWE)spatial distribution in the heavy snowbelt(SWE>6 mm)and the maximum SWE in the eastern TP.The underestimated albedo in the coupled WRF/CLM leads to underestimating the regional maximum SWE and a consequent failure to estimate SWE in the heavy snowbelt accurately.Our study demonstrates the feasibility of improving the Noah albedo scheme and provides a theoretical reference for researchers aiming to improve albedo schemes further.

A Study on a Snowband Associated with a Coastal Front and Cold-Air Damming Event of 3-4 February 1998 along the Eastern Coast of the Korean Peninsula

A 24-h simulation with the Advanced Regional Prediction System （ARPS） nonhydrostatic model is performed for the heavy snowfall event of 3-4 February 1998 along the eastern coast of Korean Peninsula; the results are used to understand the snowfall process, including why the precipitation maxima formed along the Yeongdong coastal region rather than over the mountain slope and ridge top during. The numerical simulation with a 4-kin horizontal grid spacing and 43 levels reproduces very well the narrow snowband located off the eastern Korean coast, away from, instead of over, the Yeongdong coastal mountain range. The general evolution of the snowband agrees quite well with radar observations, while the water-equivalent precipitation amount agrees reasonably well with radar precipitation estimate. The simulation results clearly show that the snow band developed due to the lifting by a coastal front that developed because of the damming of cold air against the eastern slope of the coastal mountain range. The damming was enhanced by the advection of cold air by a tow-level mountain-parallel jet from the north, formed due to geostrophic adjustment as the on-shore upslope air was decelerated by the mountain blocking. As the onshore flow weakened later due to synoptic-scale flow pattern change, the cold front propagated off shore and the precipitation dissipated.

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.

Five different types of lowered snow line in alpine valleys

The snow line for the same precipitation event in alpine valleys can vary greatly from valley to valley, even when the valleys are close together. Often this is not due to a difference in air mass, but to a different interaction of topography and topographyrelated meteorological conditions. By knowing the causes of a lowered snow line, we can better understand the differences in snow cover in alpine valleys at the same elevation over short distances or the differences in snow cover between alpine valleys and areas outside the valleys. As different types of lowered snow line respond differently to climate change, we can also understand future changes in snow conditions in alpine valleys. To better understand the process, we observed the temperature conditions during winter precipitation events on the territory of Eastern Julian Alps(Slovenia) over a period of two years, focusing on the height of the zero isotherm. Depending on atmospheric conditions, especially changes in the temperature profile and precipitation intensity during precipitation events, five causes of lowered snow line have been identified. These types can occur individually, but during multi-day snowfall events they occur frequently or in combination.

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.

THE DESIGN AND CORRECTION OF A QUANTITATIVE METHOD OF SNOW ESTIMATE BY RADAR

An optimization method is based to design a snowfall estimate method by radar for operational snow warning, and error estimation is analyzed through a case of heavy snow on March 4, 2007. Three modified schemes are developed for errors caused by temperature changes, snowflake terminal velocity, the distance from the radar and calculation methods. Due to the improvements, the correlation coefficient between the estimated snowfall and the observation is 0.66(exceeding the 99% confidence level), the average relative error is reduced to 48.74%, and the method is able to estimate weak snowfall of 0.3 mm/h and heavy snowfall above 5 mm/h. The correlation coefficient is0.82 between the estimated snowfall from the stations 50 to 100 km from the radar and the observation. The improved effect is weak when the influence of the snowflake terminal velocity is considered in those three improvement programs, which may be related to the uniform echo. The radar estimate of snow, which is classified by the distance between the sample and the radar, has the most obvious effect: it can not only increase the degree of similarity, but also reduce the overestimate and the undervaluation of the error caused by the distance between the sample and the radar.The improved algorithm further improves the accuracy of the estimate. The average relative errors are 31% and 27% for the heavy snowfall of 1.6 to 2.5 mm/h and above 2.6 mm/h, respectively, but the radar overestimates the snowfall under1.5 mm/h and underestimates the snowfall above 2.6 mm/h. Radar echo may not be sensitive to the intensity of snowfall, and the consistency shown by the error can be exploited to revise and improve the estimation accuracy of snow forecast in the operational work.

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.