Changes in Spring Snow Cover over the Eastern and Western Tibetan Plateau and Their Associated Mechanism

The spring snow cover(SC)over the western Tibetan Plateau(TP)(TPSC)(W_TPSC)and eastern TPSC(E_TPSC)have displayed remarkable decreasing and increasing trends,respectively,during 1985–2020.The current work investigates the possible mechanisms accounting for these distinct TPSC changes.Our results indicate that the decrease in W_TPSC is primarily attributed to rising temperatures,while the increase in E_TPSC is closely linked to enhanced precipitation.Local circulation analysis shows that the essential system responsible for the TPSC changes is a significant anticyclonic system centered over the northwestern TP.The anomalous descending motion and adiabatic heating linked to this anticyclone leads to warmer temperatures and consequent snowmelt over the western TP.Conversely,anomalous easterly winds along the southern flank of this anticyclone serve to transport additional moisture from the North Pacific,leading to an increase in snowfall over the eastern TP.Further analysis reveals that the anomalous anticyclone is associated with an atmospheric wave pattern that originates from upstream regions.Springtime warming of the subtropical North Atlantic(NA)sea surface temperature(SST)induces an atmospheric pattern resembling a wave train that travels eastward across the Eurasian continent before reaching the TP.Furthermore,the decline in winter sea ice(SIC)over the Barents Sea exerts a persistent warming influence on the atmosphere,inducing an anomalous atmospheric circulation that propagates southeastward and strengthens the northwest TP anticyclone in spring.Additionally,an enhancement of subtropical stationary waves has resulted in significant increases in easterly moisture fluxes over the coastal areas of East Asia,which further promotes more snowfall over eastern TP.

Changes in snow cover extent in the Central Taurus Mountains from 1981 to 2021 in relation to temperature, precipitation, and atmospheric teleconnections

The snow cover over the Taurus Mountains affects water supply, agriculture, and hydropower generation in the region. In this study, we analyzed the monthly Snow Cover Extent(SCE) from November to April in the Central Taurus Mountains(Bolkar, Aladaglar, Tahtali and Binboga Mountains) from 1981 to 2021. Linear trends of snow cover season(November to April) over the last 41 years showed decreases in SCE primarily at lower elevations. The downward trend in SCE was found to be more pronounced and statistically significant for only November and March. SCE in the Central Taurus Mountains has declined about-6.3% per decade for 2500-3000 m in November and about-6.0% per decade for 1000-1500 m and 3000+ m in March over the last 41 years. The loss of SCE has become evident since the 2000s, and the lowest negative anomalies in SCE have been observed in 2014, 2001, and 2007 in the last 41 years, which are consistent with an increase in air temperature and decreased precipitation. SCE was correlated with both mean temperature and precipitation, with temperature having a greater relative importance at all elevated gradients. Results showed that there is a strong linear relationship between SCE and the mean air temperature(r =-0.80) and precipitation(r = 0.44) for all elevated gradients during the snow season. The Arctic Oscillation(AO), the North Atlantic Oscillation(NAO), and the Mediterranean Oscillation(MO) winter indices were used to explain the year-to-year variability in SCE over the Central Taurus Mountains. The results showed that the inter-annual variability observed in the winter SCE on the Central Taurus Mountains was positively correlated with the phases of the winter AO, NAO and MO, especially below 2000 m elevation.

Impact of the Shrinkage of Arctic Sea Ice on Eurasian Snow Cover Changes in 1979-2021

Recent research has shown that snow cover induces extreme wintertime cooling and has detrimental impacts.Although the dramatic loss of Arctic sea ice certainly has contributed to a more extreme climate,the mechanism connecting sea-ice loss to extensive snow cover is still up for debate.In this study,a significant relationship between sea ice concentration(SIC)in the Barents-Kara(B-K)seas in November and snow cover extent over Eurasia in winter(November-January)has been found based in observational datasets and through numerical experiments.The reduction in B-K sea ice gives rise to a negative phase of Arctic Oscillation(AO),a deepened East Asia trough,and a shallow trough over Europe.These circulation anomalies lead to colder-than-normal Eurasian mid-latitude temperatures,providing favorable conditions for snowfall.In addition,two prominent cyclonic anomalies near Europe and Lake Baikal affect moisture transport and its divergence,which results in increased precipitation due to moisture advection and wind convergence.Furthermore,anomalous E-P flux shows that amplified upward propagating waves associated with the low SIC could contribute to the weakening of the polar vortex and southward breakouts of cold air.This work may be helpful for further understanding and predicting the snowfall conditions in the middle latitudes.

Seasonal snow cover patterns explain alpine treeline elevation better than temperature at regional scale

Unprecedented modern rates of warming are expected to advance alpine treelines to higher elevations,but global evidence suggests that current treeline dynamics are influenced by a variety of factors.Seasonal snow cover has an essential impact on tree recruitment and growth in alpine regions,which may in turn influence current treeline elevation;however,little research has been conducted on its role in regional treeline formation.Based on 11,804treeline locations in the eastern Himalayas,we extracted elevation,climate,and topographic data for treeline and snowline.Specifically,we used linear and structural equation modelling to assess the relationship between these environmental factors and treeline elevation,and the climate-snow-treeline interaction mechanism.The results showed that the treeline elevation increased with summer temperature and permanent or seasonal snowline elevation,but decreased with snow cover days and spring temperature at the treeline positions(P<0.001).Importantly,spring snowline elevation(33.4%)and seasonal snow cover days(21.1%)contributed the most to treeline elevation,outperforming the permanent snowline,temperature,precipitation,and light.Our results support the assertion that the temperature-moisture interaction affects treeline elevation in the eastern Himalayas,but we also found that the effects were strongly mediated by seasonal snow cover patterns.The increasing tendency of snow cover governed by climate humidification observed in the eastern Himalayas,is likely to limit future treeline advancement and may even cause treeline decline due to the mortality of the remaining old trees.Together,our findings highlight the role of seasonal snow cover patterns in determining treeline elevation in the eastern Himalayas,which should be considered when assessing the potential for treeline ascent in snow-mediated alpine systems elsewhere.

A decline in snow cover area of Passu and Ghulkin valleys between 1995 and 2022

The global cryosphere is experiencing accelerated melting due to climate change.Currently,the Karakoram anomaly is under discussion with a debate about the possibility that the anomaly may have recently ended.This study aims to evaluate the up-to-date changes in snow cover in the western Karakoram region.We observed the snow cover changes in Passu and Ghulkin valleys in the Hunza River basin(HRB)of the Karakoram through multitemporal Landsat satellite data between 1995 and 2022.We found a significant reduction in snow cover in these valleys,with an average reduction rate of 0.42 km~2/yr,resulting in a total reduction of~11.46 km~2 between 1995 and 2022.This reduction in snow cover is consistent with the mass loss of glaciers in the Karakoram region in recent years.The decline in snow cover in these valleys is also consistent with the meteorological data.The temperature in summer(June)has significantly increased whereas the precipitation in the accumulation season(March)has decreased.These rapid changes suggest that it is crucially important to monitor the snow cover on a regular basis to support downstream management of snowmelt runoff.In addition,there is a need of planning for mitigation and adaptation strategies for snow-related hazards.

Influence of Qinghai-Xizang Plateau snow cover on interannual variability of Western North Pacific tropical cyclone tracks

Track density function(TDF)was computed for all Western North Pacific tropical cyclones(WNP TCs)tracks from 1950 to 2018,and the TDFs were further investigated using principal component analysis(PCA)to analyze their inter-annual spatial and temporal variability.Then,the relationships between each empirical orthogonal function(EOF)mode and the typhoon count,typhoon landfall count,track pattern,and the Qinghai-Xizang Plateau snow cover(QXPSC)were examined,and the possible physical mechanisms implied by the statistical relationship were explored.The results show the QXPSC significantly affected the surface-atmosphere heat exchange through snow cover(SC)level,then changed the East Asian summer monsoon regional circulation pattern,influenced the subtropical high-pressure system strength and location,and ultimately affected the WNP TCs track patterns and thus changed their landfall locations.

Temporal and Spatial Variation Characteristics of Snow Cover Area in the Pamirs from 2010 to 2020

Scientific and comprehensive monitoring of snow cover changes in the Pamirs is of great significance to the prevention of snow disasters around the Pamirs and the full utilization of water resources. Utilize the 2010-2020 snow cover product MOD10A2, Synthesis by maximum, The temporal and spatial variation characteristics of snow cover area in the Pamirs in the past 11 years have been obtained. Research indicates: In terms of interannual changes, the snow cover area of the Pamir Plateau from 2010 to 2020 generally showed a slight decrease trend. The average snow cover area in 2012 was the largest, reaching 54.167% of the total area. In 2014, the average snow cover area was the smallest, accounting for only 44.863% of the total area. In terms of annual changes, there are obvious changes with the change of seasons. The largest snow area is in March, and the smallest snow area is in August. In the past 11 years, the average snow cover area in spring and summer showed a slow decreasing trend, and there was almost no change in autumn and winter. In terms of space, the snow cover area of the Pamirs is significantly affected by altitude, and the high snow cover areas are mainly distributed in the Karakoram Mountains and other areas with an altitude greater than 5000 meters.

Spatiotemporal variation in snow cover and its effects on grassland phenology on the Mongolian Plateau

Snow cover is an important water source for vegetation growth in arid and semi-arid areas,and grassland phenology provides valuable information on the response of terrestrial ecosystems to climate change.The Mongolian Plateau features both abundant snow cover resources and typical grassland ecosystems.In recent years,with the intensification of global climate change,the snow cover on the Mongolian Plateau has changed correspondingly,with resulting effects on vegetation growth.In this study,using MOD10A1 snow cover data and MOD13A1 Normalized Difference Vegetation Index(NDVI)data combined with remote sensing(RS)and geographic information system(GIS)techniques,we analyzed the spatiotemporal changes in snow cover and grassland phenology on the Mongolian Plateau from 2001 to 2018.The correlation analysis and grey relation analysis were used to determine the influence of snow cover parameters(snow cover fraction(SCF),snow cover duration(SCD),snow cover onset date(SCOD),and snow cover end date(SCED))on different types of grassland vegetation.The results showed wide snow cover areas,an early start time,a late end time,and a long duration of snow cover over the northern Mongolian Plateau.Additionally,a late start,an early end,and a short duration were observed for grassland phenology,but the southern area showed the opposite trend.The SCF decreased at an annual rate of 0.33%.The SCD was shortened at an annual rate of 0.57 d.The SCOD and SCED in more than half of the study area advanced at annual rates of 5.33 and 5.74 DOY(day of year),respectively.For grassland phenology,the start of the growing season(SOS)advanced at an annual rate of 0.03 DOY,the end of the growing season(EOS)was delayed at an annual rate of 0.14 DOY,and the length of the growing season(LOS)was prolonged at an annual rate of 0.17 d.The SCF,SCD,and SCED in the snow season were significantly positively correlated with the SOS and negatively correlated with the EOS and LOS.The SCOD was significantly negatively correlated with the SOS and positively correlated with the EOS and LOS.The SCD and SCF can directly affect the SOS of grassland vegetation,while the EOS and LOS were obviously influenced by the SCOD and SCED.This study provides a scientific basis for exploring the response trends of alpine vegetation to global climate change.

Spatial distributions and interannual variations of snow cover over China in the last 40 years

By using the observational snow data of more than 700 weather stations,the interannual temporal and spatial characteristics of seasonal snow cover in China were analyzed.The results show that northern Xinjiang,northeastern China–Inner Mongolia,and the southwestern and southern portions of Tibetan Plateau are three regions in China with high seasonal snow cover and also an interannual anomaly of snow cover.According to the trend of both the snow depth and snow cover days,there are three changing patterns for the seasonal snow cover:The first type is that both snow depth and snow cover days simultaneously increase or decrease;this includes northern Xinjiang,middle and eastern Inner Mongolia,and so on.The second is that snow depth increases but snow cover days decrease;this type mainly locates in the eastern parts of the northeastern plain of China and the upper reaches of the Yangtze River.The last type is that snow depth decreases but snow cover days increase at the same time such as that in middle parts of Tibetan Plateau.Snow cover in China appears to have been having a slow increasing trend during the last 40 years.On the decadal scale,snow depth and snow cover days slightly increased in the 1960s and then decreased in the 1970s;they again turn to increasing in the 1980s and persist into 1990s.

Classification of snow cover days in western China and comparison with satellite remote sensing data

The daily snow cover data from 232 meteorological stations to the west of 105°E in China for the period 1951-2004 were used to classify the snow cover and analyze decadal variations of snow cover types in western China, and comparison was made between the observational data and those retrieved from passive microwave remote sensing data （SMMR and SSM/I） in 1980-2004. The results show that stable snow-covered areas included northern Xinjiang, the Tianshan Mountains, and the eastern Tibetan Plateau with more than 60 snow cover days; no snow cover was found in the center of the southern Xinjiang Basin, the Sichuan Basin, and southern Yunnan. In addition to the above-mentioned, there were unstable snow-covered areas in western China. Furthermore, the snow cover types in northern Xinjiang, the Tianshan Mountains, the Hexi Corridor, and the vast areas from Chengdu to Kunming were unchanged. In the 1980s, the south-north dividing line between the major snow-covered area and snow-free area advanced to its most southern position. The snow cover days calculated from satellite remote sensing were generally longer than those from observational data in western China, mainly in the higher-altitude mountains, the Hexi Corridor, and the western Sichuan Plateau.

Monitoring and analysis of snow cover change in an alpine mountainous area in the Tianshan Mountains,China

Estimating the snow cover change in alpine mountainous areas(in which meteorological stations are typically lacking)is crucial for managing local water resources and constitutes the first step in evaluating the contribution of snowmelt to runoff and the water cycle.In this paper,taking the Jingou River Basin on the northern slope of the Tianshan Mountains,China as an example,we combined a new moderate-resolution imaging spectroradiometer(MODIS)snow cover extent product over China spanning from 2000 to 2020 with digital elevation model(DEM)data to study the change in snow cover and the hydrological response of runoff to snow cover change in the Jingou River Basin under the background of climate change through trend analysis,sensitivity analysis and other methods.The results indicate that from 2000 to 2020,the annual average temperature and annual precipitation in the study area increased and snow cover fraction(SCF)showed obvious signs of periodicity.Furthermore,there were significant regional differences in the spatial distribution of snow cover days(SCDs),which were numerous in the south of the basin and sparse in the central of the basin.Factors affecting the change in snow cover mainly included temperature,precipitation,elevation,slope and aspect.Compared to precipitation,temperature had a greater impact on SCF.The annual variation in SCF was limited above the elevation of 4200 m,but it fluctuated greatly below the elevation of 4200 m.These results can be used to establish prediction models of snowmelt and runoff for alpine mountainous areas with limited hydrological data,which can provide a scientific basis for the management and protection of water resources in alpine mountainous areas.

Eurasian Snow Cover Variability and Its Association with Summer Rainfall in China

This study investigates the statistical linkage between summer rainfall in China and the preceding spring Eurasian snow water equivalent （SWE）, using the datasets of summer rainfall observations from 513 stations, satellite-observed snow water equivalent, and atmospheric circulation variables in the NCEP/NCAR reanalysis during the period from 1979 to 2004. The first two coupled modes are identified by using the singular value decomposition （SVD） method. The leading SVD mode of the spring SWE variability shows a coherent negative anomaly in most of Eurasia with the opposite anomaly in some small areas of the Tibetan Plateau and East Asia. The mode displays strong interannual variability, superposed on an interdecadal variation that occurred in the late 1980s, with persistent negative phases in 1979-1987 and frequent positive phases afterwards. When the leading mode is in its positive phase, it corresponds to less SWE in spring throughout most of Eurasia. Meanwhile, excessive SWE in some small areas of the Tibetan Plateau and East Asia, summer rainfall in South and Southeast China tends to be increased, whereas it would be decreased in the up-reaches of the Yellow River. In recent two decades, the decreased spring SWE in Eurasia may be one of reasons for severe droughts in North and Northeast China and much more significant rainfall events in South and Southeast China. The second SVD mode of the spring SWE variability shows opposite spatial variations in western and eastern Eurasia, while most of the Tibetan Plateau and East Asia are in phase. This mode significantly correlates with the succeeding summer rainfall in North and Northeast China, that is, less spring SWE in western Eurasia and excessive SWE in eastern Eurasia and the Tibetan Plateau tend to be associated with decreased summer rainfall in North and Northeast China.

Interannual and Decadal Variations of Snow Cover overQinghai-Xizang Plateau and Their Relationships to Summer Monsoon Rainfall in China

Interannual and decadal variations of winter snow cover over the Qinghai-Xizang Plateau (QXP) are analyzed by using monthly mean snow depth data set of 60 stations over QXP for the period of 1958 through 1992. It is found that the winter snow cover over QXP bears a pronounced quasi-biennial oscillation, and it underwent an obvious decadal transition from a poor snow cover period to a rich snow cover period in the late 1970’s during the last 40 years. It is shown that the summer rainfall in the eastern China is closely associated with the winter snow cov-er over QXP not only in the interannual variation but also in the decadal variation. A clear relationship ex-ists in the quasi-biennial oscillation between the summer rainfall in the northern part of North China and the southern China and the winter snow cover over QXP. Furthermore, the summer rainfall in the four cli-mate divisions of Qinling-Daba Mountains, the Yangtze-Huaihe River Plain, the upper and lower reaches of the Yangtze River showed a remarkable transition from drought period to rainy period in the end of 1970’s, in good correspondence with the decadal transition of the winter snow cover over QXP. Key words Snow cover over Qinghai-Xizang Plateau - Summer monsoon rainfall in China - Interannual and decadal variations This study was supported by the National Key Programme for Developing Basic Sciences (G 1998040900 Part I).

The Summer Snow Cover Anomaly over the Tibetan Plateau and Its Association with Simultaneous Precipitation over the Mei-yu–Baiu region

The summer snow anomalies over the Tibetan Plateau （TP） and their effects on climate variability are often overlooked,possibly due to the fact that some datasets cannot properly capture summer snow cover over high terrain.The satellite-derived Equal-Area Scalable Earth grid （EASE-grid） dataset shows that snow still exists in summer in the western part and along the southem flank of the TP.Analysis demonstrates that the summer snow cover area proportion （SCAP） over the TP has a significant positive correlation with simultaneous precipitation over the mei-yu-baiu （MB） region on the interannual time scale.The close relationship between the summer SCAP and summer precipitation over the MB region could not be simply considered as a simultaneous response to the Silk Road pattern and the SST anomalies in the tropical Indian Ocean and tropical central-eastern Pacific.The SCAP anomaly has an independent effect and may directly modulate the land surface heating and,consequently,vertical motion over the western TP,and concurrently induce anomalous vertical motion over the North Indian Ocean via a meridional vertical circulation.Through a zonal vertical circulation over the tropics and a Kelvin wave-type response,anomalous vertical motion over the North Indian Ocean may result in an anomalous high over the western North Pacific and modulate the convective activity in the western Pacific warm pool,which stimulates the East Asia-Pacific （EAP） pattern and eventually affects summer precipitation over the MB region.

An Empirical Formula to Compute Snow Cover Fraction in GCMs

There exists great uncertainty in parameterizing snow cover fraction in most general circulation models (GCMs) using various empirical formulae, which has great influence on the performance of GCMs. This work reviews the commonly used relationships between region-averaged snow depth (or snow water equivalent) and snow cover extent (or fraction) and suggests a new empirical formula to compute snow cover fraction, which only depends on the domain-averaged snow depth, for GCMs with different horizontal resolution. The new empirical formula is deduced based on the 10-yr (1978-1987) 0.5°× 0.5° weekly snow depth data of the scanning multichannel microwave radiometer (SMMR) driven from the Nimbus-7 Satellite. Its validation to estimate snow cover for various GCM resolutions was tested using the climatology of NOAA satellite-observed snow cover.

A Modeling Study of the Effects of Anomalous Snow Cover over the Tibetan Plateau upon the South Asian Summer Monsoon

The e?ect of anomalous snow cover over the Tibetan Plateau upon the South Asian summer monsoon is investigated by numerical simulations using the NCAR regional climate model (RegCM2) into which gravity wave drag has been introduced. The simulations adopt relatively realistic snow mass forcings based on Scanning Multi-channel Microwave Radiometer (SMMR) pentad snow depth data. The physical mechanism and spatial structure of the sensitivity of the South Asian early summer monsoon to snow cover anomaly over the Tibetan Plateau are revealed. The main results are summarized as follows. The heavier than normal snow cover over the Plateau can obviously reduce the shortwave radiation absorbed by surface through the albedo e?ect, which is compensated by weaker upward sensible heat ?ux associated with colder surface temperature, whereas the e?ects of snow melting and evaporation are relatively smaller. The anomalies of surface heat ?uxes can last until June and become unobvious in July. The decrease of the Plateau surface temperature caused by heavier snow cover reaches its maximum value from late April to early May. The atmospheric cooling in the mid-upper troposphere over the Plateau and its surrounding areas is most obvious in May and can keep a fairly strong intensity in June. In contrast, there is warming to the south of the Plateau in the mid-lower troposphere from April to June with a maximum value in May. The heavier snow cover over the Plateau can reduce the intensity of the South Asian summer monsoon and rainfall to some extent, but this in?uence is only obvious in early summer and almost disappears in later stages.

The Effects of Anomalous Snow Cover of the Tibetan Plateau on the Surface Heating

On the basis of snow data and AWS (Automatic Weather Station) data obtained from the Tibetan Plateau in recent years (1993 to 1999), the features of sensible heat, latent heat and net long-wave radiations are estimated, and their variations in more-snow year (1997/ 1998) and less-snow year (1996/ 1997) are analyzed comparatively. The relationships between snow cover of the Tibetan Plateau and plateau’s surface heating to the atmospheric heating are also discussed. The difference between more-snow and less-snow year in spring is remarkably larger than that in winter. Therefore, the effect of anomalous snow cover of the Tibetan Plateau in winter on the plateau heating appears more clearly in the following spring of anomalous snow cover. Key words Tibetan Plateau - Snow cover - Effects - Surface heat fluxes This research was supported by the National Key Programme for Developing Basic Sciences G1998040900 (I), National Natural Science Foundation of China (40075018) and Sichuan Youth Science and Technology Fund.

Persistence of Snow Cover Anomalies over the Tibetan Plateau and the Implications for Forecasting Summer Precipitation over the Meiyu-Baiu Region

The present reported study investigated the persistence of snow anomalies over the Tibetan Plateau(TP) from the preceding seasons to summer and the relationship between the previous snow cover anomaly and summer precipitation over East Asia. The results showed that, relative to other snow indices, such as the station observational snow depth(SOSD) index and the snow water equivalent(SWE) index, the snow cover area proportion(SCAP) index calculated from the SWE and the percentage of visible snow of the Equal-Area Scalable Earth Grids(EASE-grids) dataset has a higher persistence in interannual anomalies, particularly from May to summer. As such, the May SCAP index is significantly related to summer precipitation over the Meiyu-Baiu region. The persistence of the SCAP index can partly explain the season-delayed effect of snow cover over the TP on summer rainfall over the Meiyu-Baiu region besides the contribution of the soil moisture bridge. The preceding SST anomaly in the tropical Indian Ocean and ENSO can persist through the summer and affect the summer precipitation over the Meiyu-Baiu region. However, the May SCAP index is mostly independent of the simultaneous SSTs in the tropical Indian Ocean and the preceding ENSO and may affect the summer precipitation over the Meiyu-Baiu region independent of the effects of the SST anomalies. Therefore, the May SCAP over the TP could be regarded as an important supplementary factor in the forecasting of summer precipitation over the Meiyu-Baiu region.

A new MODIS daily cloud free snow cover mapping algorithm on the Tibetan Plateau

Because of similar reflective characteristics of snow and cloud, the weather status seriously affects snow monitoring using optical remote sensing data. Cloud amount analysis during 2010 to 2011 snow seasons shows that cloud cover is the major limitation for snow cover monitoring using MOD10A1 and MYD10A1. By use of MODIS daily snow cover products and AMSR-E snow wa- ter equivalent products （SWE）, several cloud elimination methods were integrated to produce a new daily cloud flee snow cover product, and information of snow depth from 85 climate stations in Tibetan Plateau area （TP） were used to validate the accuracy of the new composite snow cover product. The results indicate that snow classification accuracy of the new daily snow cover product reaches 91.7% when snow depth is over 3 cm. This suggests that the new daily snow cover mapping algorithm is suitable for monitoring snow cover dynamic changes in TP.

Evaluation of Snow Depth and Snow Cover Fraction Simulated by Two Versions of the Flexible Global Ocean–Atmosphere–Land System Model

Based on historical runs,one of the core experiments of the fifth phase of the Coupled Model Intercomparison Project （CMIP5）,the snow depth （SD） and snow cover fraction （SCF） simulated by two versions of the Flexible Global OceanAtmosphere-Land System （FGOALS） model,Grid-point Version 2 （g2） and Spectral Version 2 （s2）,were validated against observational data.The results revealed that the spatial pattern of SD and SCF over the Northern Hemisphere （NH） are simulated well by both models,except over the Tibetan Plateau,with the average spatial correlation coefficient over all months being around 0.7 and 0.8 for SD and SCF,respectively.Although the onset of snow accumulation is captured wellby the two models in terms of the annual cycle of SD and SCF,g2 overestimates SD/SCF over most mid-and high-latitude areas of the NH.Analysis showed that g2 produces lower temperatures than s2 because it considers the indirect effects of aerosols in its atmospheric component,which is the primary driver for the SD/SCF difference between the two models.In addition,both models simulate the significant decreasing trend of SCF well over （30°-70°N） in winter during the period 1971-94.However,as g2 has a weak response to an increase in the concentration of CO2 and lower climate sensitivity,it presents weaker interannual variation compared to s2.