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.

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.

Spatiotemporal Changes of Snow Depth in Western Jilin,China from 1987 to 2018

Seasonal snow cover is a key global climate and hydrological system component drawing considerable attention due to glob-al warming conditions.However,the spatiotemporal snow cover patterns are challenging in western Jilin,China due to natural condi-tions and sparse observation.Hence,this study investigated the spatiotemporal patterns of snow cover using fine-resolution passive mi-crowave(PMW)snow depth(SD)data from 1987 to 2018,and revealed the potential influence of climate factors on SD variations.The results indicated that the interannual range of SD was between 2.90 cm and 9.60 cm during the snowy winter seasons and the annual mean SD showed a slightly increasing trend(P>0.05)at a rate of 0.009 cm/yr.In snowmelt periods,the snow cover contributed to an increase in volumetric soil water,and the change in SD was significantly affected by air temperature.The correlation between SD and air temperature was negative,while the correlation between SD and precipitation was positive during December and March.In March,the correlation coefficient exceeded 0.5 in Zhenlai,Da’an,Qianan,and Qianguo counties.However,the SD and precipitation were neg-atively correlated over western Jilin in October,and several subregions presented a negative correlation between SD and precipitation in November and April.

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.

Black Carbon Size in Snow of Chinese Altai Mountain in Central Asia

Black carbon(BC)in snow plays an important role to accelerate snow melting.However,current studies mostly focused on BC concentrations,few on their size distributions in snow which affected BC’s effect on albedo changes.Here we presented refractory BC(rBC)concentrations and size distributions in snow collected from Chinese Altai Mountains in Central Asia from November 2016 to April 2017.The results revealed that the average rBC concentrations were 5.77 and2.82 ng g-1for the surface snow and sub-surface snow,which were relatively higher in the melting season(April)than that in winter(November-January).The mass median volume-equivalent diameter of rBC size in surface snow was approximately at 120-150 nm,which was typically smaller than that in the atmosphere(about 200 nm for urban atmosphere).However,there existed no specific mass median volume-equivalent diameter of BC size for sub-surface snow in winter.While during the melting season,the median mass size of rBC in sub-surface snow was similar to that in surface snow.Backward trajectories indicated that anthropogenic sourced BC dominated rBC in snow(70%-85%).This study will promote our understanding on BC size distributions in snow,and highlight the possible impact of BC size on climate effect.

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.

Distribution assessment of soil erosion with revised RUSLE model in Tianshan Mountains

aSoil degradation caused by soil erosion is one of the world's most critical environmental issues.Soil erosion in the Tianshan Mountains has caused various environmental problems in the surrounding areas.This study used remote sensing data to analyze the distribution of the factors influencing soil erosion,and the revised universal soil loss equation(RUSLE)to calculate the total amount and distribution characteristics of soil erosion in the Tianshan Mountains in 2019.Due to the large error of RUSLE in soil erosion estimation in mountainous areas,this study modified RUSLE equation based on the characteristics of snow cover in the Tianshan Mountains.The results show that the average soil erosion was 1690.3 t/(km^(2)·year),of which insignificant erosion,slight erosion and moderate erosion accounted for 42,8%,22.4%and 9.9%,respectively.Severe erosion and above accounted for 13.3%.The accuracy of the soil erosion modulus calculated by the RUSLE was only 61.9%,with an average error of 1631.9 t/(km^(2)·year).The average error of the double-coefficient correction method was 1259.1 t/(km^(2)·year),and the average error of the modified formula method was reduced by 40.3%compared with the RUSLE,reaching 973.7 t/(km^(2)·year),and its accuracy reached 76.2%.Very severe erosion and catastrophic erosion are distributed on mountain ridges with higher elevation and on the northern area with higher precipitation.Snow cover has a certain inhibitory effect on soil erosion,and snow cover in alpine mountains is a factor that cannot be ignored in soil erosion research.

Persistent Variations in the East Asian Trough from March to April and the Possible Mechanism

The East Asian trough(EAT)profoundly influences the East Asian spring climate.In this study,the relationship of the EATs among the three spring months is investigated.Correlation analysis shows that the variation in March EAT is closely related to that of April EAT.Extended empirical orthogonal function(EEOF)analysis also confirms the co-variation of the March and April EATs.The positive/negative EEOF1 features the persistent strengthened/weakened EAT from March to April.Further investigation indicates that the variations in EEOF1 are related to a dipole sea surface temperature(SST)pattern over the North Atlantic and the SST anomaly over the tropical Indian Ocean.The dipole SST pattern over the North Atlantic,with one center east of Newfoundland Island and another east of Bermuda,could trigger a Rossby wave train to influence the EAT in March−April.The SST anomaly over the tropical Indian Ocean can change the Walker circulation and influence the atmospheric circulation over the tropical western Pacific,subsequently impacting the southern part of the EAT in March−April.Besides the SST factors,the Northeast Asian snow cover could change the regional thermal conditions and lead to persistent EAT anomalies from March to April.These three impact factors are generally independent of each other,jointly explaining large variations in the EAT EEOF1.Moreover,the signals of the three factors could be traced back to February,consequently providing a potential prediction source for the EAT variation in March and April.

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.

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.

The Influence of Seasonal Snow on Soil Thermal and Water Dynamics under Different Vegetation Covers in a Permafrost Region

Seasonal snow is one of the most important influences on the development and distribution of permafrost and the hydrothermal regime in surface soil. Alpine meadow, which constitutes the main land type in permafrost regions of the Qinghai-Tibet Plateau, was selected to study the influence of seasonal snow on the temperature and moisture in active soil layers under different vegetation coverage. Monitoring sites for soil moisture and temperature were constructed to observe the hydrothermal processes in active soil layers under different vegetation cover with seasonal snow cover variation for three years from 2010 to 2012. Differences in soil temperature and moisture in areas of diverse vegetation coverage with varying levels of snow cover were analyzed using active soil layer water and temperature indices. The results indicated that snow cover greatly influenced the hydrothermal dynamics of the active soil layer in alpine meadows. In the snow manipulation experiment with a snow depth greater than 15 cm, the snow cover postponed both the freeze-fall and thawrise onset times of soil temperature and moisture in alpine LC(lower vegetation coverage) meadows and of soil moisture in alpine HC(higher vegetation coverage) meadows; however, the opposite response occurred for soil temperatures of alpine HC meadows,where the entire melting period was extended by advancing the thaw-rise and delaying the freeze-fall onset time of the soil temperature. Snow cover resulted in a decreased amplitude and rate of variation in soil temperature, for both alpine HC meadows and alpine LC meadows, whereas the distinct influence of snow cover on the amplitude and rate of soil moisture variation occurred at different soil layers with different vegetation coverages. Snow cover increased the soil moisture of alpine grasslands during thawing periods. The results confirmed that the annual hydrothermal dynamics of active layers in permafrost were subject to the synergistic actions of both snow cover and vegetation coverage.

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.

Implications of Climate Change on Streamflow of a Snow-Fed River System of the Northwest Himalaya

Air temperature and snow cover variability are sensitive indicators of climate change. This study was undertaken to forecast and quantify the potential streamflow response to climate change in the Jhelum River basin. The implications of air temperature trends （＋0.11℃decade） reported for the entire north-west Himalaya for past century and the regional warming （＋0.7℃/decade） trends of three observatories analyzed between last two decades were used for future projection of snow cover depletion and stream flow. The streamflow was simulated and validated for the year 2007-2008 using snowmelt runoff model （SRM） based on in-situ temperature and precipitation with remotely sensed snow cover area. The simulation was repeated using higher values of temperature and modified snow cover depletion curves according to the assumed future climate. Early snow cover depletion was observed in the basin in response to warmer climate. The results show that with the increase in air temperature, streamfiow pattern of Jhelum will be severely affected. Significant redistribution of streamflow was observed in both the scenarios. Higher discharge was observed during spring-summer months due to early snowmelt contribution with water deficit during monsoon months. Discharge increased by 5%-40% during the months of March to May in 2030 and 2050. The magnitude of impact of air temperature is higher in the scenario-2 based on regional warming. The inferences pertaining to change in future streamflow pattern can facilitate long term decisions and planning concerning hydro-power potential, waterresource management and flood hazard mapping in the region.