Spatiotemporal variation of snow cover and its relationship with temperature and precipitation in the Yarlung Tsangpo-Brahmaputra River Basin

The snow cover over the Qinghai-Tibet Plateau(QTP)and its surrounding areas is very sensitive to climate changes.Due to the complexity of geographical environment in this large region,the response of snow cover to climate change should exhibit spatiotemporal differences.In this study,the spatiotemporal variations of snow cover from 2002-2015 in the Yarlung Tsangpo-Brahmaputra River Basin(YBRB)were analyzed using an optimized fractional snow cover(FSC)product derived from Moderate Resolution Imaging Spectroradiometer(MODIS).Additionally,the effects of temperature and precipitation on the variability of snow cover were also investigated.The results showed that:(1)The snow cover exhibited large spatial and temporal heterogeneity in the YBRB.High FSC was observed in the northeast of the basin and the south slope of Himalaya,while the lowest was concentrated in the broad valley of the upstream of YBRB.The FSC value reached its highest in winter and dropped to its lowest in summer,but the monthly change processes were different between upstream and downstream regions.(2)A slightly increasing tendency(3.76%/10 a)of snow cover was observed on basin-wide,but the changes varied through time and space.The FSC increased significantly in the source and midstream regions during winter to spring(10.5%-18.0%/10 a),while it changed slightly in summer over all parts of the basin(-0.4%-4.3%/10 a).(3)The study area generally became warm and wet,and the change trend of temperature was more significant than that of precipitation.Snow cover changes were weakly correlated with temperature in winter and precipitation in summer.But in spring and autumn,both precipitation and temperature were significantly related to snow cover change in most regions of the basin.(4)The dominant factor driving the changes of snow cover varied in seasons.The area dominated by temperature was slightly larger than that dominated by precipitation in spring,except that precipitation significantly dominated the snow cover changes in the source region;In summer and autumn,temperature contributed more to the snow cover change in most areas of the basin;However,in winter,precipitation played a leading role in the variations of snow cover.These findings help to understand the different performance of the snow cover in the QTP and its surrounding areas under future climate change.

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.

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.

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.

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.

Optical remote sensing of snow fraction——status and future prospects

Fractional snow cover （FSC） is that fraction of the surface covered with snow in a remotely sensed image pixel. This subpixel snow fraction is useful for atmospheric correction and to retrieve various satellite products characterizing the land surface, including albedo, temperature, soil moisture, heat fluxes, and vegetation parameters.