| Snow cover plays an important role in the cryosphere and is one of the important surface coverings in the mid-latitude mountain area.The interannual fluctuation and the spatial and temporal evolution of the snowline altitude at the end of melting season are considered as sensitive indicators of climate change.High Mountain Asia is the region with the most abundant ice and snow reserves in addition to Antarctica and the Arctic,which has an important impact on the evolution of the climate system in China and even the entire Asia.Therefore,accurately extracting the snowline altitude at the end of melting season of High Mountain Asia,and studying its spatial and temporal differences and its influencing factors,is essential to provide key information for studying the changes of the ice and snow system and its response to climate change.In this study,High Mountain Asia was used as the research area,and the remote sensing extraction method of large-scale snowline altitude at the end o melting season is developed based on MODIS snow cover products.In this method,the cloud removal of the daily MODIS snow cover products was firstly carried out based on the developed cubic spline interpolation cloud-removel method,and snow covered days(SCD)of the 16 years are extracted using the cloud-removed MODIS snow cover products.In addition,the MODIS SCD threshold for estimating perennial snow cover is calibrated using the observed data of glacier annual mass balance and Landsat data at the end of melting season.Finally,the altitude value of the snowline at the end of melting season is determined by combining the perennial snow cover area and the terrain area-elevation curve.Through linear regression,trend analysis,variogram and other methods to reveal the spatial distribution,spatio-temporal variation characteristics and spatial heterogeneity of the snowline altitude at the end of melting season of the High Mountain Asia;quantitative analysis of the snowline altitude at different spatial scales by longitude,latitude and altitude;explore the relationship between snowline altitude and meteorological elements(temperature,precipitation)on a grid-by-grid,the results are as follows:(1)The remote sensing extraction method for the snowline altitude at the end of melting season of the High Mountain Asia are developed.Compared with the“true value”extracted from the Landsat image,the average correlation coefficient R=0.82;the snowline altitude at the end of melting season of the grid of 12 glaciers and the material balance of the glaciers have a significant negative correlation(average R=-0.66).(2)The spatial distribution of the snowline altitude at the end of melting season of the High Mountain Asia mainly shows two basic characteristics:a typical latitude zonal distribution,(the characteristics of the snowline altitude gradually decreasing with the latitude increases northward);it shows from gradually decreases the high altitude area to the surrounding low mountainous area.The snowline altitude in the western High Mountain Asia is relatively low and the contour lines are densely distributed.The height of the snowline altitude in the Himalayas and the Qinghai-Tibet Plateau(5941 m)is high and the contour lines are sparsely distributed.(3)The snowline altitude from 2001 to 2016 in the High Mountain Asia shows an obvious increasing trend.75.3%of the grids shows increa sing trend,while only 0.9%with a significant decrease.There are differences in the Interannual changes of snowline altitude in different regions,The Interannual variability in Hindu Kush and West Himalayas show a downward trend,with a decline rate of-2.43m yr-1,-0.16 m yr-1,and of the height of the snowline altitude remains basically unchanged in Karakorum Mountains(0.44 m yr-1);the spatial autocorrelation distance of the snowline altitude at the end of melting season of High Mountain Asia is 1 550km.(4)The relative contribution ratios of the influences of latitude,longitude and altitude on snowline altitude at the end of melting season in the High Mountain Asia are 60.5%,2.6%and36.9%,respectively,and the relative contribution ratios vary for different subregions.Mean air temperature is positively correlated with the snowline altitude(Average R=0.58),with a weak negative correlation with precipitation,summer temperature is the dominant climatic factor affecting the Interannual variation of the snowline altitude in the study area(69.26%of the total grid),Hissar Alay Mountain,Pamir and Hindu Kush is relatively affected by the annual precipitation. |