The snowpack is changing across the globe,as the climate warms and changes.We used daily snow water equivalent(SWE)niveograph(time series of SWE)data from 458 snow telemetry(SNOTEL)stations for the period 1982 through...The snowpack is changing across the globe,as the climate warms and changes.We used daily snow water equivalent(SWE)niveograph(time series of SWE)data from 458 snow telemetry(SNOTEL)stations for the period 1982 through 2012.Nineteen indices based on amount,timing,time length,and rates were used to describe the annual temporal evolution in SWE accumulation and ablation.The trends in these annual indices were computed over the time period for each station using the Theil-Sen slope.These trends were then clustered into four groups to determine the spatial pattern of SWE trends.Temperature and precipitation data were extracted from the PRISM data set,due to the shorter time period of temperature measurement at the SNOTEL stations.Results show that SNOTEL stations can be clustered in four clusters according to the observed trends in snow indices.Cluster 1 stations are mostly located in the Eastern-and South-eastern most parts of the study area and they exhibit a generalized decrease in the indices related with peak SWE and snow accumulation.Those stations recorded a negative trend in precipitation and an increase in temperature.Cluster 4 that is mostly restricted to the North and North-west of the study area shows an almost opposite pattern to cluster 1,due to months with positive trends and a more moderate increase of temperature.Stations grouped in clusters 2 and 3 appear mixed with clusters 1 and 4,in general they show very little trends in the snow indices.展开更多
基金Funding for this work was provided by the NASA Terrestrial Hydrology Program Project NNX11AQ66G“Improved Characterization of Snow Depth in Complex Terrain Using Satellite Lidar Altimetry”(Principal Investigator Dr.Michael Jasinski from NASA-Goddard Space Flight Center)
文摘The snowpack is changing across the globe,as the climate warms and changes.We used daily snow water equivalent(SWE)niveograph(time series of SWE)data from 458 snow telemetry(SNOTEL)stations for the period 1982 through 2012.Nineteen indices based on amount,timing,time length,and rates were used to describe the annual temporal evolution in SWE accumulation and ablation.The trends in these annual indices were computed over the time period for each station using the Theil-Sen slope.These trends were then clustered into four groups to determine the spatial pattern of SWE trends.Temperature and precipitation data were extracted from the PRISM data set,due to the shorter time period of temperature measurement at the SNOTEL stations.Results show that SNOTEL stations can be clustered in four clusters according to the observed trends in snow indices.Cluster 1 stations are mostly located in the Eastern-and South-eastern most parts of the study area and they exhibit a generalized decrease in the indices related with peak SWE and snow accumulation.Those stations recorded a negative trend in precipitation and an increase in temperature.Cluster 4 that is mostly restricted to the North and North-west of the study area shows an almost opposite pattern to cluster 1,due to months with positive trends and a more moderate increase of temperature.Stations grouped in clusters 2 and 3 appear mixed with clusters 1 and 4,in general they show very little trends in the snow indices.
