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.

中文翻译：

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从雪遥测数据来看，美国西部尼韦尔特征的趋势模式

随着气候变暖和变化，积雪在全球范围内变化。我们使用了1982年至2012年期间的458个雪遥测（SNOTEL）站的每日雪水当量（SWE）实况图（SWE的时间序列）数据。使用基于数量，时间，时间长度和费率的19个指数来描述SWE累积和消融的年度时间演变。这些年度指数的趋势是使用Theil-Sen斜率在每个时间段内计算出来的。然后将这些趋势分为四个组，以确定SWE趋势的空间格局。由于SNOTEL站的温度测量时间较短，因此从PRISM数据集中提取了温度和降水数据。结果表明，根据观测到的降雪指数趋势，SNOTEL站可以分为四个簇。第1类站点主要位于研究区域的东部和东南部，它们的峰值与SWE峰值和积雪有关。这些气象站的降水量呈负趋势，温度升高。群集4主要限于研究区域的北部和西北部，与群集1的模式几乎相反，这是由于月份呈正趋势，且温度升高较为温和。聚类2和3分组的站似乎与聚类1和4混合在一起，通常它们的降雪指数趋势很小。第1类站主要位于研究区域的东部和东南部，它们的峰值与SWE峰值和积雪有关，呈普遍下降趋势。这些台站的降水量呈负趋势，温度升高。群集4主要限于研究区域的西北部和西北部，与群集1的模式几乎相反，这是由于月份呈正趋势，且温度升高较为温和。聚类2和3分组的站似乎与聚类1和4混合在一起，通常它们的降雪指数趋势很小。第1类站主要位于研究区域的东部和东南部，它们的峰值与SWE峰值和积雪有关，呈普遍下降趋势。这些气象站的降水量呈负趋势，温度升高。群集4主要限于研究区域的北部和西北部，与群集1的模式几乎相反，这是由于月份呈正趋势，且温度升高较为温和。聚类2和3分组的站似乎与聚类1和4混合在一起，通常它们的降雪指数趋势很小。群集4主要限于研究区域的北部和西北部，与群集1的模式几乎相反，这是由于月份呈正趋势，且温度升高较为温和。聚类2和3分组的站似乎与聚类1和4混合在一起，通常它们的降雪指数趋势很小。群集4主要限于研究区域的北部和西北部，与群集1的模式几乎相反，这是由于月份呈正趋势，且温度升高较为温和。聚类2和3分组的站似乎与聚类1和4混合在一起，通常它们的降雪指数趋势很小。