Development of Global Snow Cover—Trends from 23 Years of Global SnowPack

• Published in: Earth
• Main Authors: Sebastian Roessler, Andreas Jürgen Dietz
• Format: Text
• Language: English
• Published: Multidisciplinary Digital Publishing Institute 2022
• Subjects: snow cover; remote sensing; MODIS; Global SnowPack (GSP); trend analysis; Mann–Kendall (MK); Kendall; polar night
• Online Access: https://doi.org/10.3390/earth4010001

Globally, the seasonal snow cover is the areal largest, the most short-lived and the most variable part of the cryosphere. Remote sensing proved to be a reliable tool to investigate their short-term variations worldwide. The medium-resolution sensor MODIS sensor has been delivering daily snow products since the year 2000. Remaining data gaps due to cloud coverage or polar night are interpolated using the DLR’s Global SnowPack (GSP) processor which produces daily global cloud-free snow cover. With the conclusion of the hydrological year 2022 in the northern hemisphere, the snow cover dynamics of the last 23 hydrological years can now be examined. Trends in snow cover development over different time periods (months, seasons, snow seasons) were examined using the Mann–Kendall test and the Theil–Sen slope. This took place as both pixel based and being averaged over selected hydrological catchment areas. The 23-year time series proved to be sufficient to identify significant developments for large areas. Globally, an average decrease in snow cover duration of −0.44 days/year was recorded for the full hydrological year, even if slight increases in individual months such as November were also found. Likewise, a large proportion of significant trends could also be determined globally at the catchment area level for individual periods. Most drastic developments occurred in March, with an average decrease in snow cover duration by −0.16 days/year. In the catchment area of the river Neman, which drains into the Baltic Sea, there is even a decrease of −0.82 days/year.