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Snow cover affects the global surface energy balance and, with its high albedo, exerts a cooling effect on the Earth's climate. Decreases in snow cover alter the flow of solar energy from being reflected away from Earth to being absorbed, increasing the Earth's surface temperature. To gain a global understanding of snow cover change, in situ measurements are too few and far between, so remotely sensed data are needed. This research used the medium-resolution sensor MODIS on the Terra satellite, which has been observing global snow cover almost daily since the year 2000. Here, the MOD10C2 eight-day maximum value composite time series data from February 2000 to March 2023 were analyzed to detect global and regional trends in snow cover extent for the first 23 years of the 21st century. Trends in snow cover change during different time periods (seasons and snow-year) were examined using the Mann—Kendall test and the univariate differencing analysis. Both methods produced similar results. Globally, snow cover declined two to ten times as much as it increased, depending on the season of analysis, and annually, global snow cover decreased 5.12% (not including Antarctica or Greenland) based on the Mann—Kendall test at the 95th percentile (p < 0.05). Regionally, Asia had the greatest net area decline in snow cover, followed by Europe. Although North America has the second-largest extent of snow cover, it had the least amount of net decreasing snow cover relative to its size. South America had the greatest local decline in snow cover, decreasing 20.60% of its annual (snow-year) snow cover area. The Australia–New Zealand region, with just 0.34% of the global snow cover, was the only region to have a net increase in snow cover, increasing 3.61% of its annual snow cover area. [ABSTRACT FROM AUTHOR]

The boreal winter 2019/2020 was very irregular in Europe. While there was very little snow in Central Europe, the opposite was the case in northern Fenno-Scandia, particularly in the Arctic. The snow cover was more persistent here and its rapid melting led to flooding in many places. Since the last severe spring floods occurred in the region in 2018, this raises the question of whether more frequent occurrences can be expected in the future. To assess the variability of snowmelt related flooding we used snow cover maps (derived from the DLR's Global SnowPack MODIS snow product) and freely available data on runoff, precipitation, and air temperature in eight unregulated river catchment areas. A trend analysis (Mann-Kendall test) was carried out to assess the development of the parameters, and the interdependencies of the parameters were examined with a correlation analysis. Finally, a simple snowmelt runoff model was tested for its applicability to this region. We noticed an extraordinary variability in the duration of snow cover. If this extends well into spring, rapid air temperature increases leads to enhanced thawing. According to the last flood years 2005, 2010, 2018, and 2020, we were able to differentiate between four synoptic flood types based on their special hydrometeorological and snow situation and simulate them with the snowmelt runoff model (SRM). [ABSTRACT FROM AUTHOR]