Remote sensing of mountain snow from space: status and recommendations

Abstract

The spatial and temporal variation of the seasonal snowpack in mountain regions is recognized as a clear knowledge gap for climate, ecology and water resources applications. Here, we identify three salient topics where recent developments in snow remote sensing and data assimilation can lead to significant progress: snow water equivalent, high resolution snow-covered area and long term snow cover observations including snow albedo. These topics can be addressed in the near future with institutional support.

Evaluating Distributed Snow Model Resolution and Meteorology Parameterizations Against Streamflow Observations: Finer Is Not Always Better

“…In fact, the network only represents a small spatial footprint of the seasonal snow zone and due to the limited elevations the network covers (Bales et al, 2006) and it may become less representative of total snowpack in a less snowy future (Hammond et al, 2023). Remote sensing products can help improve spatial coverage of snowpack estimates but can be hindered by infrequent satellite return time, vegetation cover, complex topography, cloud masking, and require assumptions to produce metrics such as snow water equivalent (SWE) (Gascoin et al, 2024;Rittger et al, 2020). Reanalysis products, which can combine point measurements, remotely sensed data, and physical modeling, often struggle because of a paucity of high-elevation precipitation and snowpack measurements to assimilate into the product as well as inherent problems with their coarse spatial resolution to represent snow-terrain and snow-vegetation interactions (Clow et al, 2012).…”