The transition of a cold winter snowpack to one that is ripe and contributing to runoff is a complex set of processes involving boundary and internal energy fluxes that is highly variable in space and time. This transition is important to gauge, however, for resilient water resources management.

Because of the high permittivity of water compared to that of ice or air, C-band (about 5cm wavelength) synthetic aperture radar (SAR) is able to reliably detect meltwater present in the snowpack, which may provide spatially explicit information about areas of the snowpack that may be contributing to runoff. The European Space Agency’s Sentinel-1 C-band SAR satellite constellation offers consistent acquisition patterns that allow for a diurnal comparison of SAR-derived snow conditions. These may be used to identify snow surface melt/freeze cycles, which are a hallmark of snowpack warming and ripening, and could be used to validate energy balance or runoff forecasting models. However, sufficient field measurement during snowpack warming and ripening is necessary to interpret these diurnally differing SAR signals.

For my CUAHSI Pathfinder Fellowship, I was fortunate to spend six weeks living on Grand Mesa Colorado in winter/spring 2020, during which time I was able to dig over 50 snow pits to make measurements as the snowpack warmed and ripened. These measurements were made with the same protocols as the SnowEx Time Series and Intensive Observation Period campaigns on Grand Mesa, which allows for a seasonally cohesive data set. We integrate these field measurements with S1 SAR imagery as well as the physically-based SnowModel, in order to comprehensively identify snowpack phases and interpret S1 diurnal SAR snow conditions.

Here you will find processed S1 SAR imagery over Grand Mesa from July 2019 - June 2020. The Pathfinder field measurements have been incorporated with NASA SnowEx Time Series data, which will be published and publicly available through the National Snow and Ice Data Center (NSIDC) at https://nsidc.org/data/snowex.