How can the proposed WIVERN satellite mission improve global snowfall measurements?

Snowfall is an important climate change indicator affecting surface albedo, glaciers, sea ice, freshwater storage, and cloud lifetime. Accurate snowfall measurements at high latitudes are particularly important for the mass balance of ice sheets and for sustaining healthy ecosystems, including fish and wildlife populations. Yet, snowfall remains a quantity which is hard to measure due to high spatial variability, the remoteness of polar regions and challenges associated with in situ measurements of snowfall. The recently decommissioned NASA CloudSat mission provided invaluable information about global snowfall climatology from 2006 to 2023. The CloudSat-based estimates of global snowfall are considered the reference for global snowfall estimates, but these data sets suffer from poor sampling and the inability to see shallow precipitation, which limits their use, for example, as input to surface mass balance models of the major ice sheets. WIVERN (WInd VElocity Radar Nephoscope) is one of the two remaining ESA Earth Explorer 11 candidate missions equipped with a conical scanning 94 GHz radar and a passive 94 GHz radiometer. The main objective of the mission is to measure global in-cloud winds using the Doppler effect, but can also quantify cloud ice water content and precipitation rate. 

 

This presentation discusses the potential of the WIVERN mission to provide improved estimates of global snowfall measurements. Compared to CloudSat, WIVERN's 800 km swath provides 70 times better coverage and its 42 degree angle of arrival significantly reduces the radar blind zone near the surface (especially over the ocean). In addition, WIVERN's radar is accompanied by a radiometer, which can further improve the estimation of snowfall rates. The improved sampling is demonstrated for specific regions ( Antarctica, Greenland) by computing the sampling error at different spatial and temporal scales via simulations of WIVERN vs. CloudSat orbits based on the snowfall rates produced by ERA5 reanalysis. Clutter and signal to clutter ratio simulations are performed for oceanic surfaces and orographic terrains by using a geometric–optics approach and the WIVERN illumination geometry.  Our results show that the WIVERN sampling strategy significantly reduces the uncertainty in polar snowfall estimates, making it a valuable product for climate model evaluation and as an input to surface mass balance models of the major ice sheets.