Sutton's proposal selected for 2025 UMBC CIDER Award

"Determining the causes of false detections from satellite-derived precipitation is of utmost importance due to the development and dependence of precipitation estimates in global water cycle modeling, weather forecasting, flood modeling, landslide hazard assessment, drought monitoring, watershed modeling, and climate modeling. One kind of false detection that needs to be addressed is virga or “dry precipitation events”. They are described as “dry precipitation events” because they are considered precipitation events that occur higher in the atmosphere but evaporate before reaching the surface. This means that every satellite-based precipitation product is affected by virga because of the way in which precipitation is derived from satellite remote sensors. Satellite-based precipitation estimates are derived from cloud temperatures, emission-based retrievals, and/or scattering-based retrievals. Regardless of whether satellite-based precipitation estimates are derived from VIS/IR, passive microwave, or both, they are derived from measurements within the atmosphere and not at the surface. As a result, any analysis or model that uses satellite-based precipitation as inputs is problematic.

The purpose of this collaboration is to (1) complete a proof-of-concept project to identify virga events using vertical profiles from ground radar and (2) apply for a National Science Foundation (NSF) grant to support future work. The proof of concept will include collection of a database of virga events at one radar ground station and building a machine learning tool for flagging virga events. The NSF grant will seek to determine the influence that virga precipitation has on global precipitation datasets and climate modeling."