Integration of GOES-R into the Multi-Radar Multi-Sensor System for High Resolution, Seamless QPE in Complex Terrain

The launch of the GOES-R series of geostationary satellites over the United States will represent a major improvement in spatial, temporal, and spectral resolution of observations available from space compared to current observing capabilities. With this upgrade comes new opportunities for monitoring cloud and precipitation properties with the addition of several new channels that better characterize cloud top phase and microphysics.

A precipitation estimation algorithm has been under development at NSSL that leverages these enhanced satellite cloud top measurements to derive bulk hydrometeor profiles leading to stratiform rain or snow rates expected at the surface. The goal of the algorithm is to compliment QPE derived from the Multi-Radar Multi-Sensor (MRMS) system in areas where ground radar coverage is either nonexistent or blocked by terrain to provide a true multi-sensor, seamless, high-resolution QPE product with full coverage over the continental United States.

This presentation focuses on verification of the satellite QPE technique's performance relative to radar alone and other satellite-based algorithms across the western U.S. where radar coverage is most limited. Efforts to merge satellite observations with radar QPE and gauge-derived products in MRMS will also be discussed.