Utilizing CLAVR-x to Model Sensitivity of Cloud Products to Satellite Sensor Performance

Sensor performance plays a central role in the quality of weather data products produced by weather satellite observing systems. Next generation sensors harness commercial technologies and small satellite architectures that may include fewer spectral bands. The Weather Remote Sensing Systems Office (WRSSO) at The Aerospace Corporation is developing an end-to-end modeling and simulation testbed for performance analysis using CLAVR-x, a cloud detection algorithm made available by the Cooperative Institute of Meteorological Satellite Studies (CIMSS) at the University of Wisconsin. The current version of the testbed is being developed specifically for the U.S. Space Force’s EO/IR Weather System (EWS) mission to fill two top priority observational needs: cloud characterization and theater weather imagery. Orion Space Solutions’ Rapid Revisit Optical Cloud Imager (RROCI) is a next generation CubeSat approach to weather monitoring using 8 spectral bands corresponding to equivalent MODIS bands. We present simulations of RROCI sensor performance based on MODIS data, including the sensitivity of cloud products to sensor errors.