Utilizing CLAVR-x to model sensitivity of cloud products to satellite sensor performance

Cameron Martus; Brian Johnson; David Moyer; Patrick Johnson; Joel Thomas

doi:10.1117/12.3031204

20 November 2024 Utilizing CLAVR-x to model sensitivity of cloud products to satellite sensor performance

Cameron Martus, Brian Johnson, David Moyer, Patrick Johnson, Joel Thomas

Proceedings Volume 13193, Remote Sensing of Clouds and the Atmosphere XXIX; 131930E (2024) https://doi.org/10.1117/12.3031204
Event: Remote Sensing, 2024, Edinburgh, United Kingdom

Abstract

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 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. We present simulations of sensor performance based on MODIS data, characterizing the sensitivity of cloud products to sensor errors.

Conference Presentation

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Cameron Martus, Brian Johnson, David Moyer, Patrick Johnson, and Joel Thomas "Utilizing CLAVR-x to model sensitivity of cloud products to satellite sensor performance", Proc. SPIE 13193, Remote Sensing of Clouds and the Atmosphere XXIX, 131930E (20 November 2024); https://doi.org/10.1117/12.3031204

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