A Methodology for Limb-correction and Intercalibration of Next-Generation Geostationary Sensors to Improve Analysis of Multispectral Composite Imagery

NASA's MODIS instruments on the Terra and Aqua satellites have been providing imaging capabilities from polar orbit for the last 20 years allowing for twice daily sampling of mesoscale atmospheric features with multispectral or Red, Green, Blue (RGB) composite imagery. With the launch of the next generation of geostationary sensors the capability exists for expanded coverage of RGB imagery with the ability to track features over long distances and study the processes that contribute to the development of fast evolving features. However, the use of RGB imagery on a global basis is not without limitations due to the impact of limb-effects at high viewing angles and subtle spectral channel differences between satellite sensors. Previous work by Elmer et al. (2016, 2019) and Berndt et al. (2018) to develop limb-correction coefficients and intercalibration of sensors with differing spectral characteristics has been expanded to include new geostationary sensors. This presentation highlights the updated limb-correction and intercalibration methodology for near-infrared, thermal infrared, and water vapor bands (i.e. 3.7 - 13 µm) for the purpose of developing a suite of high-quality RGB imagery including the Air Mass, Differential Water Vapor, Simple Water Vapor, Night-time Microphysics, and Dust RGB products. Preliminary results demonstrating new, science-quality RGB products will be presented as examples that will allow for new investigations of fast changing weather and hazards. Once validated, the suite of RGBs will be created for select case studies and then used to demonstrate the value of the limb-corrected, intercalibrated RGBs for process studies (e.g., cyclogenesis, hurricane development, dust storms, and development of fog). This research will advance NASA Earth science research and application programs through the use of U.S. and International geostationary satellite data to provide RGB products critical to improve the understanding of weather and climate process and for associated weather forecasting applications.