An Approach for Improving Cirrus Cloud-Top Pressure/Height Estimation by Merging High-Spatial-Resolution Infrared-Window Imager Data with High-Spectral-Resolution Sounder Data

Abstract

he next-generation Visible and Infrared Imaging Radiometer Suite (VIIRS) offers infrared (IR)-window measurements with a horizontal spatial resolution of at least 1 km, but it lacks IR spectral bands that are sensitive to absorption by carbon dioxide (CO2) or water vapor (H2O). The CO2 and H2O absorption bands have high sensitivity for the inference of cloud-top pressure (CTP), especially for semitransparent ice clouds. To account for the lack of vertical resolution, the ?merging gradient? (MG) approach is introduced, wherein the high spatial resolution of an imager is combined with the high vertical resolution of a sounder for improved CTP retrievals. The Cross-Track Infrared Sounder (CrIS) is on the same payload as VIIRS. In this paper Moderate Resolution Imaging Spectroradiometer (MODIS) and Atmospheric Infrared Sounder (AIRS) data are used as proxies for VIIRS and CrIS, respectively, although the approach can be applied to any imager?sounder pair. The MG method establishes a regression relationship between gradients in both the sounder radiances convolved to imager bands and the sounder CTP retrievals. This relationship is then applied to the imager radiance measurements to obtain CTP retrievals at imager spatial resolution. Comparisons with Cloud?Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) cloud altitudes are presented for a variety of cloud scenes. Results demonstrate the ability of the MG algorithm to add spatial definition to the sounder retrievals with a higher accuracy and precision than those obtained solely from the imager.