Dual-Regression Retrieval Algorithm for Real-Time Processing of Satellite Ultraspectral Radiances

• DOI: 10.1175/jamc-d-11-0173.1
• Publication Date: 2012-03-15T21:52:17Z
• Authors: William L. Smith; Elisabeth Weisz; Stanislav V. Kireev; Daniel K. Zhou; Zhenglong Li; Eva E. Borbas
• Keywords: Cloud top; Atmospheric Infrared Sounder; Moderate-resolution imaging spectroradiometer; Infrared window; Cloud height; Spectroradiometer

Abstract A fast physically based dual-regression (DR) method is developed to produce, in real time, accurate profile and surface- cloud-property retrievals from satellite ultraspectral radiances observed for both clear- cloudy-sky conditions. The DR relies on using empirical orthogonal function (EOF) regression “clear trained” “cloud of surface skin temperature, surface-emissivity EOF coefficients, carbon dioxide concentration, cloud-top altitude, effective cloud optical depth, atmospheric moisture, ozone profiles above the below thin or broken cloud. cloud-trained retrieval obtained cloud-height-classified statistical datasets. result a with an accuracy that much higher than associated produced by unclassified currently used International Moderate Resolution Imaging Spectroradiometer/Atmospheric Infrared Sounder (MODIS/AIRS) Processing Package (IMAPP) system. improvement results fact nonlinear dependence spectral radiance variables, which due altitude moisture concentration variations, minimized as cloud-height-classification process. detailed example applications algorithm are presented. new will be retrieve Aqua AIRS, MetOp Atmospheric Sounding Interferometer, forthcoming Joint Polar Satellite System data.