Physical retrieval for precise satellite SST measurements—GOES-R Risk Reduction Study

A physical algorithm is developed to allow precise sea surface temperatures to be derived from a combination of satellite Hyperspectral Sounder (HS) and Multi-spectral Imager (MI) data as one of the GOES-R Risk Reduction studies. The physics of the algorithm involves the formulation of the radiative transfer equation, including the surface emission, the upwelling atmospheric emission, and the surface reflected sky radiation. The accuracy goal is 0.2 C, which requires the solution to accurately account for the surface emissivity and reflectivity and the atmospheric temperature, water vapor, and trace gas contributions to the observed upwelling radiance. In order to account for these contributions, high spectral resolution HS radiance spectra, as will be measured by future operational satellites, are required. However, HS observations will be at a spatial resolution where cloud contamination will often affect the measured radiance spectra. Under these conditions, low spectral, but high horizontal, resolution radiances, from a companion MI must be used both to detect HS cloud contamination and to infer the sea surface temperature in geographical regions where the HS data are affected by partial cloudiness. The multi-sensor sea surface temperatures are combined in such a manner that the transition from clear field of view HS to partly cloudy HS field of view MI sea surface temperature determinations is relatively seamless (i.e., partly cloudy HS fields of view MI determinations possess approximately the same accuracy as the HS clear fields of view)). This characteristic is accomplished by adjusting the partly clouded HS field of view MI sea surface temperature for local difference in the HS and MI sea surface temperatures obtained for surrounding HS clear sky fields of view. This poster provides a description of the multi-sensor algorithm and presents results from applying this algorithm to Aqua satellite AIRS (HS) and MODIS (MI) measurements. These algorithms will be applied to the GOES-R HES and ABI data to achieve a precise sea surface temperature in the GOES-R era.