Wednesday, 23 January 2008
Development of the GOES-R ABI Outgoing Longwave Radiation product
Exhibit Hall B (Ernest N. Morial Convention Center)
The next generation of NOAA Geostationary Operational Environment Satellite, R series (GOES-R), is scheduled to launch in approximately 2014 and will provide critical support for NOAA's missions with its advanced instruments and a comprehensive suite of quantitative environmental data. Complete Earth Radiation Budget (ERB) parameters at both the top of the atmosphere and the Earth's surface will be derived from the Advanced Baseline Imager (ABI) observations. This would be the first time that such parameters are derived operationally from the NOAA geostationary satellites, whereas the top of the atmosphere ERB parameters have been derived operationally and continuously from the NOAA Polar Orbiting Environmental Satellites (POES) of the TIROS-N series since 1979. This paper describes the development of the preliminary version of the Outgoing Longwave Radiation (OLR) algorithm that will be implemented for the GOES-R ABI instrument. We employed two surrogate instruments for the development purpose, including the Moderate-Resolution Imaging Spectroradiometer (MODIS) onboard NASA EOS satellites and the Spinning Enhanced Visible and Infrared Imager (SEVIRI) onboard the EUMETSAT METEOSAT satellites. The Single Scanner Footprint (SSF) OLR product derived from the broadband observations by the NASA Cloud and Earth's Radiant Energy System (CERES) was used as the validation reference. We have assessed the instantaneous OLR retrieval errors from MODIS and SEVIRI-derived OLR surrogating ABI capability that are at about 5 and 4 Wm-2, over the global and over the Eumetsat-8 full-disk domain, respectively. This is very satisfying as it is within the instantaneous error of the one-sigma uncertainty of the broadband OLR observations, about 5 Wm-2. Nevertheless, relatively large biases were observed over some regions, e.g., deserts. There also appeared to have view zenith angle dependent biases in the SEVIRI-derived OLR. The detailed validation results and its error analysis will be presented, and some experiment results attempting to improve the regional accuracies will be discussed.