Laszlo, I, Ciren, P, Liu, HQ, Kondragunta, S, Tarpley, JD, Goldberg, MD (2008). Remote sensing of aerosol and radiation from geostationary satellites. ADVANCES IN SPACE RESEARCH, 41(11), 1882-1893.
Abstract
The paper presents a high-level overview of current and future remote sensing of aerosol and shortwave radiation budget carried out at the US National Oceanic and Atmospheric Administration (NOAA) from the US Geostationary Operational Environmental Satellite (GOES) series. The retrievals from the current GOES imagers are based on physical principles. Aerosol and radiation are estimated in separate processing from the comparison of satellite-observed reflectances derived from a single visible channel with those calculated from detailed radiative transfer. The radiative transfer calculation accounts for multiple scattering by molecules, aerosol and cloud and absorption by the major atmospheric gases. The retrievals are performed operationally every 30 min for aerosol and every hour for radiation for pixel sizes of 4-km (aerosol) and 15- to 50-km (radiation). Both retrievals estimate the surface reflectance as a byproduct from the time composite of clear visible reflectances assuming fixed values of the aerosol optical depth. With the launch of GOES-R NOAA will begin a new era of geostationary remote sensing. The Advanced Baseline Imager (ABI) onboard GOES-R will offer capabilities for aerosol remote sensing similar to those currently provided by the Moderate Resolution Imaging Spectroradiometer (MODIS) flown on the NASA Earth Observing System (EOS) satellites. The ABI aerosol algorithm currently under development uses a multichannel approach to estimate the aerosol optical depth and aerosol model simultaneously, both over water and land. Its design is strongly inspired by the MODIS aerosol algorithm. The ABI shortwave radiation budget algorithm is based on the successful GOES Surface and Insolation Product system of NOAA and the NASA Clouds and the Earth's Radiant Energy System (CERES), Surface and Atmospheric Radiation Budget (SARB) algorithm. In all phases of the development, the algorithms are tested with proxy data generated from existing satellite observations and forward simulations. Final assessment of the performance will be made after the launch of GOES-R scheduled in 2012. Published by Elsevier Ltd on behalf of COSPAR.
DOI:
10.1016/j.asr.2007.06.047
ISSN:
0273-1177