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A Strategy to Improve the GOES-R Land Surface Temperature Product with All Weather Information in Near Real Time
  • Anand K Inamdar
Anand K Inamdar

Corresponding Author:anand.inamdar@noaa.gov

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LST is routinely retrieved from the GOES-R Advanced Baseline Imager (ABI) long wave spectral channels. Since the product is available only under clear sky conditions, large gaps exist in the data stream which correspond to contamination by clouds. However, continuous estimates of LST data are still vitally needed for several applications such as drought monitoring ,vegetation growth, and crop yield estimation etc. Studies have shown that LST tracks with corresponding changes in incident solar radiation or more specifically changes in surface absorbed solar radiation with good correlation irrespective of sky conditions (clear or cloudy). In the present study, a scheme is developed to fill in the large spatio-temporal gaps in the LST time series using surface solar absorption parameter (SSA) retrieved in near real time from other satellites. Validation of retrieved LST values over all of the SURFRAD stations reveal RMS errors of less than 1 K.