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Potential of bias correction for downscaling passive microwave and soil moisture data
Author(s) -
Kornelsen Kurt C.,
Cosh Michael H.,
Coulibaly Paulin
Publication year - 2015
Publication title -
journal of geophysical research: atmospheres
Language(s) - English
Resource type - Journals
eISSN - 2169-8996
pISSN - 2169-897X
DOI - 10.1002/2015jd023550
Subject(s) - downscaling , environmental science , water content , watershed , brightness temperature , moisture , soil science , microwave , atmospheric sciences , hydrology (agriculture) , remote sensing , meteorology , precipitation , geology , geography , physics , geotechnical engineering , quantum mechanics , machine learning , computer science
Passive microwave satellites such as Soil Moisture and Ocean Salinity or Soil Moisture Active Passive observe brightness temperature (TB) and retrieve soil moisture at a spatial resolution greater than most hydrological processes. Bias correction is proposed as a simple method to disaggregate soil moisture to a scale more appropriate for hydrological applications. Temporal stability of soil moisture and TB was demonstrated at the Little Washita and Little River Experimental Watersheds using in situ observations and the Community Microwave Emissions Model. Decomposition of the mean square difference (MSD) between the watershed average soil moisture and TB showed that bias was a major contributor to differences between watershed average and local‐scale soil moisture and TB, particularly at sites with high MSD. The mean RMSD between watershed average and local soil moisture was 0.04 m 3 m −3 and 0.06 m 3 m −3 at Little River and Little Washita, respectively. Following a simple bias correction the RMSD was reduced to 0.03 m 3 m −3 at both sites. Considering multiple incidence angles at both horizontal and vertical polarization, bias correction of watershed average TB V reduced the RMSD by approximately 75% and 45% and TB H RMSD by 68% and 36% for Little River and Little Washita, respectively, at all incidence angles. Therefore, at subsatellite grid scale, bias correction can be considered a viable technique for downscaling passive microwave observations and soil moisture retrievals.