2022
DOI: 10.1117/1.jrs.16.044507
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Fast and operational gap filling in satellite-derived aerosol optical depths using statistical techniques

Abstract: Satellite observations, used worldwide in the atmospheric sciences, are extremely useful for providing aerosol information within a wide spatial range. However, the coverage of aerosol data by satellite observations is sometimes of inferior quality because of the effects of surface reflectivity and clouds. To fill the gaps in aerosol optical depths (AODs) retrieved from geostationary ocean color imager observations, this study applies operational statistical techniques, including radial basis functions (RBFs) … Show more

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Cited by 3 publications
(1 citation statement)
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“…Additionally, GEMS AODs were utilized to update initial conditions of the Community Multiscale Air Quality Modeling System (CMAQ) 3,4 , via the three dimensional variational (3D-VAR) data assimilation (DA) system 5 . The 3D-VAR method is designed to estimate the optimal x by minimizing a cost function (J), which measures the distance of the state vector to the background and observations, obtained by (2) where H is an observation operator, xb denotes a priori information of x, and y represents an observation vector. B and R are background and observation error covariances, respectively.…”
Section: Data Assimilationmentioning
confidence: 99%
“…Additionally, GEMS AODs were utilized to update initial conditions of the Community Multiscale Air Quality Modeling System (CMAQ) 3,4 , via the three dimensional variational (3D-VAR) data assimilation (DA) system 5 . The 3D-VAR method is designed to estimate the optimal x by minimizing a cost function (J), which measures the distance of the state vector to the background and observations, obtained by (2) where H is an observation operator, xb denotes a priori information of x, and y represents an observation vector. B and R are background and observation error covariances, respectively.…”
Section: Data Assimilationmentioning
confidence: 99%