A Bayesian Framework to Quantify Uncertainty in Aerosol Optical Model Selection Applied to TROPOMI M...
A Bayesian Framework to Quantify Uncertainty in Aerosol Optical Model Selection Applied to TROPOMI Measurements
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Basel: MDPI AG
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Language
English
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Basel: MDPI AG
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This article presents a method within a Bayesian framework for quantifying uncertainty in satellite aerosol remote sensing when retrieving aerosol optical depth (AOD). By using a Bayesian model averaging technique, we take into account uncertainty in aerosol optical model selection and also obtain a shared inference about AOD based on the best-fitt...
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Full title
A Bayesian Framework to Quantify Uncertainty in Aerosol Optical Model Selection Applied to TROPOMI Measurements
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TN_cdi_doaj_primary_oai_doaj_org_article_db283734558c46ea9895e837df5b0081
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_db283734558c46ea9895e837df5b0081
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ISSN
2072-4292
E-ISSN
2072-4292
DOI
10.3390/rs16111945
