A Bayesian Framework to Quantify Uncertainty in Aerosol Optical Model Selection Applied to TROPOMI Measurements

A Bayesian Framework to Quantify Uncertainty in Aerosol Optical Model Selection Applied to TROPOMI Measurements

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...

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Bibliografische gegevens
Hoofdauteurs: Anu Kauppi, Antti Kukkurainen, Antti Lipponen, Marko Laine, Antti Arola, Hannakaisa Lindqvist, Johanna Tamminen
Formaat: Artikel
Taal:English
Gepubliceerd in: MDPI AG 2024-05-01
Reeks:Remote Sensing
Onderwerpen:
aerosol retrieval
model selection
uncertainty
Bayesian inference
TROPOMI/S5P
Online toegang:https://www.mdpi.com/2072-4292/16/11/1945

Internet

https://www.mdpi.com/2072-4292/16/11/1945

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