Sasi, Sruthy und Natraj, V. und Molina García, Víctor und Efremenko, Dmitry und Loyola, Diego und Doicu, Adrian (2020) Model Selection in Atmospheric Remote Sensing with an Application to Aerosol Retrieval from DSCOVR/EPIC, Part 1: Theory. Remote Sensing, 12 (22), 3724_1-3724_29. Multidisciplinary Digital Publishing Institute (MDPI). doi: 10.3390/rs12223724. ISSN 2072-4292.
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Offizielle URL: https://www.mdpi.com/2072-4292/12/22/3724
Kurzfassung
The retrieval of aerosol and cloud properties such as their optical thickness and/or layer/top height requires the selection of a model that describes their microphysical properties. We demonstrate that, if there is not enough information for an appropriate microphysical model selection, the solution’s accuracy can be improved if the model uncertainty is taken into account and appropriately quantified. For this purpose, we design a retrieval algorithm accounting for the uncertainty in model selection. The algorithm is based on (i) the computation of each model solution using the iteratively regularized Gauss–Newton method, (ii) the linearization of the forward model around the solution, and (iii) the maximum marginal likelihood estimation and the generalized cross-validation to estimate the optimal model. The algorithm is applied to the retrieval of aerosol optical thickness and aerosol layer height from synthetic measurements corresponding to the Earth Polychromatic Imaging Camera (EPIC) instrument onboard the Deep Space Climate Observatory (DSCOVR) satellite. Our numerical simulations show that the heuristic approach based on the thesolution minimizing the residual, which is frequently used in literature, is completely unrealistic when both the aerosol model and surface albedo are unknown.
elib-URL des Eintrags: | https://elib.dlr.de/146090/ | ||||||||||||||||||||||||||||
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Dokumentart: | Zeitschriftenbeitrag | ||||||||||||||||||||||||||||
Titel: | Model Selection in Atmospheric Remote Sensing with an Application to Aerosol Retrieval from DSCOVR/EPIC, Part 1: Theory | ||||||||||||||||||||||||||||
Autoren: |
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Datum: | 12 November 2020 | ||||||||||||||||||||||||||||
Erschienen in: | Remote Sensing | ||||||||||||||||||||||||||||
Referierte Publikation: | Ja | ||||||||||||||||||||||||||||
Open Access: | Ja | ||||||||||||||||||||||||||||
Gold Open Access: | Ja | ||||||||||||||||||||||||||||
In SCOPUS: | Ja | ||||||||||||||||||||||||||||
In ISI Web of Science: | Ja | ||||||||||||||||||||||||||||
Band: | 12 | ||||||||||||||||||||||||||||
DOI: | 10.3390/rs12223724 | ||||||||||||||||||||||||||||
Seitenbereich: | 3724_1-3724_29 | ||||||||||||||||||||||||||||
Verlag: | Multidisciplinary Digital Publishing Institute (MDPI) | ||||||||||||||||||||||||||||
ISSN: | 2072-4292 | ||||||||||||||||||||||||||||
Status: | veröffentlicht | ||||||||||||||||||||||||||||
Stichwörter: | EPIC, aerosol | ||||||||||||||||||||||||||||
HGF - Forschungsbereich: | Luftfahrt, Raumfahrt und Verkehr | ||||||||||||||||||||||||||||
HGF - Programm: | Raumfahrt | ||||||||||||||||||||||||||||
HGF - Programmthema: | Erdbeobachtung | ||||||||||||||||||||||||||||
DLR - Schwerpunkt: | Raumfahrt | ||||||||||||||||||||||||||||
DLR - Forschungsgebiet: | R EO - Erdbeobachtung | ||||||||||||||||||||||||||||
DLR - Teilgebiet (Projekt, Vorhaben): | R - Atmosphären- und Klimaforschung, R - Spektroskopische Verfahren der Atmosphäre | ||||||||||||||||||||||||||||
Standort: | Oberpfaffenhofen | ||||||||||||||||||||||||||||
Institute & Einrichtungen: | Institut für Methodik der Fernerkundung > Atmosphärenprozessoren | ||||||||||||||||||||||||||||
Hinterlegt von: | Loyola, Dr.-Ing. Diego | ||||||||||||||||||||||||||||
Hinterlegt am: | 25 Nov 2021 10:36 | ||||||||||||||||||||||||||||
Letzte Änderung: | 25 Nov 2021 10:36 |
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