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Multi-Channel Spectral Band Adjustment Factors for Thermal Infrared Measurements of Geostationary Passive Imagers

Piontek, Dennis und Bugliaro Goggia, Luca und Müller, Richard und Muser, Lukas und Jerg, Matthias (2023) Multi-Channel Spectral Band Adjustment Factors for Thermal Infrared Measurements of Geostationary Passive Imagers. Remote Sensing, 15 (1247), Seiten 1-23. Multidisciplinary Digital Publishing Institute (MDPI). doi: 10.3390/rs15051247. ISSN 2072-4292.

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Offizielle URL: https://www.mdpi.com/2072-4292/15/5/1247

Kurzfassung

The newest and upcoming geostationary passive imagers have thermal infrared channels comparable to those of more established instruments, but their spectral response functions still differ significantly. Therefore, retrievals developed for a certain type of radiometer cannot simply be applied to another imager. Here, a set of spectral band adjustment factors is determined for MSG/SEVIRI, Himawari-8/AHI, and MTG1/FCI from a training dataset based on MetOp/IASI hyperspectral observations. These correction functions allow to turn the observation of one sensor into an analogue observation of another sensor. This way, the same satellite retrieval—that has been usually developed for a specific instrument with a specific spectral response function—can be applied to produce long time series that go beyond one single satellite/satellite series or to cover the entire geostationary ring in a consistent way. It is shown that the mean uncorrected brightness temperature differences between corresponding channels of two imagers can be >1 K, in particular for the channels centered around 13.4 μm in the carbon dioxide absorption band and even when comparing different imager realizations of the same series, such as the four SEVIRI sensors aboard MSG1 to MSG4. The spectral band adjustment factors can remove the bias and even reduce the standard deviation in the brightness temperature difference by more than 80%, with the effect being dependent on the spectral channel and the complexity of the correction function. Further tests include the application of the spectral band adjustment factors in combination with (a) a volcanic ash cloud retrieval to Himawari-8/AHI observations of the Raikoke eruption 2019 and a comparison to an ICON-ART model simulation, and (b) an ice cloud retrieval to simulated MTG1/FCI test data with the outcome compared to the retrieval results using real MSG3/SEVIRI measurements for the same scene.

elib-URL des Eintrags:https://elib.dlr.de/194045/
Dokumentart:Zeitschriftenbeitrag
Titel:Multi-Channel Spectral Band Adjustment Factors for Thermal Infrared Measurements of Geostationary Passive Imagers
Autoren:
AutorenInstitution oder E-Mail-AdresseAutoren-ORCID-iDORCID Put Code
Piontek, DennisDLR, IPAhttps://orcid.org/0000-0001-9426-0564NICHT SPEZIFIZIERT
Bugliaro Goggia, LucaDLR, IPAhttps://orcid.org/0000-0003-4793-0101NICHT SPEZIFIZIERT
Müller, RichardDWD, Offenbachhttps://orcid.org/0000-0002-0376-0393NICHT SPEZIFIZIERT
Muser, LukasAWI, Bremerhavenhttps://orcid.org/0000-0002-8453-918XNICHT SPEZIFIZIERT
Jerg, MatthiasDWD, OffenbachNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Datum:24 Februar 2023
Erschienen in:Remote Sensing
Referierte Publikation:Ja
Open Access:Ja
Gold Open Access:Ja
In SCOPUS:Ja
In ISI Web of Science:Ja
Band:15
DOI:10.3390/rs15051247
Seitenbereich:Seiten 1-23
Verlag:Multidisciplinary Digital Publishing Institute (MDPI)
ISSN:2072-4292
Status:veröffentlicht
Stichwörter:passive remote sensing; geostationary satellite imager; spectral band adjustment factor; Meteosat; Himawari
HGF - Forschungsbereich:Luftfahrt, Raumfahrt und Verkehr
HGF - Programm:Luftfahrt
HGF - Programmthema:Luftverkehr und Auswirkungen
DLR - Schwerpunkt:Luftfahrt
DLR - Forschungsgebiet:L AI - Luftverkehr und Auswirkungen
DLR - Teilgebiet (Projekt, Vorhaben):L - Klima, Wetter und Umwelt, R - Atmosphären- und Klimaforschung
Standort: Oberpfaffenhofen
Institute & Einrichtungen:Institut für Physik der Atmosphäre > Wolkenphysik
Hinterlegt von: Piontek, Dennis
Hinterlegt am:27 Feb 2023 07:21
Letzte Änderung:27 Feb 2023 07:21

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