{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,27]],"date-time":"2026-05-27T21:13:20Z","timestamp":1779916400950,"version":"3.53.1"},"reference-count":79,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2023,2,24]],"date-time":"2023-02-24T00:00:00Z","timestamp":1677196800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"German weather service (Deutscher Wetterdienst, DWD)","award":["VA-ICE-2020"],"award-info":[{"award-number":["VA-ICE-2020"]}]},{"name":"German weather service (Deutscher Wetterdienst, DWD)","award":["M-ICE-2022"],"award-info":[{"award-number":["M-ICE-2022"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>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\u2014that has been usually developed for a specific instrument with a specific spectral response function\u2014can 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 &gt;1 K, in particular for the channels centered around 13.4 \u03bcm 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.<\/jats:p>","DOI":"10.3390\/rs15051247","type":"journal-article","created":{"date-parts":[[2023,2,24]],"date-time":"2023-02-24T02:32:12Z","timestamp":1677205932000},"page":"1247","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Multi-Channel Spectral Band Adjustment Factors for Thermal Infrared Measurements of Geostationary Passive Imagers"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9426-0564","authenticated-orcid":false,"given":"Dennis","family":"Piontek","sequence":"first","affiliation":[{"name":"Deutsches Zentrum f\u00fcr Luft- und Raumfahrt (DLR), Institut f\u00fcr Physik der Atmosph\u00e4re, 82234 Oberpfaffenhofen, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4793-0101","authenticated-orcid":false,"given":"Luca","family":"Bugliaro","sequence":"additional","affiliation":[{"name":"Deutsches Zentrum f\u00fcr Luft- und Raumfahrt (DLR), Institut f\u00fcr Physik der Atmosph\u00e4re, 82234 Oberpfaffenhofen, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0376-0393","authenticated-orcid":false,"given":"Richard","family":"M\u00fcller","sequence":"additional","affiliation":[{"name":"Deutscher Wetterdienst (DWD), 63067 Offenbach, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8453-918X","authenticated-orcid":false,"given":"Lukas","family":"Muser","sequence":"additional","affiliation":[{"name":"Karlsruhe Institute of Technology (KIT), Institute of Meteorology and Climate Research, 76131 Karlsruhe, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Matthias","family":"Jerg","sequence":"additional","affiliation":[{"name":"Deutscher Wetterdienst (DWD), 63067 Offenbach, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2023,2,24]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"977","DOI":"10.1175\/BAMS-83-7-Schmetz-2","article-title":"An Introduction to Meteosat Second Generation (MSG)","volume":"83","author":"Schmetz","year":"2002","journal-title":"Bull. 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