{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,8]],"date-time":"2026-07-08T20:32:21Z","timestamp":1783542741022,"version":"3.55.0"},"reference-count":33,"publisher":"MDPI AG","issue":"24","license":[{"start":{"date-parts":[[2022,12,18]],"date-time":"2022-12-18T00:00:00Z","timestamp":1671321600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Key R&amp;D Program of China","award":["2019YFA0607001"],"award-info":[{"award-number":["2019YFA0607001"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The Arctic region plays an important role in the global climate system. To promote the application of Medium Resolution Spectral Imager-II (MERSI-II) data in the ice surface temperature (IST) inversion, we used the thermal infrared channels (channels 24 and 25) of the MERSI-II onboard Chinese FY-3D satellite and the thermal infrared channels (channels 31 and 32) of the Earth Observing System (EOS) Moderate-Resolution Imaging Spectroradiometer (MODIS) onboard the National Aeronautical and Space Administration (NASA) Aqua satellite for data analysis. Using the Observation\u2013Observation cross-calibration algorithm to cross-calibrate the MERSI and MODIS thermal infrared brightness temperature (Tb) data in the Arctic, channel 24 and 25 data from the FY-3D\/MERSI-II on Arctic ice were evaluated. The thermal infrared Tb data of the MERSI-II were used to retrieve the IST via the split-window algorithm. In this study, the correlation coefficients of the thermal infrared channel Tb data between the MERSI and MODIS were &gt;0.95, the mean bias was \u22120.5501\u20130.1262 K, and the standard deviation (Std) was &lt;1.3582 K. After linear fitting, the MERSI-II thermal infrared Tb data were closer to the MODIS data, and the bias range of the 11 \u03bcm and 12 \u03bcm channels was \u22120.0214\u20130.0119 K and the Std was &lt;1.2987 K. These results indicate that the quality of the MERSI-II data is comparable to that of the MODIS data, so that can be used for application to IST inversion. When using the MERSI thermal infrared Tb data after calibration to retrieve the IST, the results of the MERSI and MODIS IST were more consistent. By comparing the IST retrieved from the MERSI thermal infrared calibrated Tb data with MODIS MYD29 product, the mean bias was \u22120.0612\u20130.0423 \u00b0C and the Std was &lt;1.3988 \u00b0C. Using the MERSI thermal infrared Tb data after calibration is better than that before calibration for retrieving the IST. When comparing the Arctic ocean sea and ice surface temperature reprocessed data (L4 SST\/IST) with the IST data retrieved from MERSI, the bias was 0.9891\u20132.7510 \u00b0C, and the Std was &lt;3.5774 \u00b0C.<\/jats:p>","DOI":"10.3390\/rs14246392","type":"journal-article","created":{"date-parts":[[2022,12,19]],"date-time":"2022-12-19T08:41:41Z","timestamp":1671439301000},"page":"6392","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Quality Assessment of FY-3D\/MERSI-II Thermal Infrared Brightness Temperature Data from the Arctic Region: Application to Ice Surface Temperature Inversion"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8031-8718","authenticated-orcid":false,"given":"Haihua","family":"Chen","sequence":"first","affiliation":[{"name":"Faculty of Information Science and Engineering, College of Marine Technology, Ocean University of China, Qingdao 266100, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5512-6370","authenticated-orcid":false,"given":"Xin","family":"Meng","sequence":"additional","affiliation":[{"name":"Faculty of Information Science and Engineering, College of Marine Technology, Ocean University of China, Qingdao 266100, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lele","family":"Li","sequence":"additional","affiliation":[{"name":"Faculty of Information Science and Engineering, College of Marine Technology, Ocean University of China, Qingdao 266100, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9065-5267","authenticated-orcid":false,"given":"Kun","family":"Ni","sequence":"additional","affiliation":[{"name":"Faculty of Information Science and Engineering, College of Marine Technology, Ocean University of China, Qingdao 266100, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,12,18]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"12609","DOI":"10.1029\/97JC00480","article-title":"Sensitivity of a global sea ice model to the treatment of ice thermodynamics and dynamics","volume":"102","author":"Fichefet","year":"1997","journal-title":"J. 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