{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,12]],"date-time":"2026-02-12T14:52:41Z","timestamp":1770907961175,"version":"3.50.1"},"reference-count":43,"publisher":"MDPI AG","issue":"23","license":[{"start":{"date-parts":[[2024,12,7]],"date-time":"2024-12-07T00:00:00Z","timestamp":1733529600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2021YFC2803303"],"award-info":[{"award-number":["2021YFC2803303"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["41676179"],"award-info":[{"award-number":["41676179"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2042024kf0037"],"award-info":[{"award-number":["2042024kf0037"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2042022dx0001"],"award-info":[{"award-number":["2042022dx0001"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2024040701010030"],"award-info":[{"award-number":["2024040701010030"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["2021YFC2803303"],"award-info":[{"award-number":["2021YFC2803303"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41676179"],"award-info":[{"award-number":["41676179"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["2042024kf0037"],"award-info":[{"award-number":["2042024kf0037"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["2042022dx0001"],"award-info":[{"award-number":["2042022dx0001"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["2024040701010030"],"award-info":[{"award-number":["2024040701010030"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Fundamental Research Funds for the Central Universities, China","award":["2021YFC2803303"],"award-info":[{"award-number":["2021YFC2803303"]}]},{"name":"Fundamental Research Funds for the Central Universities, China","award":["41676179"],"award-info":[{"award-number":["41676179"]}]},{"name":"Fundamental Research Funds for the Central Universities, China","award":["2042024kf0037"],"award-info":[{"award-number":["2042024kf0037"]}]},{"name":"Fundamental Research Funds for the Central Universities, China","award":["2042022dx0001"],"award-info":[{"award-number":["2042022dx0001"]}]},{"name":"Fundamental Research Funds for the Central Universities, China","award":["2024040701010030"],"award-info":[{"award-number":["2024040701010030"]}]},{"name":"Natural Science Foundation of Wuhan","award":["2021YFC2803303"],"award-info":[{"award-number":["2021YFC2803303"]}]},{"name":"Natural Science Foundation of Wuhan","award":["41676179"],"award-info":[{"award-number":["41676179"]}]},{"name":"Natural Science Foundation of Wuhan","award":["2042024kf0037"],"award-info":[{"award-number":["2042024kf0037"]}]},{"name":"Natural Science Foundation of Wuhan","award":["2042022dx0001"],"award-info":[{"award-number":["2042022dx0001"]}]},{"name":"Natural Science Foundation of Wuhan","award":["2024040701010030"],"award-info":[{"award-number":["2024040701010030"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Arctic sea-ice surface temperature (IST) is an important environmental and climatic parameter. Currently, wide-swath sea-ice surface temperature products have a spatial resolution of approximately 1000 m. The Medium Resolution Spectral Imager (MERSI-I) offers a thermal infrared channel with a wide-swath width of 2900 km and a high spatial resolution of 250 m. In this study, we developed an applicable single-channel algorithm to retrieve ISTs from MERSI-I data. The algorithm accounts for the following challenges: (1) the wide range of incidence angle; (2) the unstable snow-covered ice surface; (3) the variation in atmospheric water vapor content; and (4) the unique spectral response function of MERSI-I. We reduced the impact of using a constant emissivity on the IST retrieval accuracy by simulating the directional emissivity. Different ice surface types were used in the simulation, and we recommend the sun crust type as the most suitable for IST retrieval. We estimated the real-time water vapor content using a band ratio method from the MERSI-I near-infrared data. The results show that the retrieved IST was lower than the buoy measurements, with a mean bias and root-mean-square error (RMSE) of \u22121.928 K and 2.616 K. The retrieved IST is higher than the IceBridge measurements, with a mean bias and RMSE of 1.056 K and 1.760 K. Compared with the original algorithm, the developed algorithm has higher accuracy and reliability. The sensitivity analysis shows that the atmospheric water vapor content with an error of 20% may lead to an IST retrieval error of less than 1.01 K.<\/jats:p>","DOI":"10.3390\/rs16234599","type":"journal-article","created":{"date-parts":[[2024,12,9]],"date-time":"2024-12-09T10:11:47Z","timestamp":1733739107000},"page":"4599","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Arctic Sea Ice Surface Temperature Retrieval from FengYun-3A MERSI-I Data"],"prefix":"10.3390","volume":"16","author":[{"given":"Yachao","family":"Li","sequence":"first","affiliation":[{"name":"Chinese Antarctic Center of Surveying and Mapping, Wuhan University, Wuhan 430070, China"},{"name":"Key Laboratory of Polar Environment Monitoring and Public Governance, Ministry of Education, Wuhan 430079, China"}]},{"given":"Tingting","family":"Liu","sequence":"additional","affiliation":[{"name":"Chinese Antarctic Center of Surveying and Mapping, Wuhan University, Wuhan 430070, China"},{"name":"Key Laboratory of Polar Environment Monitoring and Public Governance, Ministry of Education, Wuhan 430079, China"}]},{"given":"Zemin","family":"Wang","sequence":"additional","affiliation":[{"name":"Chinese Antarctic Center of Surveying and Mapping, Wuhan University, Wuhan 430070, China"},{"name":"Key Laboratory of Polar Environment Monitoring and Public Governance, Ministry of Education, Wuhan 430079, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3968-9322","authenticated-orcid":false,"given":"Mohammed","family":"Shokr","sequence":"additional","affiliation":[{"name":"Meteorological Research Branch, Environment and Climate Change Canada, Toronto, ON M3H5T4, Canada"}]},{"given":"Menglin","family":"Yuan","sequence":"additional","affiliation":[{"name":"Chinese Antarctic Center of Surveying and Mapping, Wuhan University, Wuhan 430070, China"},{"name":"Key Laboratory of Polar Environment Monitoring and Public Governance, Ministry of Education, Wuhan 430079, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7140-2224","authenticated-orcid":false,"given":"Qiangqiang","family":"Yuan","sequence":"additional","affiliation":[{"name":"Key Laboratory of Polar Environment Monitoring and Public Governance, Ministry of Education, Wuhan 430079, China"},{"name":"School of Geodesy and Geomatics, Wuhan University, Wuhan 430079, China"}]},{"given":"Shiyu","family":"Wu","sequence":"additional","affiliation":[{"name":"Chinese Antarctic Center of Surveying and Mapping, Wuhan University, Wuhan 430070, China"},{"name":"Key Laboratory of Polar Environment Monitoring and Public Governance, Ministry of Education, Wuhan 430079, China"}]}],"member":"1968","published-online":{"date-parts":[[2024,12,7]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1334","DOI":"10.1038\/nature09051","article-title":"The central role of diminishing sea ice in recent Arctic temperature amplification","volume":"464","author":"Screen","year":"2010","journal-title":"Nature"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"2159","DOI":"10.5194\/tc-12-2159-2018","article-title":"Sunlight, clouds, sea ice, albedo, and the radiative budget: The umbrella versus the blanket","volume":"12","author":"Perovich","year":"2018","journal-title":"Cryosphere"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"420","DOI":"10.3189\/172756402781818067","article-title":"Correlation and trend studies of the sea-ice cover and surface temperatures in the Arctic","volume":"34","author":"Comiso","year":"2002","journal-title":"Ann. Glaciol."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1029\/2007GL031972","article-title":"Accelerated decline in the Arctic sea ice cover","volume":"35","author":"Comiso","year":"2008","journal-title":"Geophys. Res. Lett."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"856","DOI":"10.1038\/nclimate3011","article-title":"Contribution of sea-ice loss to Arctic amplification is regulated by Pacific Ocean decadal variability","volume":"6","author":"Screen","year":"2016","journal-title":"Nat. Clim. Chang"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Kumar, A., Perlwitz, J., Eischeid, J., Quan, X.W., Xu, T.Y., Zhang, T., Hoerling, M., Jha, B., and Wang, W.Q. (2010). Contribution of sea ice loss to Arctic amplification. Geophys. Res. Lett., 37.","DOI":"10.1029\/2010GL045022"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"2440","DOI":"10.1002\/2017JC013481","article-title":"Impact of Assimilation of Sea-Ice Surface Temperatures on a Coupled Ocean and Sea-Ice Model","volume":"123","author":"Rasmussen","year":"2018","journal-title":"J. Geophys. Res.-Oceans"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"2676","DOI":"10.1175\/JTECH-D-13-00058.1","article-title":"A novel and low-cost sea ice mass balance buoy","volume":"30","author":"Jackson","year":"2013","journal-title":"J. Atmos. Ocean. Technol."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1076","DOI":"10.1109\/TGRS.2004.825587","article-title":"Sea ice surface temperature product from MODIS","volume":"42","author":"Hall","year":"2004","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"8557","DOI":"10.1109\/TGRS.2019.2921606","article-title":"An improved single-channel polar region ice surface temperature retrieval algorithm using Landsat-8 data","volume":"57","author":"Li","year":"2019","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"302","DOI":"10.1016\/S0034-4257(97)89497-7","article-title":"High-latitude surface temperature estimates from thermal satellite data","volume":"61","author":"Key","year":"1997","journal-title":"Remote Sens. Environ."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"111975","DOI":"10.1016\/j.rse.2020.111975","article-title":"Sea ice surface temperature retrieval from Landsat 8\/TIRS: Evaluation of five methods against in situ temperature records and MODIS IST in Arctic region","volume":"248","author":"Fan","year":"2020","journal-title":"Remote Sens. Environ."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"181","DOI":"10.1016\/S0034-4257(02)00095-0","article-title":"MODIS snow-cover products","volume":"83","author":"Hall","year":"2002","journal-title":"Remote Sens. Environ."},{"key":"ref_14","first-page":"301","article-title":"The HY-1 satellite and ground system in China","volume":"22","author":"Liu","year":"2003","journal-title":"Acta Oceanol. Sin."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"251","DOI":"10.1080\/17538947.2012.658666","article-title":"Improvements on global meteorological observations from the current Fengyun 3 satellites and beyond","volume":"5","author":"Yang","year":"2012","journal-title":"Int. J. Digit. Earth"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"654","DOI":"10.1109\/JSTARS.2021.3137230","article-title":"Evaluation of sea surface temperatures derived from the HY-1D satellite","volume":"15","author":"Ye","year":"2022","journal-title":"IEEE J. Sel. Top. Appl. Earth Observ. Remote Sens."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"3250","DOI":"10.3390\/rs70303250","article-title":"Estimation and validation of land surface temperatures from Chinese second-generation polar-orbit FY-3A VIRR data","volume":"7","author":"Tang","year":"2015","journal-title":"Remote Sens."},{"key":"ref_18","first-page":"1","article-title":"Retrieval of sea surface temperature from HY-1B COCTS","volume":"60","author":"Liu","year":"2022","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1191","DOI":"10.1016\/j.asr.2012.01.014","article-title":"An introduction to China FY3 radio occultation mission and its measurement simulation","volume":"49","author":"Bi","year":"2012","journal-title":"Adv. Space Res."},{"key":"ref_20","first-page":"1","article-title":"Systematic geolocation errors of FengYun-3D MERSI-II","volume":"60","author":"Pan","year":"2022","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"9829","DOI":"10.3390\/rs6109829","article-title":"Land surface temperature retrieval from Landsat 8 TIRS-comparison between radiative transfer equation-based method, split window algorithm and single channel method","volume":"6","author":"Yu","year":"2014","journal-title":"Remote Sens."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"3719","DOI":"10.1080\/01431160010006971","article-title":"A mono-window algorithm for retrieving land surface temperature from Landsat TM data and its application to the Israel-Egypt border region","volume":"22","author":"Qin","year":"2001","journal-title":"Int. J. Remote Sens."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Jimenez-Munoz, J.C., and Sobrino, J.A. (2003). A generalized single-channel method for retrieving land surface temperature from remote sensing data. J. Geophys. Res.-Atmos., 108.","DOI":"10.1029\/2003JD003480"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"486","DOI":"10.1016\/j.rse.2005.11.001","article-title":"In-situ measured spectral directional emissivity of snow and ice in the 8\u201314 \u03bcm atmospheric window","volume":"100","author":"Hori","year":"2006","journal-title":"Remote Sens. Environ."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"181","DOI":"10.1016\/j.rse.2017.09.006","article-title":"Retrieving snow and ice characteristics by remotely sensed emissivity using the multi-view brightness temperature within 8 \u03bcm to 14 \u03bcm","volume":"201","author":"Keck","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"7243","DOI":"10.1364\/AO.52.007243","article-title":"Modeling angular-dependent spectral emissivity of snow and ice in the thermal infrared atmospheric window","volume":"52","author":"Hori","year":"2013","journal-title":"Appl. Opt."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"5161","DOI":"10.1080\/0143116031000102502","article-title":"Surface temperature and water vapour retrieval from MODIS data","volume":"24","author":"Sobrino","year":"2003","journal-title":"Int. J. Remote Sens."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1007\/s00376-010-9170-8","article-title":"Intercomparison of humidity and temperature sensors: GTS1, Vaisala RS80, and CFH","volume":"28","author":"Bian","year":"2011","journal-title":"Adv. Atmos. Sci."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"710","DOI":"10.1016\/j.asr.2004.03.012","article-title":"Terra and Aqua MODIS products available from NASA GES DAAC","volume":"34","author":"Savtchenko","year":"2004","journal-title":"Adv. Space Res."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Zhou, L., Fan, L., and Shi, C. (2023). Evaluation and Analysis of Remotely Sensed Water Vapor from the NASA VIIRS\/SNPP Product in Mainland China Using GPS Data. Remote Sens., 15.","DOI":"10.3390\/rs15061528"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"871","DOI":"10.1109\/36.175321","article-title":"Remote sensing of water vapor in the near IR from EOS\/MODIS","volume":"30","author":"Kaufman","year":"1992","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"75","DOI":"10.1007\/s13131-013-0316-2","article-title":"FY-3A\/MERSI, ocean color algorithm, products and demonstrative applications","volume":"32","author":"Sun","year":"2013","journal-title":"Acta Oceanol. Sin."},{"key":"ref_33","first-page":"777","article-title":"TIGR-like atmospheric-profile databases for accurate radiative-flux computation","volume":"126","author":"Chevallier","year":"2000","journal-title":"Q. J. R. Meteorol. Soc."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"181","DOI":"10.1016\/j.atmosres.2019.04.005","article-title":"Global validation of columnar water vapor derived from EOS MODIS-MAIAC algorithm against the ground-based AERONET observations","volume":"225","author":"Martins","year":"2019","journal-title":"Atmos. Res."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"461","DOI":"10.1016\/j.atmosres.2017.07.021","article-title":"Evaluation of radiosonde, MODIS-NIR-Clear, and AERONET precipitable water vapor using IGS ground-based GPS measurements over China","volume":"197","author":"Gui","year":"2017","journal-title":"Atmos. Res."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"2019","DOI":"10.1002\/2014GL059356","article-title":"Sea ice mass balance observations from the North Pole Environmental Observatory","volume":"41","author":"Perovich","year":"2014","journal-title":"Geophys. Res. Lett."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"962","DOI":"10.1080\/17538947.2018.1545877","article-title":"Snow depth and ice thickness derived from SIMBA ice mass balance buoy data using an automated algorithm","volume":"8","author":"Liao","year":"2019","journal-title":"Int. J. Digit. Earth"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"345","DOI":"10.3189\/172756406781811457","article-title":"Validation of AVHRR and MODIS ice surface temperature products using in situ radiometers","volume":"44","author":"Scambos","year":"2006","journal-title":"Ann. Glaciol."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"2171","DOI":"10.1175\/JAMC-D-14-0023.1","article-title":"Comparison of near-surface air temperatures and MODIS ice-surface temperatures at Summit, Greenland (2008\u20132013)","volume":"53","author":"Shuman","year":"2014","journal-title":"J. Appl. Meteorol. Climatol."},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Song, L., Wu, Y., Gong, J., Fan, P., Zheng, X., and Zhao, X. (2023). Improvement of Ice Surface Temperature Retrieval by Integrating Landsat 8\/TIRS and Operation IceBridge Observations. Remote Sens., 15.","DOI":"10.3390\/rs15184577"},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Abbasi, B., Qin, Z., Du, W., Fan, J., Zhao, C., Hang, Q., Zhao, S., and Li, S. (2020). An Algorithm to Retrieve Total Precipitable Water Vapor in the Atmosphere from FengYun 3D Medium Resolution Spectral Imager 2 (FY-3D MERSI-2) Data. Remote Sens., 12.","DOI":"10.3390\/rs12213469"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1016\/0034-4257(91)90069-I","article-title":"Atmospheric correction for land surface temperature using NOAA-11 AVHRR channels 4 and 5","volume":"38","author":"Sobrino","year":"1991","journal-title":"Remote Sens. Environ."},{"key":"ref_43","first-page":"1972","article-title":"FY-3A multi-detector radiometric calibration for infrared band of medium resolution spectral imager","volume":"18","author":"Hu","year":"2010","journal-title":"Opt. Precis. Eng."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/16\/23\/4599\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T16:49:26Z","timestamp":1760114966000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/16\/23\/4599"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,12,7]]},"references-count":43,"journal-issue":{"issue":"23","published-online":{"date-parts":[[2024,12]]}},"alternative-id":["rs16234599"],"URL":"https:\/\/doi.org\/10.3390\/rs16234599","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,12,7]]}}}