Arctic Sea Ice Surface Temperature Retrieval from FengYun-3A MERSI-I Data

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-s...

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Main Authors: Yachao Li, Tingting Liu, Zemin Wang, Mohammed Shokr, Menglin Yuan, Qiangqiang Yuan, Shiyu Wu
Format: Article
Language:English
Published: MDPI AG 2024-12-01
Series:Remote Sensing
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Online Access:https://www.mdpi.com/2072-4292/16/23/4599
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author Yachao Li
Tingting Liu
Zemin Wang
Mohammed Shokr
Menglin Yuan
Qiangqiang Yuan
Shiyu Wu
author_facet Yachao Li
Tingting Liu
Zemin Wang
Mohammed Shokr
Menglin Yuan
Qiangqiang Yuan
Shiyu Wu
author_sort Yachao Li
collection DOAJ
description 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 −1.928 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.
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publishDate 2024-12-01
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spelling doaj-art-7e05fa9e9bcb40668f1e2e1af22b50f42024-12-13T16:31:23ZengMDPI AGRemote Sensing2072-42922024-12-011623459910.3390/rs16234599Arctic Sea Ice Surface Temperature Retrieval from FengYun-3A MERSI-I DataYachao Li0Tingting Liu1Zemin Wang2Mohammed Shokr3Menglin Yuan4Qiangqiang Yuan5Shiyu Wu6Chinese Antarctic Center of Surveying and Mapping, Wuhan University, Wuhan 430070, ChinaChinese Antarctic Center of Surveying and Mapping, Wuhan University, Wuhan 430070, ChinaChinese Antarctic Center of Surveying and Mapping, Wuhan University, Wuhan 430070, ChinaMeteorological Research Branch, Environment and Climate Change Canada, Toronto, ON M3H5T4, CanadaChinese Antarctic Center of Surveying and Mapping, Wuhan University, Wuhan 430070, ChinaKey Laboratory of Polar Environment Monitoring and Public Governance, Ministry of Education, Wuhan 430079, ChinaChinese Antarctic Center of Surveying and Mapping, Wuhan University, Wuhan 430070, ChinaArctic 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 −1.928 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.https://www.mdpi.com/2072-4292/16/23/4599Arctic sea icesurface temperaturethermal infrared remote sensingFengYun satellite
spellingShingle Yachao Li
Tingting Liu
Zemin Wang
Mohammed Shokr
Menglin Yuan
Qiangqiang Yuan
Shiyu Wu
Arctic Sea Ice Surface Temperature Retrieval from FengYun-3A MERSI-I Data
Remote Sensing
Arctic sea ice
surface temperature
thermal infrared remote sensing
FengYun satellite
title Arctic Sea Ice Surface Temperature Retrieval from FengYun-3A MERSI-I Data
title_full Arctic Sea Ice Surface Temperature Retrieval from FengYun-3A MERSI-I Data
title_fullStr Arctic Sea Ice Surface Temperature Retrieval from FengYun-3A MERSI-I Data
title_full_unstemmed Arctic Sea Ice Surface Temperature Retrieval from FengYun-3A MERSI-I Data
title_short Arctic Sea Ice Surface Temperature Retrieval from FengYun-3A MERSI-I Data
title_sort arctic sea ice surface temperature retrieval from fengyun 3a mersi i data
topic Arctic sea ice
surface temperature
thermal infrared remote sensing
FengYun satellite
url https://www.mdpi.com/2072-4292/16/23/4599
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