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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Published in:Remote Sensing
Main Authors: Yachao Li, Tingting Liu, Zemin Wang, Mohammed Shokr, Menglin Yuan, Qiangqiang Yuan, Shiyu Wu
Format: Text
Language:English
Published: Multidisciplinary Digital Publishing Institute 2024
Subjects:
Online Access:https://doi.org/10.3390/rs16234599
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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 MDPI Open Access Publishing
container_issue 23
container_start_page 4599
container_title Remote Sensing
container_volume 16
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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genre Arctic
Sea ice
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Sea ice
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spelling ftmdpi:oai:mdpi.com:/2072-4292/16/23/4599/ 2025-01-16T20:26:40+00:00 Arctic Sea Ice Surface Temperature Retrieval from FengYun-3A MERSI-I Data Yachao Li Tingting Liu Zemin Wang Mohammed Shokr Menglin Yuan Qiangqiang Yuan Shiyu Wu agris 2024-12-07 application/pdf https://doi.org/10.3390/rs16234599 eng eng Multidisciplinary Digital Publishing Institute Remote Sensing for Geospatial Science https://dx.doi.org/10.3390/rs16234599 https://creativecommons.org/licenses/by/4.0/ Remote Sensing Volume 16 Issue 23 Pages: 4599 Arctic sea ice surface temperature thermal infrared remote sensing FengYun satellite Text 2024 ftmdpi https://doi.org/10.3390/rs16234599 2024-12-13T01:06:16Z 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. Text Arctic Sea ice MDPI Open Access Publishing Arctic Remote Sensing 16 23 4599
spellingShingle Arctic sea ice
surface temperature
thermal infrared remote sensing
FengYun satellite
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
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
topic_facet Arctic sea ice
surface temperature
thermal infrared remote sensing
FengYun satellite
url https://doi.org/10.3390/rs16234599