Quality Assessment of FY-3D/MERSI-II Thermal Infrared Brightness Temperature Data from the Arctic Region: Application to Ice Surface Temperature Inversion
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...
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ftdoajarticles:oai:doaj.org/article:8fc334929c384aa09d0220643b3300ab 2023-05-15T14:52:25+02:00 Quality Assessment of FY-3D/MERSI-II Thermal Infrared Brightness Temperature Data from the Arctic Region: Application to Ice Surface Temperature Inversion Haihua Chen Xin Meng Lele Li Kun Ni 2022-12-01T00:00:00Z https://doi.org/10.3390/rs14246392 https://doaj.org/article/8fc334929c384aa09d0220643b3300ab EN eng MDPI AG https://www.mdpi.com/2072-4292/14/24/6392 https://doaj.org/toc/2072-4292 doi:10.3390/rs14246392 2072-4292 https://doaj.org/article/8fc334929c384aa09d0220643b3300ab Remote Sensing, Vol 14, Iss 6392, p 6392 (2022) MERSI MODIS brightness temperature quality assessment ice surface temperature Science Q article 2022 ftdoajarticles https://doi.org/10.3390/rs14246392 2022-12-30T19:30:26Z 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–Observation cross-calibration algorithm to cross-calibrate the MERSI and MODIS thermal infrared brightness temperature ( T b ) data in the Arctic, channel 24 and 25 data from the FY-3D/MERSI-II on Arctic ice were evaluated. The thermal infrared T b 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 T b data between the MERSI and MODIS were >0.95, the mean bias was −0.5501–0.1262 K, and the standard deviation (Std) was <1.3582 K. After linear fitting, the MERSI-II thermal infrared T b data were closer to the MODIS data, and the bias range of the 11 μm and 12 μm channels was −0.0214–0.0119 K and the Std was <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 T b 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 T b data with MODIS MYD29 product, the mean bias was −0.0612–0.0423 °C and the Std was <1.3988 °C. Using the MERSI thermal infrared T b 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 ... Article in Journal/Newspaper Arctic Arctic Ocean Directory of Open Access Journals: DOAJ Articles Arctic Arctic Ocean Remote Sensing 14 24 6392 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
MERSI MODIS brightness temperature quality assessment ice surface temperature Science Q |
spellingShingle |
MERSI MODIS brightness temperature quality assessment ice surface temperature Science Q Haihua Chen Xin Meng Lele Li Kun Ni Quality Assessment of FY-3D/MERSI-II Thermal Infrared Brightness Temperature Data from the Arctic Region: Application to Ice Surface Temperature Inversion |
topic_facet |
MERSI MODIS brightness temperature quality assessment ice surface temperature Science Q |
description |
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–Observation cross-calibration algorithm to cross-calibrate the MERSI and MODIS thermal infrared brightness temperature ( T b ) data in the Arctic, channel 24 and 25 data from the FY-3D/MERSI-II on Arctic ice were evaluated. The thermal infrared T b 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 T b data between the MERSI and MODIS were >0.95, the mean bias was −0.5501–0.1262 K, and the standard deviation (Std) was <1.3582 K. After linear fitting, the MERSI-II thermal infrared T b data were closer to the MODIS data, and the bias range of the 11 μm and 12 μm channels was −0.0214–0.0119 K and the Std was <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 T b 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 T b data with MODIS MYD29 product, the mean bias was −0.0612–0.0423 °C and the Std was <1.3988 °C. Using the MERSI thermal infrared T b 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 ... |
format |
Article in Journal/Newspaper |
author |
Haihua Chen Xin Meng Lele Li Kun Ni |
author_facet |
Haihua Chen Xin Meng Lele Li Kun Ni |
author_sort |
Haihua Chen |
title |
Quality Assessment of FY-3D/MERSI-II Thermal Infrared Brightness Temperature Data from the Arctic Region: Application to Ice Surface Temperature Inversion |
title_short |
Quality Assessment of FY-3D/MERSI-II Thermal Infrared Brightness Temperature Data from the Arctic Region: Application to Ice Surface Temperature Inversion |
title_full |
Quality Assessment of FY-3D/MERSI-II Thermal Infrared Brightness Temperature Data from the Arctic Region: Application to Ice Surface Temperature Inversion |
title_fullStr |
Quality Assessment of FY-3D/MERSI-II Thermal Infrared Brightness Temperature Data from the Arctic Region: Application to Ice Surface Temperature Inversion |
title_full_unstemmed |
Quality Assessment of FY-3D/MERSI-II Thermal Infrared Brightness Temperature Data from the Arctic Region: Application to Ice Surface Temperature Inversion |
title_sort |
quality assessment of fy-3d/mersi-ii thermal infrared brightness temperature data from the arctic region: application to ice surface temperature inversion |
publisher |
MDPI AG |
publishDate |
2022 |
url |
https://doi.org/10.3390/rs14246392 https://doaj.org/article/8fc334929c384aa09d0220643b3300ab |
geographic |
Arctic Arctic Ocean |
geographic_facet |
Arctic Arctic Ocean |
genre |
Arctic Arctic Ocean |
genre_facet |
Arctic Arctic Ocean |
op_source |
Remote Sensing, Vol 14, Iss 6392, p 6392 (2022) |
op_relation |
https://www.mdpi.com/2072-4292/14/24/6392 https://doaj.org/toc/2072-4292 doi:10.3390/rs14246392 2072-4292 https://doaj.org/article/8fc334929c384aa09d0220643b3300ab |
op_doi |
https://doi.org/10.3390/rs14246392 |
container_title |
Remote Sensing |
container_volume |
14 |
container_issue |
24 |
container_start_page |
6392 |
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1766323667582582784 |