Sea Ice Concentration Products over Polar Regions with Chinese FY3C/MWRI Data
Polar sea ice affects atmospheric and ocean circulation and plays an important role in global climate change. Long time series sea ice concentrations (SIC) are an important parameter for climate research. This study presents an SIC retrieval algorithm based on brightness temperature (Tb) data from t...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-06-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/13/11/2174 |
| _version_ | 1797531645609246720 |
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| author | Lijian Shi Sen Liu Yingni Shi Xue Ao Bin Zou Qimao Wang |
| author_facet | Lijian Shi Sen Liu Yingni Shi Xue Ao Bin Zou Qimao Wang |
| author_sort | Lijian Shi |
| collection | DOAJ |
| description | Polar sea ice affects atmospheric and ocean circulation and plays an important role in global climate change. Long time series sea ice concentrations (SIC) are an important parameter for climate research. This study presents an SIC retrieval algorithm based on brightness temperature (Tb) data from the FY3C Microwave Radiation Imager (MWRI) over the polar region. With the Tb data of Special Sensor Microwave Imager/Sounder (SSMIS) as a reference, monthly calibration models were established based on time–space matching and linear regression. After calibration, the correlation between the Tb of F17/SSMIS and FY3C/MWRI at different channels was improved. Then, SIC products over the Arctic and Antarctic in 2016–2019 were retrieved with the NASA team (NT) method. Atmospheric effects were reduced using two weather filters and a sea ice mask. A minimum ice concentration array used in the procedure reduced the land-to-ocean spillover effect. Compared with the SIC product of National Snow and Ice Data Center (NSIDC), the average relative difference of sea ice extent of the Arctic and Antarctic was found to be acceptable, with values of −0.27 ± 1.85 and 0.53 ± 1.50, respectively. To decrease the SIC error with fixed tie points (FTPs), the SIC was retrieved by the NT method with dynamic tie points (DTPs) based on the original Tb of FY3C/MWRI. The different SIC products were evaluated with ship observation data, synthetic aperture radar (SAR) sea ice cover products, and the Round Robin Data Package (RRDP). In comparison with the ship observation data, the SIC bias of FY3C with DTP is 4% and is much better than that of FY3C with FTP (9%). Evaluation results with SAR SIC data and closed ice data from RRDP show a similar trend between FY3C SIC with FTPs and FY3C SIC with DTPs. Using DTPs to present the Tb seasonal change of different types of sea ice improved the SIC accuracy, especially for the sea ice melting season. This study lays a foundation for the release of long time series operational SIC products with Chinese FY3 series satellites. |
| first_indexed | 2024-03-10T10:46:40Z |
| format | Article |
| id | doaj.art-37ffab94228d4a8687a1eb93c30d0641 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-10T10:46:40Z |
| publishDate | 2021-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-37ffab94228d4a8687a1eb93c30d06412023-11-21T22:30:53ZengMDPI AGRemote Sensing2072-42922021-06-011311217410.3390/rs13112174Sea Ice Concentration Products over Polar Regions with Chinese FY3C/MWRI DataLijian Shi0Sen Liu1Yingni Shi2Xue Ao3Bin Zou4Qimao Wang5National Satellite Ocean Application Service, Beijing 100081, ChinaNational Satellite Ocean Application Service, Beijing 100081, ChinaIndependent Researcher, Mailbox No. 5111, Beijing 100094, ChinaNational Satellite Ocean Application Service, Beijing 100081, ChinaNational Satellite Ocean Application Service, Beijing 100081, ChinaNational Satellite Ocean Application Service, Beijing 100081, ChinaPolar sea ice affects atmospheric and ocean circulation and plays an important role in global climate change. Long time series sea ice concentrations (SIC) are an important parameter for climate research. This study presents an SIC retrieval algorithm based on brightness temperature (Tb) data from the FY3C Microwave Radiation Imager (MWRI) over the polar region. With the Tb data of Special Sensor Microwave Imager/Sounder (SSMIS) as a reference, monthly calibration models were established based on time–space matching and linear regression. After calibration, the correlation between the Tb of F17/SSMIS and FY3C/MWRI at different channels was improved. Then, SIC products over the Arctic and Antarctic in 2016–2019 were retrieved with the NASA team (NT) method. Atmospheric effects were reduced using two weather filters and a sea ice mask. A minimum ice concentration array used in the procedure reduced the land-to-ocean spillover effect. Compared with the SIC product of National Snow and Ice Data Center (NSIDC), the average relative difference of sea ice extent of the Arctic and Antarctic was found to be acceptable, with values of −0.27 ± 1.85 and 0.53 ± 1.50, respectively. To decrease the SIC error with fixed tie points (FTPs), the SIC was retrieved by the NT method with dynamic tie points (DTPs) based on the original Tb of FY3C/MWRI. The different SIC products were evaluated with ship observation data, synthetic aperture radar (SAR) sea ice cover products, and the Round Robin Data Package (RRDP). In comparison with the ship observation data, the SIC bias of FY3C with DTP is 4% and is much better than that of FY3C with FTP (9%). Evaluation results with SAR SIC data and closed ice data from RRDP show a similar trend between FY3C SIC with FTPs and FY3C SIC with DTPs. Using DTPs to present the Tb seasonal change of different types of sea ice improved the SIC accuracy, especially for the sea ice melting season. This study lays a foundation for the release of long time series operational SIC products with Chinese FY3 series satellites.https://www.mdpi.com/2072-4292/13/11/2174sea ice concentrationFY3Cintersensor calibrationArcticAntarctic |
| spellingShingle | Lijian Shi Sen Liu Yingni Shi Xue Ao Bin Zou Qimao Wang Sea Ice Concentration Products over Polar Regions with Chinese FY3C/MWRI Data Remote Sensing sea ice concentration FY3C intersensor calibration Arctic Antarctic |
| title | Sea Ice Concentration Products over Polar Regions with Chinese FY3C/MWRI Data |
| title_full | Sea Ice Concentration Products over Polar Regions with Chinese FY3C/MWRI Data |
| title_fullStr | Sea Ice Concentration Products over Polar Regions with Chinese FY3C/MWRI Data |
| title_full_unstemmed | Sea Ice Concentration Products over Polar Regions with Chinese FY3C/MWRI Data |
| title_short | Sea Ice Concentration Products over Polar Regions with Chinese FY3C/MWRI Data |
| title_sort | sea ice concentration products over polar regions with chinese fy3c mwri data |
| topic | sea ice concentration FY3C intersensor calibration Arctic Antarctic |
| url | https://www.mdpi.com/2072-4292/13/11/2174 |
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