Influence of Melt Ponds on the SSMIS-Based Summer Sea Ice Concentrations in the Arctic
As a long-term, near real-time, and widely used satellite derived product, the summer performance of the Special Sensor Microwave Imager/Sounder (SSMIS)-based sea ice concentration (SIC) is commonly doubted when extensive melt ponds exist on the ice surface. In this study, three SSMIS-based SIC prod...
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MDPI AG
2021-09-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/13/19/3882 |
| _version_ | 1827680591959556096 |
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| author | Jiechen Zhao Yining Yu Jingjing Cheng Honglin Guo Chunhua Li Qi Shu |
| author_facet | Jiechen Zhao Yining Yu Jingjing Cheng Honglin Guo Chunhua Li Qi Shu |
| author_sort | Jiechen Zhao |
| collection | DOAJ |
| description | As a long-term, near real-time, and widely used satellite derived product, the summer performance of the Special Sensor Microwave Imager/Sounder (SSMIS)-based sea ice concentration (SIC) is commonly doubted when extensive melt ponds exist on the ice surface. In this study, three SSMIS-based SIC products were assessed using ship-based SIC and melt pond fraction (MPF) observations from 60 Arctic cruises conducted by the Ice Watch Program and the Chinese Icebreaker Xuelong I/II. The results indicate that the product using the NASA Team (SSMIS-NT) algorithm and the product released by the Ocean and Sea Ice Satellite Application Facility (SSMIS-OS) underestimated the SIC by 15% and 7–9%, respectively, which mainly occurred in the high concentration rages, such as 80–100%, while the product using the Bootstrap (SSMIS-BT) algorithm overestimated the SIC by 3–4%, usually misestimating 80% < SIC < 100% as 100%. The MPF affected the SIC biases. For the high MPF case (e.g., 50%), the estimated biases for the three products increased to 20% (SSMIS-NT), 7% (SSMIS-BT), and 20% (SSMIS-OS) due to the influence of MPF. The relationship between the SIC biases and the MPF observations established in this study was demonstrated to greatly improve the accuracy of the 2D SIC distributions, which are useful references for model assimilation, algorithm improvement, and error analysis. |
| first_indexed | 2024-03-10T06:52:47Z |
| format | Article |
| id | doaj.art-22d49503cf2f4ebea77ac7b9cdc4c198 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-10T06:52:47Z |
| publishDate | 2021-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-22d49503cf2f4ebea77ac7b9cdc4c1982023-11-22T16:42:22ZengMDPI AGRemote Sensing2072-42922021-09-011319388210.3390/rs13193882Influence of Melt Ponds on the SSMIS-Based Summer Sea Ice Concentrations in the ArcticJiechen Zhao0Yining Yu1Jingjing Cheng2Honglin Guo3Chunhua Li4Qi Shu5National Marine Environmental Forecasting Centre (NMEFC), Key Laboratory of Marine Hazards Forecasting, Ministry of Natural Resources, Beijing 100081, ChinaSchool of Geospatial Engineering and Science, Sun Yat-sen University, Zhuhai 519082, ChinaEditorial Office for Professional Publications, China Ocean Press, Beijing 100081, ChinaNational Marine Environmental Forecasting Centre (NMEFC), Key Laboratory of Marine Hazards Forecasting, Ministry of Natural Resources, Beijing 100081, ChinaNational Marine Environmental Forecasting Centre (NMEFC), Key Laboratory of Marine Hazards Forecasting, Ministry of Natural Resources, Beijing 100081, ChinaLaboratory for Regional Oceanography and Numerical Modeling, Pilot National Laboratory for Marine Science and Technology (Qingdao), Qingdao 266237, ChinaAs a long-term, near real-time, and widely used satellite derived product, the summer performance of the Special Sensor Microwave Imager/Sounder (SSMIS)-based sea ice concentration (SIC) is commonly doubted when extensive melt ponds exist on the ice surface. In this study, three SSMIS-based SIC products were assessed using ship-based SIC and melt pond fraction (MPF) observations from 60 Arctic cruises conducted by the Ice Watch Program and the Chinese Icebreaker Xuelong I/II. The results indicate that the product using the NASA Team (SSMIS-NT) algorithm and the product released by the Ocean and Sea Ice Satellite Application Facility (SSMIS-OS) underestimated the SIC by 15% and 7–9%, respectively, which mainly occurred in the high concentration rages, such as 80–100%, while the product using the Bootstrap (SSMIS-BT) algorithm overestimated the SIC by 3–4%, usually misestimating 80% < SIC < 100% as 100%. The MPF affected the SIC biases. For the high MPF case (e.g., 50%), the estimated biases for the three products increased to 20% (SSMIS-NT), 7% (SSMIS-BT), and 20% (SSMIS-OS) due to the influence of MPF. The relationship between the SIC biases and the MPF observations established in this study was demonstrated to greatly improve the accuracy of the 2D SIC distributions, which are useful references for model assimilation, algorithm improvement, and error analysis.https://www.mdpi.com/2072-4292/13/19/3882sea ice concentrationmelt pond fractionSSMISarctic |
| spellingShingle | Jiechen Zhao Yining Yu Jingjing Cheng Honglin Guo Chunhua Li Qi Shu Influence of Melt Ponds on the SSMIS-Based Summer Sea Ice Concentrations in the Arctic Remote Sensing sea ice concentration melt pond fraction SSMIS arctic |
| title | Influence of Melt Ponds on the SSMIS-Based Summer Sea Ice Concentrations in the Arctic |
| title_full | Influence of Melt Ponds on the SSMIS-Based Summer Sea Ice Concentrations in the Arctic |
| title_fullStr | Influence of Melt Ponds on the SSMIS-Based Summer Sea Ice Concentrations in the Arctic |
| title_full_unstemmed | Influence of Melt Ponds on the SSMIS-Based Summer Sea Ice Concentrations in the Arctic |
| title_short | Influence of Melt Ponds on the SSMIS-Based Summer Sea Ice Concentrations in the Arctic |
| title_sort | influence of melt ponds on the ssmis based summer sea ice concentrations in the arctic |
| topic | sea ice concentration melt pond fraction SSMIS arctic |
| url | https://www.mdpi.com/2072-4292/13/19/3882 |
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