Reconstructing tropical monthly sea surface temperature variability by assimilating coral proxy datasets
Abstract Coral reconstruction often serves as a major proxy of high-resolution sea surface temperature (SST) variability beyond the instrumental era. However, coral reconstructions are sparse and are usually studied for interannual variability, with few studies on the monthly features. In this study...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2024-10-01
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| Series: | npj Climate and Atmospheric Science |
| Online Access: | https://doi.org/10.1038/s41612-024-00816-w |
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| author | Wenqing Hu Liang Ning Zhengyu Liu Jian Liu Fen Wu Mi Yan Leilei Jiang Lili Lei Fangmiao Xing Haohao Sun Kefan Chen Yanmin Qin Weiyi Sun Qin Wen Benyue Li |
| author_facet | Wenqing Hu Liang Ning Zhengyu Liu Jian Liu Fen Wu Mi Yan Leilei Jiang Lili Lei Fangmiao Xing Haohao Sun Kefan Chen Yanmin Qin Weiyi Sun Qin Wen Benyue Li |
| author_sort | Wenqing Hu |
| collection | DOAJ |
| description | Abstract Coral reconstruction often serves as a major proxy of high-resolution sea surface temperature (SST) variability beyond the instrumental era. However, coral reconstructions are sparse and are usually studied for interannual variability, with few studies on the monthly features. In this study, we reconstruct the monthly SST spatial field by applying the paleoclimate data assimilation method to the coral records of the latest CoralHydro2k data set for the instrument period of 1880–2000. A comparison with observed SST variability shows that our assimilated tropical SST variability performs reasonably well for the seasonal cycle and monthly ENSO characteristics, notably the phase-locking and onset timing, and more realistic spatial fields relative to the model simulations. This study suggests the feasibility of applying paleoclimate data assimilation to reconstruct the monthly SST in the historical period. |
| format | Article |
| id | doaj-art-01c38862e68b4debb980b2e01776cb46 |
| institution | OA Journals |
| issn | 2397-3722 |
| language | English |
| publishDate | 2024-10-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | npj Climate and Atmospheric Science |
| spelling | doaj-art-01c38862e68b4debb980b2e01776cb462025-08-20T02:18:24ZengNature Portfolionpj Climate and Atmospheric Science2397-37222024-10-017111010.1038/s41612-024-00816-wReconstructing tropical monthly sea surface temperature variability by assimilating coral proxy datasetsWenqing Hu0Liang Ning1Zhengyu Liu2Jian Liu3Fen Wu4Mi Yan5Leilei Jiang6Lili Lei7Fangmiao Xing8Haohao Sun9Kefan Chen10Yanmin Qin11Weiyi Sun12Qin Wen13Benyue Li14Key Laboratory for Virtual Geographic Environment, Ministry of Education; State Key Laboratory Cultivation Base of Geographical Environment Evolution of Jiangsu Province; Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application; School of Geography, Nanjing Normal UniversityKey Laboratory for Virtual Geographic Environment, Ministry of Education; State Key Laboratory Cultivation Base of Geographical Environment Evolution of Jiangsu Province; Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application; School of Geography, Nanjing Normal UniversityDepartment of Geography, Ohio State UniversityKey Laboratory for Virtual Geographic Environment, Ministry of Education; State Key Laboratory Cultivation Base of Geographical Environment Evolution of Jiangsu Province; Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application; School of Geography, Nanjing Normal UniversityKey Laboratory for Virtual Geographic Environment, Ministry of Education; State Key Laboratory Cultivation Base of Geographical Environment Evolution of Jiangsu Province; Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application; School of Geography, Nanjing Normal UniversityKey Laboratory for Virtual Geographic Environment, Ministry of Education; State Key Laboratory Cultivation Base of Geographical Environment Evolution of Jiangsu Province; Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application; School of Geography, Nanjing Normal UniversityGuangxi Laboratory on the Study of Coral Reefs in the South China Sea, Coral Reef Research Centre of China, School of Marine Sciences, Guangxi UniversityKey Laboratory of Mesoscale Severe Weather, Ministry of Education, and School of Atmospheric Sciences, Nanjing UniversityKey Laboratory for Virtual Geographic Environment, Ministry of Education; State Key Laboratory Cultivation Base of Geographical Environment Evolution of Jiangsu Province; Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application; School of Geography, Nanjing Normal UniversityKey Laboratory of Mesoscale Severe Weather, Ministry of Education, and School of Atmospheric Sciences, Nanjing UniversityKey Laboratory for Virtual Geographic Environment, Ministry of Education; State Key Laboratory Cultivation Base of Geographical Environment Evolution of Jiangsu Province; Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application; School of Geography, Nanjing Normal UniversityKey Laboratory for Virtual Geographic Environment, Ministry of Education; State Key Laboratory Cultivation Base of Geographical Environment Evolution of Jiangsu Province; Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application; School of Geography, Nanjing Normal UniversityKey Laboratory for Virtual Geographic Environment, Ministry of Education; State Key Laboratory Cultivation Base of Geographical Environment Evolution of Jiangsu Province; Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application; School of Geography, Nanjing Normal UniversityKey Laboratory for Virtual Geographic Environment, Ministry of Education; State Key Laboratory Cultivation Base of Geographical Environment Evolution of Jiangsu Province; Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application; School of Geography, Nanjing Normal UniversityKey Laboratory for Virtual Geographic Environment, Ministry of Education; State Key Laboratory Cultivation Base of Geographical Environment Evolution of Jiangsu Province; Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application; School of Geography, Nanjing Normal UniversityAbstract Coral reconstruction often serves as a major proxy of high-resolution sea surface temperature (SST) variability beyond the instrumental era. However, coral reconstructions are sparse and are usually studied for interannual variability, with few studies on the monthly features. In this study, we reconstruct the monthly SST spatial field by applying the paleoclimate data assimilation method to the coral records of the latest CoralHydro2k data set for the instrument period of 1880–2000. A comparison with observed SST variability shows that our assimilated tropical SST variability performs reasonably well for the seasonal cycle and monthly ENSO characteristics, notably the phase-locking and onset timing, and more realistic spatial fields relative to the model simulations. This study suggests the feasibility of applying paleoclimate data assimilation to reconstruct the monthly SST in the historical period.https://doi.org/10.1038/s41612-024-00816-w |
| spellingShingle | Wenqing Hu Liang Ning Zhengyu Liu Jian Liu Fen Wu Mi Yan Leilei Jiang Lili Lei Fangmiao Xing Haohao Sun Kefan Chen Yanmin Qin Weiyi Sun Qin Wen Benyue Li Reconstructing tropical monthly sea surface temperature variability by assimilating coral proxy datasets npj Climate and Atmospheric Science |
| title | Reconstructing tropical monthly sea surface temperature variability by assimilating coral proxy datasets |
| title_full | Reconstructing tropical monthly sea surface temperature variability by assimilating coral proxy datasets |
| title_fullStr | Reconstructing tropical monthly sea surface temperature variability by assimilating coral proxy datasets |
| title_full_unstemmed | Reconstructing tropical monthly sea surface temperature variability by assimilating coral proxy datasets |
| title_short | Reconstructing tropical monthly sea surface temperature variability by assimilating coral proxy datasets |
| title_sort | reconstructing tropical monthly sea surface temperature variability by assimilating coral proxy datasets |
| url | https://doi.org/10.1038/s41612-024-00816-w |
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