{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,27]],"date-time":"2026-03-27T16:00:35Z","timestamp":1774627235755,"version":"3.50.1"},"reference-count":38,"publisher":"MDPI AG","issue":"20","license":[{"start":{"date-parts":[[2024,10,12]],"date-time":"2024-10-12T00:00:00Z","timestamp":1728691200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["42227901"],"award-info":[{"award-number":["42227901"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62261160387"],"award-info":[{"award-number":["62261160387"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"National Natural Science Foundation of China (NSFC) and Research Grants Council (RGC) of Hong Kong Joint Research Scheme","award":["42227901"],"award-info":[{"award-number":["42227901"]}]},{"name":"National Natural Science Foundation of China (NSFC) and Research Grants Council (RGC) of Hong Kong Joint Research Scheme","award":["62261160387"],"award-info":[{"award-number":["62261160387"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Numerical weather prediction of sea surface temperature (SST) is crucial for regional operational forecasts. Deep learning offers an alternative approach to traditional numerical general circulation models for numerical weather prediction. In our previous work, we developed a sophisticated deep learning model known as the Attention-based Context Fusion Network (ACFN). This model integrates an attention mechanism with a convolutional neural network framework. In this study, we applied the ACFN model to the South China Sea to evaluate its performance in predicting SST. The results indicate that for a 1-day lead time, the ACFN model achieves a Mean Absolute Error of 0.215 \u00b0C and a coefficient of determination (R2) of 0.972. In addition, in situ buoy data were utilized to validate the forecast results. The Mean Absolute Error for forecasts using these data increased to 0.500 \u00b0C for a 1-day lead time, with a corresponding R2 of 0.590. Comparative analyses show that the ACFN model surpasses traditional models such as ConvLSTM and PredRNN in terms of accuracy and reliability.<\/jats:p>","DOI":"10.3390\/rs16203793","type":"journal-article","created":{"date-parts":[[2024,10,14]],"date-time":"2024-10-14T07:47:05Z","timestamp":1728892025000},"page":"3793","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Numerical Weather Prediction of Sea Surface Temperature in South China Sea Using Attention-Based Context Fusion Network"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0690-6252","authenticated-orcid":false,"given":"Hailun","family":"He","sequence":"first","affiliation":[{"name":"State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography, Ministry of Natural Resources, Hangzhou 310012, China"},{"name":"Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519082, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2734-3794","authenticated-orcid":false,"given":"Benyun","family":"Shi","sequence":"additional","affiliation":[{"name":"College of Computer and Information Engineering (College of Artificial Intelligence), Nanjing Tech University, Nanjing 211816, China"}]},{"given":"Yuting","family":"Zhu","sequence":"additional","affiliation":[{"name":"College of Computer and Information Engineering (College of Artificial Intelligence), Nanjing Tech University, Nanjing 211816, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-6368-6137","authenticated-orcid":false,"given":"Liu","family":"Feng","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Hong Kong Baptist University, Hong Kong, China"}]},{"given":"Conghui","family":"Ge","sequence":"additional","affiliation":[{"name":"College of Computer and Information Engineering (College of Artificial Intelligence), Nanjing Tech University, Nanjing 211816, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0831-7999","authenticated-orcid":false,"given":"Qi","family":"Tan","sequence":"additional","affiliation":[{"name":"College of Computer and Information Engineering (College of Artificial Intelligence), Nanjing Tech University, Nanjing 211816, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-7857-2221","authenticated-orcid":false,"given":"Yue","family":"Peng","sequence":"additional","affiliation":[{"name":"College of Computer and Information Engineering (College of Artificial Intelligence), Nanjing Tech University, Nanjing 211816, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0166-3944","authenticated-orcid":false,"given":"Yang","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Hong Kong Baptist University, Hong Kong, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9541-2064","authenticated-orcid":false,"given":"Zheng","family":"Ling","sequence":"additional","affiliation":[{"name":"Key Laboratory of Climate, Resources and Environment in Continental Shelf Sea and Deep Sea of Department of Education of Guangdong Province, College of Ocean and Meteorology, Guangdong Ocean University, Zhanjiang 524088, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7331-7610","authenticated-orcid":false,"given":"Shuang","family":"Li","sequence":"additional","affiliation":[{"name":"Institute of Physical Oceanography and Remote Sensing, Ocean College, Zhejiang University, Zhoushan 316021, China"}]}],"member":"1968","published-online":{"date-parts":[[2024,10,12]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"6833","DOI":"10.1175\/JCLI-D-19-0957.1","article-title":"Strengthened relationship between Tropical West Pacific and midsummer precipitation over Northeast China after the mid-1990s","volume":"33","author":"Han","year":"2020","journal-title":"J. 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