{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,29]],"date-time":"2026-07-29T18:25:56Z","timestamp":1785349556055,"version":"3.55.0"},"reference-count":58,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2023,3,28]],"date-time":"2023-03-28T00:00:00Z","timestamp":1679961600000},"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":["42075035"],"award-info":[{"award-number":["42075035"]}],"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":["42075011"],"award-info":[{"award-number":["42075011"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["www.mdpi.com"],"crossmark-restriction":true},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Tropical cyclones (TCs) seriously threaten the safety of human life and property especially when approaching a coast or making landfall. Robust, long-lead predictions are valuable for managing policy responses. However, despite decades of efforts, seasonal prediction of TCs remains a challenge. Here, we introduce a deep-learning prediction model to make skillful seasonal prediction of TC track density in the Western North Pacific (WNP) during the typhoon season, with a lead time of up to four months. To overcome the limited availability of observational data, we use TC tracks from CMIP5 and CMIP6 climate models as the training data, followed by a transfer-learning method to train a fully convolutional neural network named SeaUnet. Through the deep-learning process (i.e., heat map analysis), SeaUnet identifies physically based precursors. We show that SeaUnet has a good performance for typhoon distribution, outperforming state-of-the-art dynamic systems. The success of SeaUnet indicates its potential for operational use.<\/jats:p>","DOI":"10.3390\/rs15071797","type":"journal-article","created":{"date-parts":[[2023,3,28]],"date-time":"2023-03-28T04:37:15Z","timestamp":1679978235000},"page":"1797","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Skillful Seasonal Prediction of Typhoon Track Density Using Deep Learning"],"prefix":"10.3390","volume":"15","author":[{"given":"Zhihao","family":"Feng","sequence":"first","affiliation":[{"name":"College of Meteorology and Oceanography, National University of Defense Technology, Changsha 410000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shuo","family":"Lv","sequence":"additional","affiliation":[{"name":"College of Meteorology and Oceanography, National University of Defense Technology, Changsha 410000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuan","family":"Sun","sequence":"additional","affiliation":[{"name":"College of Advanced Interdisciplinary Studies, National University of Defense Technology, Nanjing 210000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1813-0159","authenticated-orcid":false,"given":"Panmao","family":"Zhai","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing 100000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yanluan","family":"Lin","sequence":"additional","affiliation":[{"name":"Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing 100000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yixuan","family":"Shen","sequence":"additional","affiliation":[{"name":"PLA Troop 32033, Haikou 570100, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wei","family":"Zhong","sequence":"additional","affiliation":[{"name":"College of Advanced Interdisciplinary Studies, National University of Defense Technology, Nanjing 210000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2023,3,28]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"3297","DOI":"10.1175\/JCLI-D-16-0888.1","article-title":"Variation of the tropical cyclone season start in the western north pacific","volume":"30","author":"Kim","year":"2017","journal-title":"J. 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Proceedings of the 2019 International Conference on Data Mining Workshops (ICDMW), Beijing, China.","DOI":"10.1109\/ICDMW.2019.00036"}],"updated-by":[{"DOI":"10.3390\/rs18122015","type":"correction","label":"Correction","source":"publisher","updated":{"date-parts":[[2023,3,28]],"date-time":"2023-03-28T00:00:00Z","timestamp":1679961600000}}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/7\/1797\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,6,17]],"date-time":"2026-06-17T08:45:50Z","timestamp":1781685950000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/7\/1797"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,3,28]]},"references-count":58,"journal-issue":{"issue":"7","published-online":{"date-parts":[[2023,4]]}},"alternative-id":["rs15071797"],"URL":"https:\/\/doi.org\/10.3390\/rs15071797","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,3,28]]}}}