{"title":"基于确定性预报模式评估 2018 年夏季黄海海洋热浪的可预测性","authors":"Haiqing Yu , Hui Wang , Chunxin Yuan , Qinwang Xing","doi":"10.1016/j.wace.2024.100663","DOIUrl":null,"url":null,"abstract":"<div><p>Understanding the predictability of marine heatwaves (MHWs) and identifying the sources of their forecast errors are essential for enhancing their forecast accuracy. In the summer of 2018, a powerful MHW struck the Yellow Sea, resulting in significant economic losses for the sea cucumber culture industry in China's coastal areas. However, the ability to predict the evolution of this MHW remains uncertain. In this study, several forecast experiments were conducted based on a deterministic ocean forecast model to address this issue. The results demonstrate that this MHW can be effectively predicted with a lead time of less than 3 days. Specifically, the mean MHW forecast accuracy is 0.66 and the mean absence/presence accuracy is 0.79 at a 3-day lead time. Beyond a 3-day lead time, the MHW forecast accuracy steadily decreases, which is primarily due to the overpredicted “False Alarms” during its growth and decay phases. The overpredicted “False Alarms” are largely attributed to uncertainties in predicting wind and air temperature related to two typhoons passing through the Yellow Sea. Additionally, anomalous ocean circulation induced by atmospheric forcing uncertainties may also trigger MHW forecast errors through advection. Future efforts involving parameter optimization, air-sea coupling, ensemble forecasts and integration with artificial intelligence-based weather forecasts are suggested to improve the prediction of MHWs. Our findings may provide implications for stakeholders in preparation for any future occurrences of MHWs in the Yellow Sea.</p></div>","PeriodicalId":48630,"journal":{"name":"Weather and Climate Extremes","volume":"44 ","pages":"Article 100663"},"PeriodicalIF":6.1000,"publicationDate":"2024-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2212094724000240/pdfft?md5=15d625e2a027b750d1eb837af0ae7bdc&pid=1-s2.0-S2212094724000240-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Assessing the predictability of the marine heatwave in the Yellow Sea during the summer of 2018 based on a deterministic forecast model\",\"authors\":\"Haiqing Yu , Hui Wang , Chunxin Yuan , Qinwang Xing\",\"doi\":\"10.1016/j.wace.2024.100663\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Understanding the predictability of marine heatwaves (MHWs) and identifying the sources of their forecast errors are essential for enhancing their forecast accuracy. In the summer of 2018, a powerful MHW struck the Yellow Sea, resulting in significant economic losses for the sea cucumber culture industry in China's coastal areas. However, the ability to predict the evolution of this MHW remains uncertain. In this study, several forecast experiments were conducted based on a deterministic ocean forecast model to address this issue. The results demonstrate that this MHW can be effectively predicted with a lead time of less than 3 days. Specifically, the mean MHW forecast accuracy is 0.66 and the mean absence/presence accuracy is 0.79 at a 3-day lead time. Beyond a 3-day lead time, the MHW forecast accuracy steadily decreases, which is primarily due to the overpredicted “False Alarms” during its growth and decay phases. The overpredicted “False Alarms” are largely attributed to uncertainties in predicting wind and air temperature related to two typhoons passing through the Yellow Sea. Additionally, anomalous ocean circulation induced by atmospheric forcing uncertainties may also trigger MHW forecast errors through advection. Future efforts involving parameter optimization, air-sea coupling, ensemble forecasts and integration with artificial intelligence-based weather forecasts are suggested to improve the prediction of MHWs. Our findings may provide implications for stakeholders in preparation for any future occurrences of MHWs in the Yellow Sea.</p></div>\",\"PeriodicalId\":48630,\"journal\":{\"name\":\"Weather and Climate Extremes\",\"volume\":\"44 \",\"pages\":\"Article 100663\"},\"PeriodicalIF\":6.1000,\"publicationDate\":\"2024-03-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S2212094724000240/pdfft?md5=15d625e2a027b750d1eb837af0ae7bdc&pid=1-s2.0-S2212094724000240-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Weather and Climate Extremes\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2212094724000240\",\"RegionNum\":1,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"METEOROLOGY & ATMOSPHERIC SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Weather and Climate Extremes","FirstCategoryId":"89","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2212094724000240","RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"METEOROLOGY & ATMOSPHERIC SCIENCES","Score":null,"Total":0}
Assessing the predictability of the marine heatwave in the Yellow Sea during the summer of 2018 based on a deterministic forecast model
Understanding the predictability of marine heatwaves (MHWs) and identifying the sources of their forecast errors are essential for enhancing their forecast accuracy. In the summer of 2018, a powerful MHW struck the Yellow Sea, resulting in significant economic losses for the sea cucumber culture industry in China's coastal areas. However, the ability to predict the evolution of this MHW remains uncertain. In this study, several forecast experiments were conducted based on a deterministic ocean forecast model to address this issue. The results demonstrate that this MHW can be effectively predicted with a lead time of less than 3 days. Specifically, the mean MHW forecast accuracy is 0.66 and the mean absence/presence accuracy is 0.79 at a 3-day lead time. Beyond a 3-day lead time, the MHW forecast accuracy steadily decreases, which is primarily due to the overpredicted “False Alarms” during its growth and decay phases. The overpredicted “False Alarms” are largely attributed to uncertainties in predicting wind and air temperature related to two typhoons passing through the Yellow Sea. Additionally, anomalous ocean circulation induced by atmospheric forcing uncertainties may also trigger MHW forecast errors through advection. Future efforts involving parameter optimization, air-sea coupling, ensemble forecasts and integration with artificial intelligence-based weather forecasts are suggested to improve the prediction of MHWs. Our findings may provide implications for stakeholders in preparation for any future occurrences of MHWs in the Yellow Sea.
期刊介绍:
Weather and Climate Extremes
Target Audience:
Academics
Decision makers
International development agencies
Non-governmental organizations (NGOs)
Civil society
Focus Areas:
Research in weather and climate extremes
Monitoring and early warning systems
Assessment of vulnerability and impacts
Developing and implementing intervention policies
Effective risk management and adaptation practices
Engagement of local communities in adopting coping strategies
Information and communication strategies tailored to local and regional needs and circumstances