{"title":"利用季节预报模式对北太平洋西部大气河流的季节预报","authors":"Yuya Baba","doi":"10.1002/asl.1299","DOIUrl":null,"url":null,"abstract":"<p>Seasonal prediction of atmospheric rivers (ARs) in the western north Pacific (WNP) is examined using a seasonal prediction model with and without atmospheric initialisation. A 20-year seasonal prediction was conducted to evaluate the model's prediction skill, particularly focusing over the Japan area. The prediction skill of the present model indicated that the seasonal AR frequency is predictable with a lead time of up to 7–10 months, and the atmospheric initialisation further improved the skill. An additional investigation was conducted to identify the source of predictability for seasonal ARs. One significant source is the predictability of the Pacific-Japan (PJ) pattern, which is influenced by the model's skill in predicting tropical sea surface temperature (SST) variability. The anticyclonic circulation southeast of Japan is well predicted when the tropical SST variability and PJ pattern are accurately predicted. Another source of predictability difference originated from the subsurface sea temperature (SBT) beneath the subtropical high in the North Pacific. When the SBT prediction is improved with atmospheric initialisation, it enhances the air-sea interactions over the subtropical high in the WNP and southeast of Japan, leading to better predictability of seasonal ARs.</p>","PeriodicalId":50734,"journal":{"name":"Atmospheric Science Letters","volume":"26 5","pages":""},"PeriodicalIF":2.0000,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/asl.1299","citationCount":"0","resultStr":"{\"title\":\"Seasonal Prediction of Atmospheric Rivers in the Western North Pacific Using a Seasonal Prediction Model\",\"authors\":\"Yuya Baba\",\"doi\":\"10.1002/asl.1299\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Seasonal prediction of atmospheric rivers (ARs) in the western north Pacific (WNP) is examined using a seasonal prediction model with and without atmospheric initialisation. A 20-year seasonal prediction was conducted to evaluate the model's prediction skill, particularly focusing over the Japan area. The prediction skill of the present model indicated that the seasonal AR frequency is predictable with a lead time of up to 7–10 months, and the atmospheric initialisation further improved the skill. An additional investigation was conducted to identify the source of predictability for seasonal ARs. One significant source is the predictability of the Pacific-Japan (PJ) pattern, which is influenced by the model's skill in predicting tropical sea surface temperature (SST) variability. The anticyclonic circulation southeast of Japan is well predicted when the tropical SST variability and PJ pattern are accurately predicted. Another source of predictability difference originated from the subsurface sea temperature (SBT) beneath the subtropical high in the North Pacific. When the SBT prediction is improved with atmospheric initialisation, it enhances the air-sea interactions over the subtropical high in the WNP and southeast of Japan, leading to better predictability of seasonal ARs.</p>\",\"PeriodicalId\":50734,\"journal\":{\"name\":\"Atmospheric Science Letters\",\"volume\":\"26 5\",\"pages\":\"\"},\"PeriodicalIF\":2.0000,\"publicationDate\":\"2025-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1002/asl.1299\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Atmospheric Science Letters\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/asl.1299\",\"RegionNum\":4,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"METEOROLOGY & ATMOSPHERIC SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Atmospheric Science Letters","FirstCategoryId":"89","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/asl.1299","RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"METEOROLOGY & ATMOSPHERIC SCIENCES","Score":null,"Total":0}
Seasonal Prediction of Atmospheric Rivers in the Western North Pacific Using a Seasonal Prediction Model
Seasonal prediction of atmospheric rivers (ARs) in the western north Pacific (WNP) is examined using a seasonal prediction model with and without atmospheric initialisation. A 20-year seasonal prediction was conducted to evaluate the model's prediction skill, particularly focusing over the Japan area. The prediction skill of the present model indicated that the seasonal AR frequency is predictable with a lead time of up to 7–10 months, and the atmospheric initialisation further improved the skill. An additional investigation was conducted to identify the source of predictability for seasonal ARs. One significant source is the predictability of the Pacific-Japan (PJ) pattern, which is influenced by the model's skill in predicting tropical sea surface temperature (SST) variability. The anticyclonic circulation southeast of Japan is well predicted when the tropical SST variability and PJ pattern are accurately predicted. Another source of predictability difference originated from the subsurface sea temperature (SBT) beneath the subtropical high in the North Pacific. When the SBT prediction is improved with atmospheric initialisation, it enhances the air-sea interactions over the subtropical high in the WNP and southeast of Japan, leading to better predictability of seasonal ARs.
期刊介绍:
Atmospheric Science Letters (ASL) is a wholly Open Access electronic journal. Its aim is to provide a fully peer reviewed publication route for new shorter contributions in the field of atmospheric and closely related sciences. Through its ability to publish shorter contributions more rapidly than conventional journals, ASL offers a framework that promotes new understanding and creates scientific debate - providing a platform for discussing scientific issues and techniques.
We encourage the presentation of multi-disciplinary work and contributions that utilise ideas and techniques from parallel areas. We particularly welcome contributions that maximise the visualisation capabilities offered by a purely on-line journal. ASL welcomes papers in the fields of: Dynamical meteorology; Ocean-atmosphere systems; Climate change, variability and impacts; New or improved observations from instrumentation; Hydrometeorology; Numerical weather prediction; Data assimilation and ensemble forecasting; Physical processes of the atmosphere; Land surface-atmosphere systems.