{"title":"改进冬季NAO分季节预测的潜力是什么?","authors":"Chris Kent, Adam A. Scaife, Nick Dunstone","doi":"10.1002/asl.1146","DOIUrl":null,"url":null,"abstract":"The North Atlantic Oscillation (NAO) is the leading mode of variability across the Atlantic sector and is a key metric of extratropical forecast performance. Skilful predictions of the NAO are possible at medium‐range (1–2 weeks) and seasonal time scales. However, in a leading dynamical prediction system, we find that sub‐seasonal predictions (1 month NAO with a lead time of 20–30 days) are not statistically significant and represent a gap in forecast skill. In this study, we have investigated the potential for improving predictions using a large ensemble of dynamical hindcasts. First, we find that monthly predictions of the NAO are only weakly related to forecast errors at the medium‐range. This implies that improving medium‐range forecast performance is unlikely to drive significant improvements at longer lead times. Second, the Madden‐Julian Oscillation (MJO) is the leading mode of sub‐seasonal variability in the Tropics and projects onto the NAO with a lag of 10–15 days, but its teleconnection is only partially represented in current forecast systems. We, therefore, assess whether improved MJO‐NAO teleconnections are likely to lead to improved monthly NAO predictions. We find that even perfect MJO forecasts and teleconnections lead to only small improvements in NAO prediction skills. This work indicates that monthly timescales may represent a predictability gap for the NAO and hence the Euro‐Atlantic winter climate in which genuine skill improvements are difficult to achieve. Potential progress in this area could stem from currently unknown sources of skill and large initialised climate ensembles will be a vital tool for investigating these.","PeriodicalId":50734,"journal":{"name":"Atmospheric Science Letters","volume":null,"pages":null},"PeriodicalIF":2.0000,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/asl.1146","citationCount":"2","resultStr":"{\"title\":\"What potential for improving sub-seasonal predictions of the winter NAO?\",\"authors\":\"Chris Kent, Adam A. Scaife, Nick Dunstone\",\"doi\":\"10.1002/asl.1146\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The North Atlantic Oscillation (NAO) is the leading mode of variability across the Atlantic sector and is a key metric of extratropical forecast performance. Skilful predictions of the NAO are possible at medium‐range (1–2 weeks) and seasonal time scales. However, in a leading dynamical prediction system, we find that sub‐seasonal predictions (1 month NAO with a lead time of 20–30 days) are not statistically significant and represent a gap in forecast skill. In this study, we have investigated the potential for improving predictions using a large ensemble of dynamical hindcasts. First, we find that monthly predictions of the NAO are only weakly related to forecast errors at the medium‐range. This implies that improving medium‐range forecast performance is unlikely to drive significant improvements at longer lead times. Second, the Madden‐Julian Oscillation (MJO) is the leading mode of sub‐seasonal variability in the Tropics and projects onto the NAO with a lag of 10–15 days, but its teleconnection is only partially represented in current forecast systems. We, therefore, assess whether improved MJO‐NAO teleconnections are likely to lead to improved monthly NAO predictions. We find that even perfect MJO forecasts and teleconnections lead to only small improvements in NAO prediction skills. This work indicates that monthly timescales may represent a predictability gap for the NAO and hence the Euro‐Atlantic winter climate in which genuine skill improvements are difficult to achieve. Potential progress in this area could stem from currently unknown sources of skill and large initialised climate ensembles will be a vital tool for investigating these.\",\"PeriodicalId\":50734,\"journal\":{\"name\":\"Atmospheric Science Letters\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.0000,\"publicationDate\":\"2022-12-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1002/asl.1146\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Atmospheric Science Letters\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/asl.1146\",\"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.1146","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}
What potential for improving sub-seasonal predictions of the winter NAO?
The North Atlantic Oscillation (NAO) is the leading mode of variability across the Atlantic sector and is a key metric of extratropical forecast performance. Skilful predictions of the NAO are possible at medium‐range (1–2 weeks) and seasonal time scales. However, in a leading dynamical prediction system, we find that sub‐seasonal predictions (1 month NAO with a lead time of 20–30 days) are not statistically significant and represent a gap in forecast skill. In this study, we have investigated the potential for improving predictions using a large ensemble of dynamical hindcasts. First, we find that monthly predictions of the NAO are only weakly related to forecast errors at the medium‐range. This implies that improving medium‐range forecast performance is unlikely to drive significant improvements at longer lead times. Second, the Madden‐Julian Oscillation (MJO) is the leading mode of sub‐seasonal variability in the Tropics and projects onto the NAO with a lag of 10–15 days, but its teleconnection is only partially represented in current forecast systems. We, therefore, assess whether improved MJO‐NAO teleconnections are likely to lead to improved monthly NAO predictions. We find that even perfect MJO forecasts and teleconnections lead to only small improvements in NAO prediction skills. This work indicates that monthly timescales may represent a predictability gap for the NAO and hence the Euro‐Atlantic winter climate in which genuine skill improvements are difficult to achieve. Potential progress in this area could stem from currently unknown sources of skill and large initialised climate ensembles will be a vital tool for investigating these.
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.