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DOI10.1007/s00382-018-4366-1
Seasonal predictability of winter ENSO types in operational dynamical model predictions
Ren H.-L.; Scaife A.A.; Dunstone N.; Tian B.; Liu Y.; Ineson S.; Lee J.-Y.; Smith D.; Liu C.; Thompson V.; Vellinga M.; MacLachlan C.
发表日期2019
ISSN0930-7575
起始页码3869
结束页码3890
卷号52期号:2020-07-08
英文摘要The El Niño-Southern Oscillation (ENSO) events of recent decades have been divided into the two different types based on their spatial patterns, the Eastern Pacific (EP) type and Central Pacific (CP) type. Their most significant difference is the distinguished zonal center locations of sea surface temperature (SST) anomalies in the equatorial Pacific. In this study, based on six operational climate models, we evaluate predictability of the two types of ENSO events in winter to examine whether dynamical predictions can distinguish between the two spatial patterns at lead time of 1 month and tell us more than simply whether an event is on the way. We show that winter EP and CP El Niño and La Niña events can only be distinguished in a minority of these models at 1-month lead, and the EP type tends to has a more realistic zonal positions of SST pattern centers than the CP type. Compared to the SST patterns, the differences between the two types are less apparent in precipitation especially for the two La Niña types in the models. Examinations of the extratropical teleconnections to the two ENSO types show that some of the models can reproduce the differences between EP and CP teleconnections. Evaluations of model predictions show that the EP El Niño event has the same level hit rate with the CP El Niño and the CP La Niña event has much higher hit rate than the EP La Niña. While the multi-model ensemble increases Niño index prediction skill, it does not help to improve forecast skill of center longitude index of the SST patterns and distinguish the two types of ENSO events. Although ENSO skill is very high at this lead time, the rapid loss of the initialized information on the different ENSO types in most of the models severely limits the predictability of the two types of winter ENSO events and more research is needed to improve the performance of climate models in forecasting the two ENSO types. © 2018, The Author(s).
英文关键词Dynamical model; Evaluation; Predictability; Two types of winter ENSO events
语种英语
scopus关键词climate modeling; El Nino-Southern Oscillation; forecasting method; prediction; sea surface temperature; seasonal variation; teleconnection; temperature anomaly; winter; Pacific Ocean; Pacific Ocean (Central); Pacific Ocean (East); Pacific Ocean (Equatorial)
来源期刊Climate Dynamics
文献类型期刊论文
条目标识符http://gcip.llas.ac.cn/handle/2XKMVOVA/146422
作者单位Laboratory for Climate Studies and CMA-NJU Joint Laboratory for Climate Prediction Studies, National Climate Center, China Meteorological Administration, 46 Zhongguancun, Haidian District, Beijing, 100081, China; Department of Atmospheric Science, School of Environmental Studies, China University of Geoscience, Wuhan, 430074, China; Met Office Hadley Centre, Exeter, United Kingdom; College of Engineering, Mathematics and Physical Sciences, Exeter University, Exeter, United Kingdom; Research Center for Climate Sciences, Pusan National University, Busan, South Korea
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GB/T 7714
Ren H.-L.,Scaife A.A.,Dunstone N.,et al. Seasonal predictability of winter ENSO types in operational dynamical model predictions[J],2019,52(2020-07-08).
APA Ren H.-L..,Scaife A.A..,Dunstone N..,Tian B..,Liu Y..,...&MacLachlan C..(2019).Seasonal predictability of winter ENSO types in operational dynamical model predictions.Climate Dynamics,52(2020-07-08).
MLA Ren H.-L.,et al."Seasonal predictability of winter ENSO types in operational dynamical model predictions".Climate Dynamics 52.2020-07-08(2019).
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