气候变化领域集成服务门户(CCPortal): Multiyear statistical prediction of ENSO enhanced by the tropical Pacific observing system

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DOI	10.1175/JCLI-D-18-0877.1
	Multiyear statistical prediction of ENSO enhanced by the tropical Pacific observing system
	Petrova D.; Ballester J.; Koopman S.J.; Rodó X.
发表日期	2020
ISSN	0894-8755
起始页码	163
结束页码	174
卷号	33 期号:1
英文摘要	The theoretical predictability limit of El Niño-Southern Oscillation has been shown to be on the order of years, but long-lead predictions of El Niño (EN) and La Niña (LN) are still lacking. State-of-the-art forecasting schemes traditionally do not predict beyond the spring barrier. Recent efforts have been dedicated to the improvement of dynamical models, while statistical schemes still need to take full advantage of the availability of ocean subsurface variables, provided regularly for the last few decades as a result of the Tropical Ocean-Global Atmosphere Program (TOGA). Here we use a number of predictor variables, including temperature at different depths and regions of the equatorial ocean, in a flexible statistical dynamic components model to make skillful long-lead retrospective predictions (hindcasts) of the Niño-3.4 index in the period 1970-2016. The model hindcasts the major EN episodes up to 2.5 years in advance, including the recent extreme 2015/16 EN. The analysis demonstrates that events are predicted more accurately after the completion of the observational array in the tropical Pacific in 1994, as a result of the improved data quality and coverage achieved by TOGA. Therefore, there is potential to issue long-lead predictions of this climatic phenomenon at a low computational cost. © 2019 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).
英文关键词	Atmospheric pressure; Climatology; Tropics; Computational costs; Predictability limit; Predictor variables; Southern oscillation; Statistical dynamics; Statistical prediction; Statistical scheme; Tropical ocean-global atmospheres; Forecasting; data quality; El Nino; El Nino-Southern Oscillation; La Nina; prediction; statistical analysis; Pacific Ocean; Pacific Ocean (Tropical)
语种	英语
来源期刊	Journal of Climate
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/171557
作者单位	Climate and Health Programme, Barcelona Institute for Global Health, Barcelona, Catalonia, Spain; Vrije Universiteit Amsterdam, Amsterdam, Netherlands; Climate and Health Programme, Barcelona Institute for Global Health, Institució Catalana de Recerca i Estudis Avancats, Barcelona, Catalonia, Spain
推荐引用方式 GB/T 7714	Petrova D.,Ballester J.,Koopman S.J.,et al. Multiyear statistical prediction of ENSO enhanced by the tropical Pacific observing system[J],2020,33(1).
APA	Petrova D.,Ballester J.,Koopman S.J.,&Rodó X..(2020).Multiyear statistical prediction of ENSO enhanced by the tropical Pacific observing system.Journal of Climate,33(1).
MLA	Petrova D.,et al."Multiyear statistical prediction of ENSO enhanced by the tropical Pacific observing system".Journal of Climate 33.1(2020).