气候变化领域集成服务门户(CCPortal): Assessing the fidelity of predictability estimates

CCPortal

DOI	10.1007/s00382-017-3903-7
	Assessing the fidelity of predictability estimates
	Pegion K.; DelSole T.; Becker E.; Cicerone T.
发表日期	2019
ISSN	0930-7575
起始页码	7251
结束页码	7265
卷号	53 期号:12
英文摘要	Predictability is an intrinsic limit of the climate system due to uncertainty in initial conditions and the chaotic nature of the atmosphere. Estimates of predictability together with calculations of current prediction skill are used to define the gaps in our prediction capabilities, inform future model developments, and indicate to stakeholders the potential for making forecasts that can inform their decisions. The true predictability of the climate system is not known and must be estimated, typically using a perfect model estimate from an ensemble prediction system. However, different prediction systems can give different estimates of predictability. Can we determine which estimate of predictability is most representative of the true predictability of the climate system? We test three metrics as potential indicators of the fidelity of predictability estimates in an idealized framework—the spread-error relationship, autocorrelation and skill. Using the North American multi-model ensemble re-forecast database, we quantify whether these metrics accurately indicate a model’s ability to properly estimate predictability. It is found that none of these metrics is a robust measure for determining whether a predictability estimate is realistic for El Nino-Southern oscillation events. For temperature and precipitation over land, errors in the spread-error ratio are related to errors in estimating predictability at the shortest lead-times, while skill is not related to predictability errors. The relationship between errors in the autocorrelation and errors in estimating predictability varies by lead-time and region. © 2017, Springer-Verlag GmbH Germany.
英文关键词	NMME; Predictability
语种	英语
scopus关键词	assessment method; El Nino-Southern Oscillation; ensemble forecasting; estimation method; prediction; weather forecasting
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/145830
作者单位	Department of Atmospheric, Oceanic, and Earth Sciences and Center for Ocean-Land-Atmosphere Studies, George Mason University, Fairfax, VA, United States; NOAA/Climate Prediction Center and Innovim, LLC, College Park, MD, United States
推荐引用方式 GB/T 7714	Pegion K.,DelSole T.,Becker E.,et al. Assessing the fidelity of predictability estimates[J],2019,53(12).
APA	Pegion K.,DelSole T.,Becker E.,&Cicerone T..(2019).Assessing the fidelity of predictability estimates.Climate Dynamics,53(12).
MLA	Pegion K.,et al."Assessing the fidelity of predictability estimates".Climate Dynamics 53.12(2019).