气候变化领域集成服务门户(CCPortal): Optimal estimation of stochastic energy balance model parameters

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DOI	10.1175/JCLI-D-19-0589.1
	Optimal estimation of stochastic energy balance model parameters
	Cummins D.P.; Stephenson D.B.; Stott P.A.
发表日期	2020
ISSN	0894-8755
起始页码	7909
结束页码	7926
卷号	33 期号:18
英文摘要	This study has developed a rigorous and efficient maximum likelihood method for estimating the parameters in stochastic energy balance models (with any k . 0 number of boxes) given time series of surface temperature and top-of-the-atmosphere net downward radiative flux. The method works by finding a state-space representation of the linear dynamic system and evaluating the likelihood recursively via the Kalman filter. Confidence intervals for estimated parameters are straightforward to construct in the maximum likelihood framework, and information criteria may be used to choose an optimal number of boxes for parsimonious k-box emulation of atmosphere–ocean general circulation models (AOGCMs). In addition to estimating model parameters the method enables hidden state estimation for the unobservable boxes corresponding to the deep ocean, and also enables noise filtering for observations of surface temperature. The feasibility, reliability, and performance of the proposed method are demonstrated in a simulation study. To obtain a set of optimal k-box emulators, models are fitted to the 4 3 CO2 step responses of 16 AOGCMs in CMIP5. It is found that for all 16 AOGCMs three boxes are required for optimal k-box emulation. The number of boxes k is found to influence, sometimes strongly, the impulse responses of the fitted models. © 2020 American Meteorological Society.
英文关键词	Atmospheric temperature; Climate models; Energy balance; Kalman filters; Linear control systems; Maximum likelihood estimation; State space methods; Stochastic models; Stochastic systems; Surface properties; Energy balance models; Hidden state estimations; Information criterion; Linear dynamic system; Maximum likelihood methods; Ocean general circulation models; State space representation; Top of the atmospheres; Parameter estimation; air-sea interaction; energy balance; estimation method; general circulation model; Kalman filter; maximum likelihood analysis; parsimony analysis; stochasticity
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/171130
作者单位	University of Exeter, Exeter, United Kingdom
推荐引用方式 GB/T 7714	Cummins D.P.,Stephenson D.B.,Stott P.A.. Optimal estimation of stochastic energy balance model parameters[J],2020,33(18).
APA	Cummins D.P.,Stephenson D.B.,&Stott P.A..(2020).Optimal estimation of stochastic energy balance model parameters.Journal of Climate,33(18).
MLA	Cummins D.P.,et al."Optimal estimation of stochastic energy balance model parameters".Journal of Climate 33.18(2020).