气候变化领域集成服务门户(CCPortal): Effective sample size for precipitation estimation in atmospheric general circulation model ensemble experiments: dependence on temporal and spatial averaging scales

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DOI	10.1007/s10584-020-02886-0
	Effective sample size for precipitation estimation in atmospheric general circulation model ensemble experiments: dependence on temporal and spatial averaging scales
	Hibino K.; Takayabu I.
发表日期	2020
ISSN	0165-0009
英文摘要	The accuracy of climate projections is improved by increasing the number of samples from ensemble experiments, leading to a decrease in the confidence interval of a target climatological variable. The improvement in the accuracy depends on the degree of independence of each ensemble member in the experiments. When the members of ensemble experiments are dependent on each other, the introduction of an effective sample size (ESS) is necessary to correctly estimate the confidence interval. This study is the first attempt to estimate the ESS for precipitation as a function of the number of ensemble members, although some previous studies have investigated another type of ESS in terms of the length of simulation period. The ESS in the present study is intrinsic to the atmospheric general circulation models (AGCM) forced by the ocean boundary condition because the outputs of AGCM ensemble members are similar or dependent on each other due to the commonly used boundary condition, i.e., the distribution of sea surface temperature, sea ice concentration, and sea ice thickness. Looking at the values of ESS as a function of geographical location, those in the tropics and over the ocean are smaller than those at higher latitudes and over continents; precipitation events in areas with smaller (larger) ESS are strongly (weakly) constrained by the ocean boundary condition. The increase in temporal and spatial averaging scales for precipitation estimation leads to the decrease in the ESS, of whose trend is attributed to the spatio-temporal characteristics of the precipitation events as represented by the power spectrum and co-spectrum. © 2020, Springer Nature B.V.
英文关键词	Atmospheric general circulation model; Effective sample size; Ensemble experiment; Precipitation assessment; Temporal and spatial averaging scales
语种	英语
scopus关键词	Clouds; Oceanography; Sea ice; Surface waters; Atmospheric general circulation models; Degree of independence; Geographical locations; Precipitation estimation; Sea ice concentration; Sea surface temperature (SST); Spatiotemporal characteristics; Temporal and spatial; Boundary conditions
来源期刊	Climatic Change
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/147279
作者单位	Institute of Industrial Science, The University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8505, Japan; Meteorological Research Institute, 1-1, Nagamine, Tsukuba, Ibaraki 305-0052, Japan
推荐引用方式 GB/T 7714	Hibino K.,Takayabu I.. Effective sample size for precipitation estimation in atmospheric general circulation model ensemble experiments: dependence on temporal and spatial averaging scales[J],2020.
APA	Hibino K.,&Takayabu I..(2020).Effective sample size for precipitation estimation in atmospheric general circulation model ensemble experiments: dependence on temporal and spatial averaging scales.Climatic Change.
MLA	Hibino K.,et al."Effective sample size for precipitation estimation in atmospheric general circulation model ensemble experiments: dependence on temporal and spatial averaging scales".Climatic Change (2020).