| DOI: | 10.1175/JCLI-D-12-00485.1
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| Scopus记录号: | 2-s2.0-84888049213
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| 论文题名: | An evaluation of decadal probability forecasts from state-of-the-art climate models |
| 作者: | Suckling E.B.; Smith L.A.
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| 刊名: | Journal of Climate
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| ISSN: | 8948755
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| 出版年: | 2013
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| 卷: | 26, 期:23 | | 起始页码: | 9334
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| 结束页码: | 9347
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| 语种: | 英语
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| Scopus关键词: | Ensembles
; Forecast verification/skill
; Hindcasts
; Probability forecasts/models/distribution
; Statistical forecasting
; Climate change
; Computer simulation
; Decision support systems
; Dielectric properties
; Earth (planet)
; Forecasting
; Models
; Time series
; Climate models
; climate modeling
; climatology
; decadal variation
; ensemble forecasting
; hindcasting
; probability
; time series analysis
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| 英文摘要: | While state-of-the-art models of Earth's climate system have improved tremendously over the last 20 years, nontrivial structural flaws still hinder their ability to forecast the decadal dynamics of the Earth system realistically. Contrasting the skill of these models not only with each other but also with empirical models can reveal the space and time scales on which simulation models exploit their physical basis effectively and quantify their ability to add information to operational forecasts. The skill of decadal probabilistic hindcasts for annual global-mean and regional-mean temperatures from the EU Ensemble-Based Predictions of Climate Changes and Their Impacts (ENSEMBLES) project is contrasted with several empirical models. Both the ENSEMBLES models and a "dynamic climatology" empirical model show probabilistic skill above that of a static climatology for global-mean temperature. The dynamic climatology model, however, often outperforms the ENSEMBLES models. The fact that empirical models display skill similar to that of today's state-of-the-art simulation models suggests that empirical forecasts can improve decadal forecasts for climate services, just as in weather, medium-range, and seasonal forecasting. It is suggested that the direct comparison of simulation models with empirical models becomes a regular component of large model forecast evaluations. Doing so would clarify the extent to which state-of-the-art simulation models provide information beyond that available from simpler empirical models and clarify current limitations in using simulation forecasting for decision support. Ultimately, the skill of simulation models based on physical principles is expected to surpass that of empirical models in a changing climate; their direct comparison provides information on progress toward that goal, which is not available in model-model intercomparisons. © 2013 American Meteorological Society. |
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| 资源类型: | 期刊论文
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| 标识符: | http://119.78.100.158/handle/2HF3EXSE/51531
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| Appears in Collections: | 气候变化事实与影响
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作者单位: | Centre for the Analysis of Time Series, London School of Economics, Houghton Street, London WC2A 2AE, United Kingdom
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| Recommended Citation: | |
Suckling E.B.,Smith L.A.. An evaluation of decadal probability forecasts from state-of-the-art climate models[J]. Journal of Climate,2013-01-01,26(23)
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