| DOI: | 10.1175/JCLI-D-11-00275.1
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| Scopus记录号: | 2-s2.0-84865170933
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| 论文题名: | Exploring perturbed physics ensembles in a regional climate model |
| 作者: | Bellprat O.; Kotlarski S.; Thi D.L.; R C.S.
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| 刊名: | Journal of Climate
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| ISSN: | 8948755
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| 出版年: | 2012
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| 卷: | 25, 期:13 | | 起始页码: | 4582
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| 结束页码: | 4599
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| 语种: | 英语
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| Scopus关键词: | Annual cycle
; Bias
; Climate prediction
; Climate sensitivity
; Global climate model
; Interannual variability
; Model parameters
; Model uncertainties
; Natural variability
; Objective models
; Parameter uncertainty
; Parametric uncertainties
; Precipitation intensity
; Ranking methods
; Reanalysis
; Regional climate models
; Regional scale
; Skill metric
; Superensembles
; Systematic evaluation
; Total cloud cover
; Climate change
; Climate models
; Error analysis
; Optimization
; Uncertainty analysis
; air temperature
; annual variation
; climate modeling
; climate prediction
; cloud cover
; ensemble forecasting
; error analysis
; optimization
; precipitation (climatology)
; precipitation intensity
; ranking
; regional climate
; uncertainty analysis
; Europe
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| 英文摘要: | Perturbed physics ensembles (PPEs) have been widely used to assess climate model uncertainties and have provided new estimates of climate sensitivity and parametric uncertainty in state-of-the-art climate models. So far, mainly global climate models were used to generate PPEs, and little work has been conducted with regional climate models. This paper discusses the parameter uncertainty in two PPEs of a regional climate model driven by reanalysis data for the present climate over Europe. The uncertainty is evaluated for the variables of 2-m temperature, precipitation, and total cloud cover, with a focus on the annual cycle, interannual variability, and selected extremes. The authors show that the simulated spread of the PPEs encompasses the observations at a regional scale in terms of the annual cycle and the interannual variability, provided observational uncertainty is taken into account. To rank the PPEs a new skill metric is proposed, which takes into account observational uncertainty and natural variability. The metric is a generalization of the climate prediction index (CPI) and is compared to metrics used in other studies. The consideration of observational uncertainty is particularly important for total cloud cover and reveals that current observations do not allow for a systematic evaluation of high precipitation intensities over the entire European domain. The skill framework is additionally used to identify important model parameters, which are of interest for an objective model calibration. © 2012 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/52329
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| Appears in Collections: | 气候变化事实与影响
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作者单位: | Institute for Atmospheric and Climate Science, ETH Zurich, Zurich, Switzerland
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| Recommended Citation: | |
Bellprat O.,Kotlarski S.,Thi D.L.,et al. Exploring perturbed physics ensembles in a regional climate model[J]. Journal of Climate,2012-01-01,25(13)
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