DOI: 10.1175/JCLI-D-17-0404.1
Scopus记录号: 2-s2.0-85043679828
论文题名: Large-scale predictors for extreme hourly precipitation events in convection-permitting climate simulations
作者: Chan S.C. ; Kendon E.J. ; Roberts N. ; Blenkinsop S. ; Fowler H.J.
刊名: Journal of Climate
ISSN: 8948755
出版年: 2018
卷: 31, 期: 6 起始页码: 2115
结束页码: 2131
语种: 英语
英文关键词: Atmosphere
; Climate models
; Europe
; Mesoscale models
; Model comparison
; Regression analysis
Scopus关键词: Earth atmosphere
; Precipitation (meteorology)
; Regression analysis
; Cumulus parameterization
; Europe
; Extreme precipitation events
; Large-scale circulation patterns
; Meso-scale models
; Model comparison
; Regression relationship
; Weather and climate models
; Climate models
英文摘要: Midlatitude extreme precipitation events are caused by well-understood meteorological drivers, such as vertical instability and low pressure systems. In principle, dynamical weather and climate models behave in the same way, although perhaps with the sensitivities to the drivers varying between models. Unlike parameterized convection models (PCMs), convection-permitting models (CPMs) are able to realistically capture subdaily extreme precipitation. CPMs are computationally expensive; being able to diagnose the occurrence of subdaily extreme precipitation from large-scale drivers, with sufficient skill, would allow effective targeting of CPM downscaling simulations. Here the regression relationships are quantified between the occurrence of extreme hourly precipitation events and vertical stability and circulation predictors in southern United Kingdom 1.5-km CPM and 12-km PCM present- and future-climate simulations. Overall, the large-scale predictors demonstrate skill in predicting the occurrence of extreme hourly events in both the 1.5- and 12-km simulations. For the present-climate simulations, extreme occurrences in the 12-km model are less sensitive to vertical stability than in the 1.5-km model, consistent with understanding the limitations of cumulus parameterization. In the future-climate simulations, the regression relationship is more similar between the two models, which may be understood from changes to the large-scale circulation patterns and land surface climate. Overall, regression analysis offers a promising avenue for targeting CPM simulations. The authors also outline which events would be missed by adopting such a targeted approach. © 2018 American Meteorological Society. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/111617
Appears in Collections: 气候减缓与适应
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作者单位: School of Engineering, Newcastle University, Newcastle upon Tyne, United Kingdom; Met Office Hadley Centre, Exeter, United Kingdom; MetOffice at Reading, Reading, United Kingdom
Recommended Citation:
Chan S.C.,Kendon E.J.,Roberts N.,et al. Large-scale predictors for extreme hourly precipitation events in convection-permitting climate simulations[J]. Journal of Climate,2018-01-01,31(6)