DOI: 10.1007/s00382-016-3407-x
Scopus记录号: 2-s2.0-84992422459
论文题名: Climate model forecast biases assessed with a perturbed physics ensemble
作者: Mulholland D.P. ; Haines K. ; Sparrow S.N. ; Wallom D.
刊名: Climate Dynamics
ISSN: 9307575
出版年: 2017
卷: 49, 期: 2017-05-06 起始页码: 1729
结束页码: 1746
语种: 英语
英文关键词: Climate model optimisation
; HadCM3
; Model drift
; Perturbed physics
英文摘要: Perturbed physics ensembles have often been used to analyse long-timescale climate model behaviour, but have been used less often to study model processes on shorter timescales. We combine a transient perturbed physics ensemble with a set of initialised forecasts to deduce regional process errors present in the standard HadCM3 model, which cause the model to drift in the early stages of the forecast. First, it is shown that the transient drifts in the perturbed physics ensembles can be used to recover quantitatively the parameters that were perturbed. The parameters which exert most influence on the drifts vary regionally, but upper ocean mixing and atmospheric convective processes are particularly important on the 1-month timescale. Drifts in the initialised forecasts are then used to recover the ‘equivalent parameter perturbations’, which allow identification of the physical processes that may be at fault in the HadCM3 representation of the real world. Most parameters show positive and negative adjustments in different regions, indicating that standard HadCM3 values represent a global compromise. The method is verified by correcting an unusually widespread positive bias in the strength of wind-driven ocean mixing, with forecast drifts reduced in a large number of areas as a result. This method could therefore be used to improve the skill of initialised climate model forecasts by reducing model biases through regional adjustments to physical processes, either by tuning or targeted parametrisation refinement. Further, such regionally tuned models might also significantly outperform standard climate models, with global parameter configurations, in longer-term climate studies. © 2016, The Author(s). 资助项目: NERC, Natural Environment Research Council
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/53090
Appears in Collections: 过去全球变化的重建
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作者单位: Department of Meteorology, University of Reading, Reading, United Kingdom; Department of Meteorology and National Centre for Earth Observation, University of Reading, Reading, United Kingdom; Oxford e-Research Centre, University of Oxford, Oxford, United Kingdom
Recommended Citation:
Mulholland D.P.,Haines K.,Sparrow S.N.,et al. Climate model forecast biases assessed with a perturbed physics ensemble[J]. Climate Dynamics,2017-01-01,49(2017-05-06)