DOI: 10.1007/s00382-013-1751-7
Scopus记录号: 2-s2.0-84894359286
论文题名: Evaluation of the CORDEX-Africa multi-RCM hindcast: Systematic model errors
作者: Kim J. ; Waliser D.E. ; Mattmann C.A. ; Goodale C.E. ; Hart A.F. ; Zimdars P.A. ; Crichton D.J. ; Jones C. ; Nikulin G. ; Hewitson B. ; Jack C. ; Lennard C. ; Favre A.
刊名: Climate Dynamics
ISSN: 9307575
出版年: 2014
卷: 42, 期: 2017-05-06 起始页码: 1189
结束页码: 1202
语种: 英语
英文关键词: Africa
; CORDEX
; Impact assessments
; IPCC
; RCM evaluation
; Regional climate
; Systematic model biases
英文摘要: Monthly-mean precipitation, mean (TAVG), maximum (TMAX) and minimum (TMIN) surface air temperatures, and cloudiness from the CORDEX-Africa regional climate model (RCM) hindcast experiment are evaluated for model skill and systematic biases. All RCMs simulate basic climatological features of these variables reasonably, but systematic biases also occur across these models. All RCMs show higher fidelity in simulating precipitation for the west part of Africa than for the east part, and for the tropics than for northern Sahara. Interannual variation in the wet season rainfall is better simulated for the western Sahel than for the Ethiopian Highlands. RCM skill is higher for TAVG and TMAX than for TMIN, and regionally, for the subtropics than for the tropics. RCM skill in simulating cloudiness is generally lower than for precipitation or temperatures. For all variables, multi-model ensemble (ENS) generally outperforms individual models included in ENS. An overarching conclusion in this study is that some model biases vary systematically for regions, variables, and metrics, posing difficulties in defining a single representative index to measure model fidelity, especially for constructing ENS. This is an important concern in climate change impact assessment studies because most assessment models are run for specific regions/sectors with forcing data derived from model outputs. Thus, model evaluation and ENS construction must be performed separately for regions, variables, and metrics as required by specific analysis and/or assessments. Evaluations using multiple reference datasets reveal that cross-examination, quality control, and uncertainty estimates of reference data are crucial in model evaluations. © 2013 Springer-Verlag Berlin Heidelberg. 资助项目: NASA, National Aeronautics and Space Administration
; NSF, National Science Foundation
; NSF, National Science Foundation
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/54283
Appears in Collections: 过去全球变化的重建
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作者单位: JIFRESSE, University of California Los Angeles, Los Angeles, CA, United States; Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, United States; Sveriges Meteorologiska och Hydrologiska Institut, Norrköping, Sweden; University of Cape Town, Cape Town, South Africa; Centre de Recherches de Climatologie, UMR 6282, Biogéosciences CNRS, Universitée de Bourgogne, Dijon, France
Recommended Citation:
Kim J.,Waliser D.E.,Mattmann C.A.,et al. Evaluation of the CORDEX-Africa multi-RCM hindcast: Systematic model errors[J]. Climate Dynamics,2014-01-01,42(2017-05-06)