DOI: 10.5194/hess-19-361-2015
Scopus记录号: 2-s2.0-84921484824
论文题名: Assessment of precipitation and temperature data from CMIP3 global climate models for hydrologic simulation
作者: McMahon T ; A ; , Peel M ; C ; , Karoly D ; J
刊名: Hydrology and Earth System Sciences
ISSN: 10275606
出版年: 2015
卷: 19, 期: 1 起始页码: 361
结束页码: 377
语种: 英语
Scopus关键词: Climate change
; Climatology
; Data flow analysis
; Error statistics
; Mean square error
; Coupled Model Intercomparison Project
; Environmental studies
; Hydrologic simulations
; Interdisciplinary research
; Mean and standard deviations
; Mean annual temperatures
; Meteorological research institutes
; Root mean square errors
; Climate models
; climate modeling
; future prospect
; global climate
; precipitation (climatology)
; temperature effect
英文摘要: The objective of this paper is to identify better performing Coupled Model Intercomparison Project phase 3 (CMIP3) global climate models (GCMs) that reproduce grid-scale climatological statistics of observed precipitation and temperature for input to hydrologic simulation over global land regions. Current assessments are aimed mainly at examining the performance of GCMs from a climatology perspective and not from a hydrology standpoint. The performance of each GCM in reproducing the precipitation and temperature statistics was ranked and better performing GCMs identified for later analyses. Observed global land surface precipitation and temperature data were drawn from the Climatic Research Unit (CRU) 3.10 gridded data set and re-sampled to the resolution of each GCM for comparison. Observed and GCM-based estimates of mean and standard deviation of annual precipitation, mean annual temperature, mean monthly precipitation and temperature and Köppen-Geiger climate type were compared. The main metrics for assessing GCM performance were the Nash-Sutcliffe efficiency (NSE) index and root mean square error (RMSE) between modelled and observed long-term statistics. This information combined with a literature review of the performance of the CMIP3 models identified the following better performing GCMs from a hydrologic perspective: HadCM3 (Hadley Centre for Climate Prediction and Research), MIROCm (Model for Interdisciplinary Research on Climate) (Center for Climate System Research (The University of Tokyo), National Institute for Environmental Studies, and Frontier Research Center for Global Change), MIUB (Meteorological Institute of the University of Bonn, Meteorological Research Institute of KMA, and Model and Data group), MPI (Max Planck Institute for Meteorology) and MRI (Japan Meteorological Research Institute). The future response of these GCMs was found to be representative of the 44 GCM ensemble members which confirms that the selected GCMs are reasonably representative of the range of future GCM projections. © Author(s) 2015. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/78634
Appears in Collections: 气候变化事实与影响
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作者单位: Department of Infrastructure Engineering, University of MelbourneVIC, Australia; School of Earth Sciences, ARC Centre of Excellence for Climate System Science, University of MelbourneVIC, Australia
Recommended Citation:
McMahon T,A,, Peel M,et al. Assessment of precipitation and temperature data from CMIP3 global climate models for hydrologic simulation[J]. Hydrology and Earth System Sciences,2015-01-01,19(1)