globalchange  > 气候变化与战略
DOI: 10.5194/hess-23-4803-2019
论文题名:
Selection of multi-model ensemble of general circulation models for the simulation of precipitation and maximum and minimum temperature based on spatial assessment metrics
作者: Ahmed K.; Sachindra D.A.; Shahid S.; Demirel M.C.; Chung E.-S.
刊名: Hydrology and Earth System Sciences
ISSN: 1027-5606
出版年: 2019
卷: 23, 期:11
起始页码: 4803
结束页码: 4824
语种: 英语
Scopus关键词: Atmospheric thermodynamics ; Decision trees ; Efficiency ; Climate projection ; Coupled Model Intercomparison Project ; General circulation model ; Maximum and minimum temperatures ; Multi-model ensemble ; Seasonal precipitations ; Spatial performance ; Temporal performance ; Climate models ; climate change ; climate modeling ; CMIP ; general circulation model ; precipitation (climatology) ; simulation ; spatial analysis ; temperature effect ; Pakistan
英文摘要: The climate modelling community has trialled a large number of metrics for evaluating the temporal performance of general circulation models (GCMs), while very little attention has been given to the assessment of their spatial performance, which is equally important. This study evaluated the performance of 36 Coupled Model Intercomparison Project 5 (CMIP5) GCMs in relation to their skills in simulating mean annual, monsoon, winter, pre-monsoon, and post-monsoon precipitation and maximum and minimum temperature over Pakistan using state-of-the-art spatial metrics, SPAtial EFficiency, fractions skill score, Goodman-Kruskal's lambda, Cramer's V, Mapcurves, and Kling-Gupta efficiency, for the period 1961-2005. The multi-model ensemble (MME) precipitation and maximum and minimum temperature data were generated through the intelligent merging of simulated precipitation and maximum and minimum temperature of selected GCMs employing random forest (RF) regression and simple mean (SM) techniques. The results indicated some differences in the ranks of GCMs for different spatial metrics. The overall ranks indicated NorESM1-M, MIROC5, BCC-CSM1-1, and ACCESS1-3 as the best GCMs in simulating the spatial patterns of mean annual, monsoon, winter, pre-monsoon, and post-monsoon precipitation and maximum and minimum temperature over Pakistan. MME precipitation and maximum and minimum temperature generated based on the best-performing GCMs showed more similarities with observed precipitation and maximum and minimum temperature compared to precipitation and maximum and minimum temperature simulated by individual GCMs. The MMEs developed using RF displayed better performance than the MMEs based on SM. Multiple spatial metrics have been used for the first time for selecting GCMs based on their capability to mimic the spatial patterns of annual and seasonal precipitation and maximum and minimum temperature. The approach proposed in the present study can be extended to any number of GCMs and climate variables and applicable to any region for the suitable selection of an ensemble of GCMs to reduce uncertainties in climate projections. © 2019 Author(s).
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/162849
Appears in Collections:气候变化与战略

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作者单位: Ahmed, K., Faculty of Civil Engineering, Universiti Teknologi Malaysia (UTM), Johor Bahru, 81310, Malaysia, Faculty of Water Resource Management, Lasbela University of Agriculture, Water and Marine Sciences, Balochistan, 90150, Pakistan; Sachindra, D.A., Institute for Sustainability and Innovation, College of Engineering and Science, Victoria University, P.O. Box 14428, Melbourne, VIC 8001, Australia; Shahid, S., Faculty of Civil Engineering, Universiti Teknologi Malaysia (UTM), Johor Bahru, 81310, Malaysia; Demirel, M.C., Department of Civil Engineering, Istanbul Technical University, Maslak, Istanbul, 34469, Turkey; Chung, E.-S., Department of Civil Engineering, Seoul National University of Science and Technology, Seoul, 01811, South Korea

Recommended Citation:
Ahmed K.,Sachindra D.A.,Shahid S.,et al. Selection of multi-model ensemble of general circulation models for the simulation of precipitation and maximum and minimum temperature based on spatial assessment metrics[J]. Hydrology and Earth System Sciences,2019-01-01,23(11)
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