气候变化领域集成服务门户(CCPortal): A MCDM-based framework for selection of general circulation models and projection of spatio-temporal rainfall changes: A case study of Nigeria

CCPortal

DOI	10.1016/j.atmosres.2019.03.033
	A MCDM-based framework for selection of general circulation models and projection of spatio-temporal rainfall changes: A case study of Nigeria
	Shiru M.S.; Shahid S.; Chung E.-S.; Alias N.; Scherer L.
发表日期	2019
ISSN	0169-8095
起始页码	1
结束页码	16
卷号	225
英文摘要	A multi-criteria decision-making approach was used for the selection of GCMs for Nigeria based on their ability to replicate historical rainfall estimated using three entropy-based feature selection methods namely, Entropy Gain (EG), Gain Ratio (GR), and Symmetrical Uncertainty (SU). Performances of four bias correction methods were compared to identify the most suitable method for downscaling and projection of rainfall using the selected GCMs. Random forest (RF) regression was used for the generation of the multi-model ensemble (MME) average of projected rainfall. The ensemble projections for each of the representative concentration pathways (RCPs) 2.6, 4.5, 6.0, and 8.5 were computed and compared with global precipitation climatology centre (GPCC) historical rainfall of Nigeria to assess the percentage changes in annual rainfall with 95% level of confidence at different ecological zones for three future periods 2010–2039, 2040–2069, and 2070–2099. Quantile regression was used to assess the changes in seasonal rainfall at 95% confidence interval over the present century. The results revealed that MRI-CGCM3, HadGEM2-ES, CSIRO-Mk3-6-0 and CESM1-CAM5 are the most suitable GCMs for the projection of rainfall in Nigeria. The linear scaling method was found as the most suitable approach for downscaling of rainfall in terms of all the statistical indices used. It was found to downscale rainfall with normalized root mean square error (NRMSE) in the range of 30.7–44.0%, while Nash-Sutcliff efficiency (NSE) was between 0.81 and 0.91, and modified coefficient of agreement (md) was between 0.82 and 0.88. Projection of rainfall showed no significant change in Nigeria over the century under RCP 2.6, 4.5 and 6.5, while RCP 8.5 showed a decrease in the last part of the century (2070–2099). The seasonal changes in rainfall showed an increase in rainfall in the range of 0–20% in most parts of the north. The methodology in this study can reduce the uncertainty inherent in climate change projection and produce better projection of possible spatial and temporal changes in annual and seasonal rainfall. © 2019
英文关键词	Feature selection method; General circulation model; Information entropy; Random forest; Statistical downscaling
语种	英语
scopus关键词	Climate change; Decision making; Decision trees; Feature extraction; Mean square error; Uncertainty analysis; Feature selection methods; General circulation model; Information entropy; Random forests; Statistical downscaling; Rain; annual variation; downscaling; entropy; general circulation model; machine learning; multicriteria analysis; precipitation (climatology); regression analysis; spatial variation; Nigeria
来源期刊	Atmospheric Research
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/162224
作者单位	Department of Water and Environmental Engineering, School of Civil Engineering, Faculty of Engineering, Universiti Teknologi Malaysia (UTM), Johor Bahru, 81310, Malaysia; Department of Environmental Sciences, Faculty of Science, Federal University Dutse, Dutse, P.M.B 7156, Nigeria; Department of Civil Engineering, Seoul National University of Science and Technology, Seoul, 01811, South Korea; Institute of Environmental Sciences (CML), Leiden University, Einsteinweg 2, Leiden, CC 2333, Netherlands
推荐引用方式 GB/T 7714	Shiru M.S.,Shahid S.,Chung E.-S.,et al. A MCDM-based framework for selection of general circulation models and projection of spatio-temporal rainfall changes: A case study of Nigeria[J],2019,225.
APA	Shiru M.S.,Shahid S.,Chung E.-S.,Alias N.,&Scherer L..(2019).A MCDM-based framework for selection of general circulation models and projection of spatio-temporal rainfall changes: A case study of Nigeria.Atmospheric Research,225.
MLA	Shiru M.S.,et al."A MCDM-based framework for selection of general circulation models and projection of spatio-temporal rainfall changes: A case study of Nigeria".Atmospheric Research 225(2019).