Future Ko spacing diaeresis ppen-Geiger climate zones over Southeast Asia using CMIP6 Multimodel Ensemble

被引:19
作者
Hamed, Mohammed Magdy [1 ,2 ]
Nashwan, Mohamed Salem [3 ]
Shahid, Shamsuddin [2 ]
Wang, Xiao-Jun [4 ,5 ]
Bin Ismail, Tarmizi [2 ]
Dewan, Ashraf [6 ]
Asaduzzaman, Md [7 ]
机构
[1] Arab Acad Sci Technol & Maritime Transport AASTMT, Construct & Bldg Engn Dept, Coll Engn & Technol, B 2401 Smart Village, Giza 12577, Egypt
[2] Univ Teknol Malaysia UTM, Fac Civil Engn, Dept Water & Environm Engn, Skudia 81310, Malaysia
[3] Arab Acad Sci Technol & Maritime Transport AASTMT, Construct & Bldg Engn Dept, Coll Engn & Technol, Cairo 2033, Egypt
[4] Nanjing Hydraul Res Inst, State Key Lab Hydrol Water Resources & Hydraul En, Nanjing 210029, Peoples R China
[5] Minist Water Resources, Res Ctr Climate Change, Nanjing 210029, Peoples R China
[6] Curtin Univ, Spatial Sci Discipline, Sch Earth & Planetary Sci, Kent St, Perth, WA 6102, Australia
[7] Staffordshire Univ, Dept Engn, Sch Digital Technol & Arts, Stoke On Trent, Staffs, England
关键词
Koppen-Geiger climate classification; Global climate models; Shared socioeconomic pathways; Spatial metrics; Climate shifts; CLASSIFICATION; SHIFTS; PRECIPITATION; DISTRIBUTIONS; SIMILARITY; FORECASTS; SELECTION; IMPACTS; MODELS; MAP;
D O I
10.1016/j.atmosres.2022.106560
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
A possible shift in climate zones in Southeast Asia (SEA) for different shared socioeconomic pathways (SSPs) is evaluated in this study. The ability of 19 Coupled Model Intercomparison Project (CMIP6) global climate models (GCMs) in reconstructing the Ko center dot ppen-Geiger climate zones in SEA, estimated using reanalysis data (ERA5) for the period 1979-2014, was analysed using five categorical evaluation metrics. The best-performing models were selected to prepare an ensemble to project possible shifts in climate zones for different SSP scenarios in the future. Besides, future projections in climate variables were evaluated to assess the driving factor of climate shifts in the future. The results showed that three CMIP6 GCMs, EC-Earth3-Veg-LR, CMCC-ESM2 and CanESM5, had a higher skill in classifying the observed climate of SEA. Selected GCMs showed climate shifting in 3.4 to 12.6% of the total area of SEA for different SSPs. The highest geographical shift in climate was projected in the north, from dry winter and hot summer (Cwa) to tropical with dry winter (Aw), followed by Aw to tropical monsoon (Am) in the north and south, and tropical without dry season (Af) to Am in the middle and southwest of SEA. An increase in minimum temperature was the key to climate shifting from Cwa to Aw in the north, while increased rainfall was a reason for Aw to Am transition in the north and south. Overall, climatic shifting was higher for high emission scenarios. The maps of future climate zones generated in this study can help to identify the hotspots of ecologically vulnerable areas in SEA due to climate change.
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收藏
页数:18
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