DOI: 10.1016/j.atmosres.2018.06.006
Scopus记录号: 2-s2.0-85048117899
论文题名: Model output statistics downscaling using support vector machine for the projection of spatial and temporal changes in rainfall of Bangladesh
作者: Pour S.H. ; Shahid S. ; Chung E.-S. ; Wang X.-J.
刊名: Atmospheric Research
ISSN: 1698095
出版年: 2018
卷: 213 起始页码: 149
结束页码: 162
语种: 英语
英文关键词: Climate change projection
; Model output statistics
; Representative concentration pathways
; Statistical downscaling
; Support vector machine
Scopus关键词: Atmospheric thermodynamics
; Climate change
; Climate models
; Support vector machines
; Climate change projections
; Coupled Model Intercomparison Project
; Global precipitation
; Model output statistics
; Performance assessment
; Representative concentration pathways
; Spatial and temporal changes
; Statistical downscaling
; Rain
; climate change
; downscaling
; ensemble forecasting
; monsoon
; numerical model
; rainfall
; spatiotemporal analysis
; support vector machine
; temporal variation
; Bangladesh
英文摘要: A model output statistics (MOS) downscaling approach based on support vector machine (SVM) is proposed in this study for the projection of spatial and temporal changes in rainfall of Bangladesh. A combination of past performance assessment and envelope-based methods is used for the selection of GCM ensemble from Coupled Model Intercomparison Project phase 5 (CMIP5). Gauge-based gridded monthly rainfall data of Global Precipitation Climatological Center (GPCC) is used as a reference for downscaling and projection of GCM rainfall at regular grid intervals. The obtained results reveal the ability of SVM-based MOS models to replicate the temporal variation and distribution of GPCC rainfall efficiently. The ensemble mean of selected GCM projections downscaled using MOS models show changes in annual precipitation in the range of −4.2% to 24.6% in Bangladesh under four Representative Concentration Pathways (RCP) scenarios. Annual rainfalls are projected to increase more in the western part (5.1% to 24.6%) where average annual rainfall is relatively low, and less in the eastern part (−4.2 to 12.4%) where average annual rainfall is relatively high, which indicates more homogeneity in the spatial distribution of rainfall in Bangladesh in future. A higher increase in rainfall is projected during monsoon compared to other seasons, which indicates more concentration of rainfall in Bangladesh during monsoon. © 2018 Elsevier B.V. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/108796
Appears in Collections: 影响、适应和脆弱性 气候变化事实与影响
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作者单位: Faculty of Civil Engineering, Universiti Teknologi Malaysia (UTM), Johor Bahru, 81310, Malaysia; Faculty of Civil Engineering, Seoul National University of Science and Technology, Seoul, 01811, South Korea; State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Nanjing Hydraulic Research Institute, Nanjing, 210029, China
Recommended Citation:
Pour S.H.,Shahid S.,Chung E.-S.,et al. Model output statistics downscaling using support vector machine for the projection of spatial and temporal changes in rainfall of Bangladesh[J]. Atmospheric Research,2018-01-01,213