Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1016/j.atmosres.2018.06.006 |
Model output statistics downscaling using support vector machine for the projection of spatial and temporal changes in rainfall of Bangladesh | |
Pour, Sahar Hadi1; Shahid, Shamsuddin1; Chung, Eun-Sung2; Wang, Xiao-Jun3 | |
2018-11-15 | |
发表期刊 | ATMOSPHERIC RESEARCH |
ISSN | 0169-8095 |
EISSN | 1873-2895 |
出版年 | 2018 |
卷号 | 213页码:149-162 |
文章类型 | Article |
语种 | 英语 |
国家 | Malaysia; South Korea; Peoples R China |
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. |
英文关键词 | Statistical downscaling Model output statistics Climate change projection Representative concentration pathways Support vector machine |
领域 | 地球科学 |
收录类别 | SCI-E |
WOS记录号 | WOS:000442169800013 |
WOS关键词 | PROBABILISTIC CLIMATE PROJECTIONS ; MULTIMODEL ENSEMBLE ; PRECIPITATION PREDICTION ; SIMULATED PRECIPITATION ; MAXIMUM TEMPERATURE ; MINIMUM TEMPERATURE ; FEATURE-SELECTION ; AIR-TEMPERATURE ; WATER-RESOURCES ; CHANGE IMPACT |
WOS类目 | Meteorology & Atmospheric Sciences |
WOS研究方向 | Meteorology & Atmospheric Sciences |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/37974 |
专题 | 地球科学 |
作者单位 | 1.Univ Teknol Malaysia, Fac Civil Engn, Johor Baharu 81310, Malaysia; 2.Seoul Natl Univ Sci & Technol, Fac Civil Engn, Seoul 01811, South Korea; 3.Nanjing Hydraul Res Inst, State Key Lab Hydrol Water Resources & Hydraul En, Nanjing 210029, Jiangsu, Peoples R China |
推荐引用方式 GB/T 7714 | Pour, Sahar Hadi,Shahid, Shamsuddin,Chung, Eun-Sung,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,2018,213:149-162. |
APA | Pour, Sahar Hadi,Shahid, Shamsuddin,Chung, Eun-Sung,&Wang, Xiao-Jun.(2018).Model output statistics downscaling using support vector machine for the projection of spatial and temporal changes in rainfall of Bangladesh.ATMOSPHERIC RESEARCH,213,149-162. |
MLA | Pour, Sahar Hadi,et al."Model output statistics downscaling using support vector machine for the projection of spatial and temporal changes in rainfall of Bangladesh".ATMOSPHERIC RESEARCH 213(2018):149-162. |
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