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DOI | 10.1007/s10584-018-2276-1 |
Conditional stochastic simulation model for spatial downscaling for assessing the effects of climate change on hydro-meteorological variables | |
Lee, Taesam1; Ouarda, Taha B. M. J.2 | |
2018-10-01 | |
发表期刊 | CLIMATIC CHANGE |
ISSN | 0165-0009 |
EISSN | 1573-1480 |
出版年 | 2018 |
卷号 | 150页码:163-180 |
文章类型 | Article |
语种 | 英语 |
国家 | South Korea; Canada |
英文摘要 | The current study examines the recently proposed bias correction and stochastic analogues (BCSA) statistical spatial downscaling technique and attempts to improve it by conditioning coarse resolution data when generating replicates. While the BCSA method reproduces the statistical features of the observed fine data, this existing model does not replicate the observed coarse spatial pattern, and subsequently, the cross-correlation between the observed coarse data and downscaled fine data with the model cannot be preserved. To address the dissimilarity between the BCSA downscaled data and observed fine data, a new statistical spatial downscaling method, conditional stochastic simulation with bias correction (BCCS), which employs the conditional multivariate distribution and principal component analysis, is proposed. Gridded observed climate data of mean daily precipitation (mm/day) covering a month at 1/8 degrees for a fine resolution and at 1 degrees for a coarse resolution over Florida for the current and future periods were used to verify and cross-validate the proposed technique. The observed coarse and fine data cover the 50-year period from 1950 to1999, and the future RCP4.5 and RCP8.5 climate scenarios cover the 100-year period from 2000 to 2099. The verification and cross-validation results show that the proposed BCCS downscaling method serves as an effective alternative means of downscaling monthly precipitation levels to assess climate change effects on hydrological variables. The RCP4.5 and RCP8.5 GCM scenarios are successfully downscaled. |
领域 | 气候变化 |
收录类别 | SCI-E |
WOS记录号 | WOS:000448034000003 |
WOS关键词 | DAILY PRECIPITATION ; BIAS CORRECTION ; CHANGE IMPACTS ; REGRESSION ; STREAMFLOW ; UTILITY |
WOS类目 | Environmental Sciences ; Meteorology & Atmospheric Sciences |
WOS研究方向 | Environmental Sciences & Ecology ; 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/30033 |
专题 | 气候变化 |
作者单位 | 1.Gyeongsang Natl Univ, ERI, Dept Civil Engn, Jinju, South Korea; 2.INRS ETE, 490 Rue Couronne, Quebec City, PQ G1K 9A9, Canada |
推荐引用方式 GB/T 7714 | Lee, Taesam,Ouarda, Taha B. M. J.. Conditional stochastic simulation model for spatial downscaling for assessing the effects of climate change on hydro-meteorological variables[J]. CLIMATIC CHANGE,2018,150:163-180. |
APA | Lee, Taesam,&Ouarda, Taha B. M. J..(2018).Conditional stochastic simulation model for spatial downscaling for assessing the effects of climate change on hydro-meteorological variables.CLIMATIC CHANGE,150,163-180. |
MLA | Lee, Taesam,et al."Conditional stochastic simulation model for spatial downscaling for assessing the effects of climate change on hydro-meteorological variables".CLIMATIC CHANGE 150(2018):163-180. |
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