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DOI | 10.1002/2017GL073053 |
Ensemble-based Reconstructed Forcing (ERF) for regional climate modeling: Attaining the performance at a fraction of cost | |
Erfanian, Amir1,2; Wang, Guiling1,2; Fomenko, Lori1,2; Yu, Miao3 | |
2017-04-16 | |
发表期刊 | GEOPHYSICAL RESEARCH LETTERS |
ISSN | 0094-8276 |
EISSN | 1944-8007 |
出版年 | 2017 |
卷号 | 44期号:7 |
文章类型 | Article |
语种 | 英语 |
国家 | USA; Peoples R China |
英文摘要 | Multimodel ensemble (MME) is considered the most reliable for both present-day and future climate simulations. However, the conventional MME approach can create physical inconsistencies between climate variables. It can also be computationally inhibiting when using regional climate models (RCMs) due to uncertainties originating from both RCMs and the driving global climate models (GCMs) which must be accounted for. Here we propose the Ensemble-based Reconstructed Forcing (ERF) approach which derives the RCM's initial and boundary conditions from the ensemble average of multiple GCMs. Using ensembles of up to six GCMs as examples, we show that the ERF approach with a single RCM integration performs comparably to the MME average in bias reduction. The ERF simulation provides unaltered solutions to the RCM's underlying equations, making it theoretically superior to the conventional MME approach which averages multiple solutions and may result in a physically implausible climate state. |
英文关键词 | ERF multimodel ensemble RCM climate change climate projection bias reduction |
领域 | 气候变化 |
收录类别 | SCI-E |
WOS记录号 | WOS:000400186500037 |
WOS关键词 | MULTIMODEL ENSEMBLE ; SPATIAL VARIABILITY ; SIMULATIONS ; PROJECTIONS ; UNCERTAINTY ; IMPACTS |
WOS类目 | Geosciences, Multidisciplinary |
WOS研究方向 | Geology |
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/28001 |
专题 | 气候变化 |
作者单位 | 1.Univ Connecticut, Dept Civil & Environm Engn, Storrs, CT 06269 USA; 2.Univ Connecticut, Ctr Environm Sci & Engn, Storrs, CT 06269 USA; 3.Nanjing Univ Informat Sci & Technol, Key Lab Meteorol Disaster, Minist Educ, Nanjing, Jiangsu, Peoples R China |
推荐引用方式 GB/T 7714 | Erfanian, Amir,Wang, Guiling,Fomenko, Lori,et al. Ensemble-based Reconstructed Forcing (ERF) for regional climate modeling: Attaining the performance at a fraction of cost[J]. GEOPHYSICAL RESEARCH LETTERS,2017,44(7). |
APA | Erfanian, Amir,Wang, Guiling,Fomenko, Lori,&Yu, Miao.(2017).Ensemble-based Reconstructed Forcing (ERF) for regional climate modeling: Attaining the performance at a fraction of cost.GEOPHYSICAL RESEARCH LETTERS,44(7). |
MLA | Erfanian, Amir,et al."Ensemble-based Reconstructed Forcing (ERF) for regional climate modeling: Attaining the performance at a fraction of cost".GEOPHYSICAL RESEARCH LETTERS 44.7(2017). |
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