Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1007/s00382-017-3639-4 |
Accounting for downscaling and model uncertainty in fine-resolution seasonal climate projections over the Columbia River Basin | |
Ahmadalipour, Ali1; Moradkhani, Hamid1; Rana, Arun2 | |
2018 | |
发表期刊 | CLIMATE DYNAMICS |
ISSN | 0930-7575 |
EISSN | 1432-0894 |
出版年 | 2018 |
卷号 | 50页码:717-733 |
文章类型 | Article |
语种 | 英语 |
国家 | USA; Sweden |
英文摘要 | Climate change is expected to have severe impacts on natural systems as well as various socio-economic aspects of human life. This has urged scientific communities to improve the understanding of future climate and reduce the uncertainties associated with projections. In the present study, ten statistically downscaled CMIP5 GCMs at 1/16th deg. spatial resolution from two different downscaling procedures are utilized over the Columbia River Basin (CRB) to assess the changes in climate variables and characterize the associated uncertainties. Three climate variables, i.e. precipitation, maximum temperature, and minimum temperature, are studied for the historical period of 1970-2000 as well as future period of 2010-2099, simulated with representative concentration pathways of RCP4.5 and RCP8.5. Bayesian Model Averaging (BMA) is employed to reduce the model uncertainty and develop a probabilistic projection for each variable in each scenario. Historical comparison of long-term attributes of GCMs and observation suggests a more accurate representation for BMA than individual models. Furthermore, BMA projections are used to investigate future seasonal to annual changes of climate variables. Projections indicate significant increase in annual precipitation and temperature, with varied degree of change across different sub-basins of CRB. We then characterized uncertainty of future projections for each season over CRB. Results reveal that model uncertainty is the main source of uncertainty, among others. However, downscaling uncertainty considerably contributes to the total uncertainty of future projections, especially in summer. On the contrary, downscaling uncertainty appears to be higher than scenario uncertainty for precipitation. |
英文关键词 | Climate change Uncertainty Global climate models Columbia River Basin Bayesian Model Averaging |
领域 | 气候变化 |
收录类别 | SCI-E |
WOS记录号 | WOS:000422908700045 |
WOS关键词 | FUTURE CLIMATE ; TEMPERATURE PROJECTIONS ; PACIFIC-NORTHWEST ; CHANGE IMPACTS ; UNITED-STATES ; PRECIPITATION ; EXTREMES ; SUMMER ; SIMULATIONS ; VARIABILITY |
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/35855 |
专题 | 气候变化 |
作者单位 | 1.Portland State Univ, Remote Sensing & Water Resources Lab, Dept Civil & Environm Engn, Portland, OR 97207 USA; 2.Swedish Meteorol & Hydrol Inst, Norrkoping, Sweden |
推荐引用方式 GB/T 7714 | Ahmadalipour, Ali,Moradkhani, Hamid,Rana, Arun. Accounting for downscaling and model uncertainty in fine-resolution seasonal climate projections over the Columbia River Basin[J]. CLIMATE DYNAMICS,2018,50:717-733. |
APA | Ahmadalipour, Ali,Moradkhani, Hamid,&Rana, Arun.(2018).Accounting for downscaling and model uncertainty in fine-resolution seasonal climate projections over the Columbia River Basin.CLIMATE DYNAMICS,50,717-733. |
MLA | Ahmadalipour, Ali,et al."Accounting for downscaling and model uncertainty in fine-resolution seasonal climate projections over the Columbia River Basin".CLIMATE DYNAMICS 50(2018):717-733. |
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