Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1016/j.atmosres.2017.12.008 |
Uncertainties of statistical downscaling from predictor selection: Equifinality and transferability | |
Fu, Guobin1; Charles, Stephen P.1; Chiew, Francis H. S.2; Ekstrom, Marie2,3; Potter, Nick J.2 | |
2018-05-01 | |
发表期刊 | ATMOSPHERIC RESEARCH
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ISSN | 0169-8095 |
EISSN | 1873-2895 |
出版年 | 2018 |
卷号 | 203页码:130-140 |
文章类型 | Article |
语种 | 英语 |
国家 | Australia; Wales |
英文摘要 | The nonhomogeneous hidden Markov model (NHMM) statistical downscaling model, 38 catchments in southeast Australia and 19 general circulation models (GCMs) were used in this study to demonstrate statistical down scaling uncertainties caused by equifinality to and transferability. That is to say, there could be multiple sets of predictors that give similar daily rainfall simulation results for both calibration and validation periods, but project different amounts (or even directions of change) of rainfall changing in the future. Results indicated that two sets of predictors (Set 1 with predictors of sea level pressure north-south gradient, u-wind at 700 hPa, v-wind at 700 hPa, and specific humidity at 700 hPa and Set 2 with predictors of sea level pressure north-south gradient, u-wind at 700 hPa, v-wind at 700 hPa, and dewpoint temperature depression at 850 hPa) as inputs to the NHMM produced satisfactory results of seasonal rainfall in comparison with observations. For example, during the model calibration period, the relative errors across the 38 catchments ranged from 0.48 to 1.76% with a mean value of 1.09% for the predictor Set 1, and from 0.22 to 2.24% with a mean value of 1.16% for the predictor Set 2. However, the changes of future rainfall from NHMM projections based on 19 GCMs produced projections with a different sign for these two different sets of predictors: Set 1 predictors project an increase of future rainfall with magnitudes depending on future time periods and emission scenarios, but Set 2 predictors project a decline of future rainfall. Such divergent projections may present a significant challenge for applications of statistical downscaling as well as climate change impact studies, and could potentially imply caveats in many existing studies in the literature. |
英文关键词 | Statistical downscaling Uncertainties Equifinality Transferability Predictor selections NHMM GCMs |
领域 | 地球科学 |
收录类别 | SCI-E |
WOS记录号 | WOS:000426226400012 |
WOS关键词 | CIRCULATION MODEL OUTPUT ; DAILY RAINFALL ; CLIMATE-CHANGE ; FUTURE CLIMATE ; ANALOG METHOD ; PRECIPITATION ; PROJECTIONS ; IMPACTS ; RUNOFF |
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/37955 |
专题 | 地球科学 |
作者单位 | 1.CSIRO Land & Water, Private Bag 5, Wembley, WA 6913, Australia; 2.CSIRO Land & Water, GPO Box 1666, Canberra, ACT, Australia; 3.Cardiff Univ, Sch Earth & Ocean Sci, Cardiff CF10 3AT, S Glam, Wales |
推荐引用方式 GB/T 7714 | Fu, Guobin,Charles, Stephen P.,Chiew, Francis H. S.,et al. Uncertainties of statistical downscaling from predictor selection: Equifinality and transferability[J]. ATMOSPHERIC RESEARCH,2018,203:130-140. |
APA | Fu, Guobin,Charles, Stephen P.,Chiew, Francis H. S.,Ekstrom, Marie,&Potter, Nick J..(2018).Uncertainties of statistical downscaling from predictor selection: Equifinality and transferability.ATMOSPHERIC RESEARCH,203,130-140. |
MLA | Fu, Guobin,et al."Uncertainties of statistical downscaling from predictor selection: Equifinality and transferability".ATMOSPHERIC RESEARCH 203(2018):130-140. |
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