| DOI: | 10.1007/s10584-016-1862-3
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| Scopus记录号: | 2-s2.0-85006375053
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| 论文题名: | On bias correction in drought frequency analysis based on climate models |
| 作者: | Aryal Y.; Zhu J.
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| 刊名: | Climatic Change
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| ISSN: | 0165-0009
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| EISSN: | 1573-1480
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| 出版年: | 2017
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| 卷: | 140, 期:2018-03-04 | | 起始页码: | 361
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| 结束页码: | 374
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| 语种: | 英语
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| Scopus关键词: | Climate change
; Drought
; Drought characteristics
; Drought frequency analysis
; Mean and standard deviations
; National centers for environmental predictions
; Precipitation frequency
; Regional climate changes
; Regional climate modeling (RCM)
; Standardized precipitation index
; Climate models
; climate modeling
; climate prediction
; correction
; drought
; environmental assessment
; frequency analysis
; index method
; precipitation (climatology)
; precipitation assessment
; regional climate
; scenario analysis
; North America
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| 英文摘要: | Assessment of future drought characteristics based on climate models is difficult as climate models usually have bias in simulating precipitation frequency and intensity. In this study, we examine the significance of bias correction in the context of drought frequency and scenario analysis using output from climate models. In particular, we use three bias correction techniques with different emphases and complexities to investigate how they affect the results of drought frequency and severity based on climate models. The characteristics of drought are investigated using regional climate model (RCM) output from the North American Regional Climate Change Assessment Program (NARCCAP). The Standardized Precipitation Index (SPI) is used to compare and forecast drought characteristics at different timescales. Systematic biases in the RCM precipitation output are corrected against the National Centers for Environmental Prediction (NCEP) North American Regional Reanalysis (NARR) data and the bias-corrected RCM historical simulations. Preserving mean and standard deviation of NARR precipitation is essential in drought frequency analysis. The results demonstrate that bias correction significantly decreases the RCM errors in reproducing drought frequency derived from the NARR data. Different timescales of input precipitation in the bias corrections show similar results. The relative changes in drought frequency in future scenario compared to historical scenario are similar whether both scenarios are bias corrected or both are not bias corrected. © 2016, Springer Science+Business Media Dordrecht. |
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| 资源类型: | 期刊论文
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| 标识符: | http://119.78.100.158/handle/2HF3EXSE/84108
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| Appears in Collections: | 气候减缓与适应
气候变化事实与影响
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作者单位: | Department of Civil and Architectural Engineering, University of Wyoming, Laramie, WY, United States
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| Recommended Citation: | |
Aryal Y.,Zhu J.. On bias correction in drought frequency analysis based on climate models[J]. Climatic Change,2017-01-01,140(2018-03-04)
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