DOI: 10.1007/s10584-015-1559-z
Scopus记录号: 2-s2.0-84959099434
论文题名: Assessing the impact of CMIP5 climate multi-modeling on estimating the precipitation seasonality and timing
作者: Demirel M.C. ; Moradkhani H.
刊名: Climatic Change
ISSN: 0165-0009
EISSN: 1573-1480
出版年: 2016
卷: 135, 期: 2 起始页码: 357
结束页码: 372
语种: 英语
Scopus关键词: Bayesian networks
; Cells
; Cytology
; Precipitation (meteorology)
; River basin projects
; Watersheds
; Bayesian model averaging
; Coupled Model Intercomparison Project
; Daily time series
; Extreme precipitation events
; Global climate model
; Historical periods
; Mean absolute error
; Spatial disaggregation
; Climate models
; climate modeling
; environmental gradient
; error correction
; extreme event
; general circulation model
; precipitation assessment
; seasonality
; time series analysis
; Columbia Basin
英文摘要: This paper investigates the effect of a Bayesian Model Averaging (BMA) method on simulated precipitation over the Columbia River Basin using two statistically downscaled climate datasets, i.e., Bias-Correction Spatial Disaggregation (BCSD) and Multivariate Adaptive Constructed Analogs (MACA). To this end daily observed and simulated precipitation are used to calculate different indices focusing solely on seasonality, event-timing, and variability in timing (persistence) of the precipitation. The climate model weights are estimated for each cell (6 × 6 km) of the Columbia River Basin using daily time series for the historical period 1970–1999 from the ten Global Climate Models (GCMs) participating to the Coupled Model Intercomparison Project platform, Phase 5. The results show that BMA results in more than 15 % improvement/reduction in mean absolute error as compared to the individual GCMs. The improvement is, in general, higher for the MACA models than for the BCSD models. The results of variability in precipitation timing show that extreme precipitation events are mostly not persistent (i.e., occurring in different periods throughout the year), i.e., more than 75 % of the grid cells with an elevation above 900 m indicate persistence values less than 0.2 whereas nearly 70 % of the high elevation cells indicate such low persistence. Further we find that the variability in persistence is higher in high elevation cells than those with low elevation. The picture is different for MACA ensembles as the simulated persistence of extreme precipitation events is higher than that for the observed and BCSD datasets. © 2015, Springer Science+Business Media Dordrecht. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/84378
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 Environmental Engineering, Portland State University, Portland, OR, United States; Geological Survey of Denmark and Greenland, Øster Voldgade 10, Copenhagen, Denmark
Recommended Citation:
Demirel M.C.,Moradkhani H.. Assessing the impact of CMIP5 climate multi-modeling on estimating the precipitation seasonality and timing[J]. Climatic Change,2016-01-01,135(2)