DOI: 10.1175/JCLI-D-15-0439.1
Scopus记录号: 2-s2.0-84959521012
论文题名: The influence of climate model biases on projections of aridity and drought
作者: Ficklin D.L. ; Abatzoglou J.T. ; Robeson S.M. ; Dufficy A.
刊名: Journal of Climate
ISSN: 8948755
出版年: 2016
卷: 29, 期: 4 起始页码: 1369
结束页码: 1389
语种: 英语
Scopus关键词: Climate change
; Drought
; Systematic errors
; Climate condition
; Global climate model
; High resolution
; Historical simulation
; Hydrological impacts
; Impact analysis
; Palmer drought severity indices
; Western United States
; Climate models
; aridity
; climate modeling
; climate prediction
; drought
; ensemble forecasting
; United States
英文摘要: Global climate models (GCMs) have biases when simulating historical climate conditions, which in turn have implications for estimating the hydrological impacts of climate change. This study examines the differences in projected changes of aridity [defined as the ratio of precipitation (P) over potential evapotranspiration (PET), or P/PET] and the Palmer drought severity index (PDSI) between raw and bias-corrected GCM output for the continental United States (CONUS). For historical simulations (1950-79) the raw GCM ensemble median has a positive precipitation bias (124%) and negative PET bias (27%) compared to the bias-corrected output when averaged over CONUS with the most acute biases over the interior western United States. While both raw and bias-corrected GCM ensembles project more aridity (lower P/PET) for CONUS in the late twenty-first century (2070-99), relative enhancements in aridity were found for biascorrected data compared to the raw GCM ensemble owing to positive precipitation and negative PET biases in the raw GCM ensemble. However, the bias-corrected GCM ensemble projects less acute decreases in summer PDSI for the southwestern United States compared to the raw GCM ensemble (from 1 to 2 PDSI units higher), stemming from biases in precipitation amount and seasonality in the raw GCM ensemble. Compared to the raw GCM ensemble, bias-corrected GCM inputs not only correct for systematic errors but also can produce high-resolution projections that are useful for impact analyses. Therefore, changes in hydroclimate metrics often appear considerably different in bias-corrected output compared to raw GCM output. © 2016 American Meteorological Society. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/50126
Appears in Collections: 气候变化事实与影响
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作者单位: Department of Geography, Indiana University, Bloomington, IN, United States; Department of Geography, University of Idaho, Moscow, ID, United States; Department of Geography, Indiana University, Bloomington, IN, United States; Geological Sciences, Indiana University, Bloomington, IN, United States
Recommended Citation:
Ficklin D.L.,Abatzoglou J.T.,Robeson S.M.,et al. The influence of climate model biases on projections of aridity and drought[J]. Journal of Climate,2016-01-01,29(4)