DOI: 10.1007/s00382-012-1627-2
Scopus记录号: 2-s2.0-84875740439
论文题名: Assessment of a stochastic downscaling methodology in generating an ensemble of hourly future climate time series
作者: Fatichi S. ; Ivanov V.Y. ; Caporali E.
刊名: Climate Dynamics
ISSN: 9307575
出版年: 2013
卷: 40, 期: 2017-07-08 起始页码: 1841
结束页码: 1861
语种: 英语
英文关键词: Firenze
; Italy
; Stochastic downscaling
; Uncertainty assessment
; Weather generator
英文摘要: This study extends a stochastic downscaling methodology to generation of an ensemble of hourly time series of meteorological variables that express possible future climate conditions at a point-scale. The stochastic downscaling uses general circulation model (GCM) realizations and an hourly weather generator, the Advanced WEather GENerator (AWE-GEN). Marginal distributions of factors of change are computed for several climate statistics using a Bayesian methodology that can weight GCM realizations based on the model relative performance with respect to a historical climate and a degree of disagreement in projecting future conditions. A Monte Carlo technique is used to sample the factors of change from their respective marginal distributions. As a comparison with traditional approaches, factors of change are also estimated by averaging GCM realizations. With either approach, the derived factors of change are applied to the climate statistics inferred from historical observations to re-evaluate parameters of the weather generator. The re-parameterized generator yields hourly time series of meteorological variables that can be considered to be representative of future climate conditions. In this study, the time series are generated in an ensemble mode to fully reflect the uncertainty of GCM projections, climate stochasticity, as well as uncertainties of the downscaling procedure. Applications of the methodology in reproducing future climate conditions for the periods of 2000-2009, 2046-2065 and 2081-2100, using the period of 1962-1992 as the historical baseline are discussed for the location of Firenze (Italy). The inferences of the methodology for the period of 2000-2009 are tested against observations to assess reliability of the stochastic downscaling procedure in reproducing statistics of meteorological variables at different time scales. © 2012 Springer-Verlag Berlin Heidelberg. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/55061
Appears in Collections: 过去全球变化的重建
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作者单位: Department of Civil and Environmental Engineering, University of Firenze, Florence, Italy; Institute of Environmental Engineering, ETH Zürich, Wolfgang-Pauli-Str. 15, HIL D 23.2, 8093 Zurich, Switzerland; Department of Civil and Environmental Engineering, University of Michigan, 1351 Beal Avenue, 105 EWRE, Ann Arbor, MI, United States
Recommended Citation:
Fatichi S.,Ivanov V.Y.,Caporali E.. Assessment of a stochastic downscaling methodology in generating an ensemble of hourly future climate time series[J]. Climate Dynamics,2013-01-01,40(2017-07-08)