期刊
INTERNATIONAL JOURNAL OF CLIMATOLOGY
卷 27, 期 12, 页码 1643-1655出版社
WILEY
DOI: 10.1002/joc.1602
关键词
statistical downscaling; dynamical downscaling; hydrological impacts; climate change; regional climate; bias correction
Two downscaling methods designed for the study of the hydrological impact of climate change on the Seine basin in France are tested for present climate. First, a multivariate statistical downscaling (SD) methodology based on weather typing and conditional resampling is described. Then, a bias correction technique for dynamical downscaling based on quantile-quantile mapping is introduced. To evaluate the end-to-end SD methodology, the atmospheric forcing derived from the large-scale circulation (LSC) of the ERA40 reanalysis by SD is used to force a hydrological model. Simulated discharges reproduce historical values reasonably well. Next, the dynamical and statistical approaches are compared using the Meteo-France ARPEGE general circulation model in a variable resolution configuration (resolution around 60 km over France). The ARPEGE simulation is downscaled using the two methodologies, and hydrological simulations are performed. Regarding downscaled temperature and precipitation, the statistical approach is more efficient in reproducing the temporal and spatial autocorrelation properties. The simulated river discharges from the two approaches are nevertheless very similar: the two methods reproduce well the seasonal cycle and the daily distribution of streamflows. Finally, the results of the study are discussed from a practical impact study perspective. Copyright (C) 2007 Royal Meteorological Society
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据