The utility of daily large-scale climate data in the assessment of climate change impacts on daily streamflow in California

作者：Edwin P. Maurer, Hugo G. Hidalgo, T. K. Das, Michael D. Dettinger, Daniel R. Cayan · 发表于：Hydrology and earth system sciences · 年份：2010 · DOI：10.5194/hess-14-1125-2010 · 被引用次数：355 · 研究领域：Hydrology and Watershed Management Studies、Climate variability and models、Hydrology and Drought Analysis

Abstract. Three statistical downscaling methods were applied to NCEP/NCAR reanalysis (used as a surrogate for the best possible general circulation model), and the downscaled meteorology was used to drive a hydrologic model over California. The historic record was divided into an "observed" period of 1950–1976 to provide the basis for downscaling, and a "projected" period of 1977–1999 for assessing skill. The downscaling methods included a bias-correction/spatial downscaling method (BCSD), which relies solely on monthly large scale meteorology and resamples the historical record to obtain daily sequences, a constructed analogues approach (CA), which uses daily large-scale anomalies, and a hybrid method (BCCA) using a quantile-mapping bias correction on the large-scale data prior to the CA approach. At 11 sites we compared three simulated daily flow statistics: streamflow timing, 3-day peak flow, and 7-day low flow. While all downscaling methods produced reasonable streamflow statistics at most locations, the BCCA method consistently outperformed the other methods, capturing the daily large-scale skill and translating it to simulated streamflows that more skillfully reproduced observationally-driven streamflows.