Using Natural Variability as a Baseline to Evaluate the Performance of Bias Correction Methods in Hydrological Climate Change Impact Studies

摘要: AbstractPostprocessing of climate model outputs is usually performed to remove biases prior performing change impact studies. The evaluation the performance bias correction methods routinely done by comparing postprocessed observed data. However, such an approach does not take into account inherent uncertainty linked natural variability and may end up recommending unnecessary complex postprocessing methods. This study evaluates using as a baseline. baseline implies that any between simulations observations only significant if it larger than variability. Four are evaluated with respect reproducing set climatic hydrological statistics. When baseline, still outperform simplest ones for precipitation temperature time series, although differences ar...