Effects of univariate and multivariate statistical downscaling methods on climatic and hydrologic indicators for Alberta, Canada

Statistical downscaling methods have been actively developed to improve the applicability of global climate models’ (GCMs) outputs to impact studies at a local scale. This study presents a multivariate bias correction (MBC) method that preserves GCM-driven climate change signals and the interdependence between hydro-climate variables by combining the quantile delta mapping (QDM) method with distribution-free shuffle approach, refer to as MBCDS. …