Evaluation of bias correction techniques for generating high-resolution daily temperature projections from CMIP6 models

Due to the considerable biases in general circulation models (GCMs) simulation, bias correction methods are required and widely applied reduce model for impact studies. This study evaluated performance of two methods, quantile delta mapping (QDM) scaled distribution (SDM), generating high-resolution daily maximum temperature (Tmax) minimum (Tmin) projections Canada using latest GCMs from Coupled Model Intercomparison Project phase 6 (CMIP6). CMIP6 show overall consistency with observations before after correction, better on Tmax compared Tmin. QDM shows relative while SDM superior skill preserving raw climate signals. effective reducing Tmin all GCMs. Both similar skills reproducing monthly probability capturing seasonal spatial patterns over Canada. Multi-model ensemble means have good simulating mean but poor high low quantiles as well standard deviation. corrected best performance. presents a comprehensive assessment applications individual their multi-model predictions Canada, providing reference significance studies technical support further adaptation planning around world.