Downscaled and bias corrected dataset for multiple GCMs and variables

Understanding the impact of climate variability and change is of great importance for developing adaptation and mitigation strategies. Coarse resolution data sets such as simulations of general circulation models (GCMs) are important for reconstructing historical climate and predicting the future. However, scale discrepancy and biases limit the coarse resolution data sets from being directly used for impact assessments and decision making. One solution for bridging this gap is to downscale and bias correct coarse resolution data to the local scale.