  Bias correction is a common pre-processing step applied to climate model data
before it is used for further analysis. This article introduces an efficient
adaptation of a well-established bias-correction method - quantile mapping -
for global horizontal irradiance (GHI) that ensures corrected data is
physically plausible through incorporating measurements of clearsky GHI. The
proposed quantile mapping method is fit on reanalysis data to first bias
correct for regional climate models (RCMs) and is tested on RCMs forced by
general circulation models (GCMs) to understand existing biases directly from
GCMs. Additionally, we adapt a functional analysis of variance methodology that
analyzes sources of remaining biases after implementing the proposed quantile
mapping method and considered biases by climate region. This analysis is
applied to four sets of climate model output from NA-CORDEX and compared
against data from the National Solar Radiation Database produced by the
National Renewable Energy Lab.
