  Initial steps in statistical downscaling involve being able to compare
observed data from regional climate models (RCMs). This prediction requires (1)
regridding RCM output from their native grids and at differing spatial
resolutions to a common grid in order to be comparable to observed data and (2)
bias correcting RCM data, via quantile mapping, for example, for future
modeling and analysis. The uncertainty associated with (1) is not always
considered for downstream operations in (2). This work examines this
uncertainty, which is not often made available to the user of a regridded data
product. This analysis is applied to RCM solar radiation data from the
NA-CORDEX data archive and observed data from the National Solar Radiation
Database housed at the National Renewable Energy Lab. A case study of the
mentioned methods over California is presented.
