Advances in Statistical Climatology, Meteorology and Oceanography (Dec 2023)

Regridding uncertainty for statistical downscaling of solar radiation

  • M. D. Bailey,
  • M. D. Bailey,
  • D. Nychka,
  • M. Sengupta,
  • A. Habte,
  • Y. Xie,
  • S. Bandyopadhyay

DOI
https://doi.org/10.5194/ascmo-9-103-2023
Journal volume & issue
Vol. 9
pp. 103 – 120

Abstract

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Initial steps in statistical downscaling involve being able to compare observed data from regional climate models (RCMs). This prediction requires (1) regridding RCM outputs 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, for example via quantile mapping, 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 (North American Coordinated Regional Climate Downscaling Experiment) 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.