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Evaluation of CMIP6 GCMs over the CONUS for downscaling studies
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  • Moetasim Ashfaq,
  • Deeksha Rastogi,
  • Muhammad Adnan Abid,
  • Shih-Chieh Kao
Moetasim Ashfaq
Oak Ridge National Laboratory (DOE)

Corresponding Author:[email protected]

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Deeksha Rastogi
Oak Ridge National Laboratory
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Muhammad Adnan Abid
The Abdus Salam International Centre for Theoretical Physics
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Shih-Chieh Kao
Oak Ridge National Laboratory
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Despite the necessity of Global Climate Models (GCMs) sub-selection in the dynamical downscaling experiments, an objective approach for their selection is currently lacking. Building on the previously established concepts in GCMs evaluation frameworks, we relatively rank 37 GCMs from the 6th phase of Coupled Models Intercomparison Project (CMIP6) over four regions representing the contiguous United States (CONUS). The ranking is based on their performance across 60 evaluation metrics in the historical period (1981–2014). To ensure that the outcome is not method-dependent, we employ two distinct approaches to remove the redundancy in the evaluation criteria. The first approach is a simple weighted averaging technique. Each GCM is ranked based on its weighted average performance across evaluation measures, after each metric is weighted between zero and one depending on its uniqueness. The second approach applies empirical orthogonal function analysis in which each GCM is ranked based on its sum of distances from the reference in the principal component space. The two methodologies work in contrasting ways to remove the metrics redundancy but eventually develop similar GCMs rankings. While the models from the same institute tend to display comparable skills, the high-resolution model versions distinctively perform better than their lower-resolution counterparts. The results from this study should be helpful in the selection of models for dynamical downscaling efforts, such as the COordinated Regional Downscaling Experiment (CORDEX), and in understanding the strengths and deficiencies of CMIP6 GCMs in the representation of various background climate characteristics across CONUS.