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@@ -22,7 +22,7 @@ The assumption that historical model “fidelity” ([Shukla et al. 2006](https:
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The REF functions best as an entry point for deeper investigation into CMIP models.
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It serves three primary purposes for the CMIP user community:
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* REF diagnostics give a broad overview of the spread across models in terms of global metrics.
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* REF diagnostics give a broad overview of the spread across models in terms of calculated metrics.
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* REF diagnostics can be useful for identifying a subset of models to answer a specific research question, by examining diagnostic criteria related to model performance in key processes or regions relevant to the study.
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* REF outputs can be used to inform model selection for downscaling applications ([Sobolowski et al. 2025](https://doi.org/10.1175/BAMS-D-23-0189.1.))
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and multi-model weighting schemes ([Merrifield et al. 2023](https://doi.org/10.5194/gmd-16-4715-2023)),
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