An extremes-weighted empirical quantile mapping for global climate model data bias correction for improved emphasis on extremes

Accuracy in the global climate model (GCM) projections is essential for developing reliable impact mitigation strategies. The conventional bias correction methods used to improve this accuracy often fail to capture the extremes, specifically for precipitation, due to the generic correction applicati...

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