A Complete Density Correction using Normalizing Flows (CDC-NF) for CMIP6 GCMs.

ABSTRACT: Global Climate Models (GCMs) are essential for climate projections but often exhibit biases, particularly in representing extremes and multivariate dependencies, which limit their utility in impact assessments. Traditional bias correction (BC) methods, such as quantile mapping, address marginal distributions but fail to correct joint extremes and cross-variable relationships. To address these challenges, we propose a Complete Density Correction using Normalizing Flows (CDC-NF), a novel method leveraging invertible transformations to adjust the full joint distribution of GCM outputs. Using observational data from NOAA nClimGrid-daily and CMIP6 GCM projections, The CDC-NF method was applied at a daily temporal resolution to precipitation and maximum temperature outputs from CMIP6 GCM project

SUBMITTER: Fang S 

PROVIDER: S-EPMC12287353 | biostudies-literature | 2025 Jul

REPOSITORIES: biostudies-literature