Quantifying internal variability in large-ensemble climate data with the Wasserstein distance
This paper proposes a robust, parameter-free metric based on the 1-Wasserstein distance to quantify the relative magnitude of internal variability in large-ensemble climate data, demonstrating its superior stability and clarity compared to existing methods across various distribution shapes and forcing scenarios.