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physics.ao-ph2026
Understanding Perturbed Parameter Ensemble Sensitivities Using A Contrastive Learning Approach
Da Fan, David John Gagne, Gregory S Elsaesser +5
Perturbed parameter ensembles (PPEs) reveal how physics parameters affect climate simulations, but interpreting parameter sensitivities across multivariate, spatially structured ou…
physics.ao-ph2025
Calibrating Geophysical Predictions under Constrained Probabilistic Distributions
Zhewen Hou, Jiajin Sun, Subashree Venkatasubramanian +3
Machine learning (ML) has shown significant promise in studying complex geophysical dynamical systems, including turbulence and climate processes. Such systems often display sensit…