3 papers
physics.ao-ph2026
Tracing the space-time causal origins of Earth system extremes
Jhayron S. Pérez-Carrasquilla, Jhayron S. Pérez-Carrasquilla, J. Jake Nichol +5
Identifying the causes of Earth's extremes is challenging because counterfactual experiments are not possible in the observed world. Data-driven causal discovery complements comput…
cs.LG2025
Recommendations for Comprehensive and Independent Evaluation of Machine Learning-Based Earth System Models
Paul A. Ullrich, Elizabeth A. Barnes, William D. Collins +9
Machine learning (ML) is a revolutionary technology with demonstrable applications across multiple disciplines. Within the Earth science community, ML has been most visible for wea…
physics.ao-ph2024
Can Transfer Learning be Used to Identify Tropical State-Dependent Bias Relevant to Midlatitude Subseasonal Predictability?
Kirsten J. Mayer, Katherine Dagon, Maria J. Molina
Previous research has demonstrated that specific states of the climate system can lead to enhanced subseasonal predictability (i.e., state-dependent predictability). However, biase…