88 citations · 89 across the 4 of their papers we have counts for
4 papers
Tracing the space-time causal origins of Earth system extremes
Jhayron S. Pérez-Carrasquilla, J. Jake Nichol, Vanessa Robledo +4
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…
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…
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…
Astrophysical Fluid Dynamics via Direct Statistical Simulation
S. M. Tobias, K. Dagon, J. B. Marston
In this paper we introduce the concept of Direct Statistical Simulation (DSS) for astrophysical flows. This technique may be appropriate for problems in astrophysical fluids where…