399 citations · 2.6k across the 69 of their papers we have counts for
72 papers
AI Emulation of Stochastic Sudden Stratospheric Warming with Interpretable Latent Structure
C. Daniel Boscu, Daniel Hernandez, Fabio Alvarez Ventura +4
Rare weather regime transitions pose a challenge for data-driven modeling due to class imbalance. In this study, we develop a probabilistic deep learning emulator for a prototypica…
Explaining El Niño Forecasts with the Average Gradient Outer Product
Yuan Hui, Dorian S. Abbot, Robert J. Webber
An important and unresolved problem in the physical sciences is explaining the predictions made by neural networks. Several explainable artificial intelligence (XAI) methods have b…
Optimizing Geoengineering Interventions Using Differentiable Climate Models
Pulkit Dubey, Dorian S. Abbot, Ashesh Chattopadhyay
The deployment of a geoengineering program to cool Earth's climate may be imminent. It is crucial that tools be developed to ensure that such a program would achieve its objectives…
The Effect of Planetary Rotation Period on Clouds in a Global Climate Model with a Bin Microphysics Scheme
Huanzhou Yang, Eric T. Wolf, Cheng-Cheng Liu +3
Clouds are the largest source of uncertainty in climate simulations. For exoplanets, cloud simulation is particularly challenging because of the lack of observational data to tune…
Seafloor Weathering and Stochastic Outgassing Unlikely to Significantly Shorten the Future Lifespan of Earth's Terrestrial Biosphere
Livia Zhu, R. J. Graham, Dorian S. Abbot
Current understanding suggests that as the Sun brightens in the far future, Earth's carbonate-silicate cycle will offset increasing temperatures by drawing CO out of the atmosp…
Using a rare event sampling technique to quantify extreme El Niño event statistics
Sarah Packman, Justin Finkel, Dorian S. Abbot +1
Extreme El Niño events, such as occurred in 1997--1998, can induce severe weather on a global scale, with significant socioeconomic impacts that motivate efforts to understand them…