Author

D. Abbot

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Preprint Oct 2026

Explaining El Ni\~no Forecasts with the Average Gradient Outer Product

An important and unresolved problem in the physical sciences is explaining the predictions made by neural networks. Several explainable artificial intelligence (XAI) methods have been proposed to address this problem, including gradient XAI, Integrated Gradients, and GradientSHAP. We evaluate the baseline XAI methods a...

Yu-Wen Hui, D. Abbot, Robert J. Webber · 0 citations

Open access Sep 2026

Paleogeographic controls on Phanerozoic weathering rates and implications for climate regulation

Earth’s climate has remained habitable for billions of years, a stability usually attributed to a negative feedback from silicate weathering – the chemical breakdown of silicate rocks on land, which consumes atmospheric carbon dioxide faster as climate warms. However, whether temperature or hydrology primarily drives t...

R. J. Graham, B. Cael, M. Fu et al. · Nature Communications · 0 citations

#artificial intelligence Preprint Sep 2026

Optimizing Geoengineering Interventions Using Differentiable Climate Models

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 while minimizing disruption. Here we exploit recently developed differentiable atmospheric models to demonstrate a novel geoengineering con...

Pulkit Dubey, D. Abbot, Ashesh Chattopadhyay · 0 citations