5 papers
DLESyM-Ocean: A Deep Learning Probabilistic Global Model for Simulating Present-Day Upper Ocean and Sea Ice
Zachary I Espinosa, Nathaniel Cresswell-Clay, William Yik +6
While AI has shown remarkable promise in atmospheric and meteorological forecasting, accurately simulating other components of the Earth system with AI remains an active frontier.…
Imposing the Fundamental Dynamical Constraint of Hydrostatic Balance to Improve Global ML Weather Prediction
Akshay Subramaniam, Dale Durran, David Pruitt +2
Forecasting weather accurately and efficiently is a critical capability in our ability to adapt to climate change. Data driven approaches to this problem have enjoyed much success…
Enforcing Equity in Neural Climate Emulators
William Yik, Sam J. Silva
Neural network emulators have become an invaluable tool for a wide variety of climate and weather prediction tasks. While showing incredibly promising results, these networks do no…
Southern Ocean Dynamics Under Climate Change: New Knowledge Through Physics-Guided Machine Learning
William Yik, Maike Sonnewald, Mariana C. A. Clare +1
Complex ocean systems such as the Antarctic Circumpolar Current play key roles in the climate, and current models predict shifts in their strength and area under climate change. Ho…
Exploring Randomly Wired Neural Networks for Climate Model Emulation
William Yik, Sam J. Silva, Andrew Geiss +1
Exploring the climate impacts of various anthropogenic emissions scenarios is key to making informed decisions for climate change mitigation and adaptation. State-of-the-art Earth…