4 papers
A Next-Generation Snow Albedo Parameterization for Climate Modeling using Constrained Machine Learning
Andrew Charbonneau, Katherine Deck, Tapio Schneider
We demonstrate a data-driven parameterization for snow albedo using a constrained neural differential equation that directly predicts a range of snow albedo tendencies from standar…
A Physics-Constrained Neural Differential Equation Framework for Data-Driven Snowpack Simulation
Andrew Charbonneau, Katherine Deck, Tapio Schneider
This paper presents a physics-constrained neural differential equation framework for parameterization, and employs it to model the time evolution of seasonal snow depth given hydro…
Surface to Seafloor: A Generative AI Framework for Decoding the Ocean Interior State
Andre N. Souza, Simone Silvestri, Katherine Deck +3
Understanding subsurface ocean dynamics is essential for quantifying oceanic heat and mass transport, but direct observations at depth remain sparse due to logistical and technolog…
Toward Routing River Water in Land Surface Models with Recurrent Neural Networks
Mauricio Lima, Katherine Deck, Oliver R. A. Dunbar +1
Machine learning is playing an increasing role in hydrology, supplementing or replacing physics-based models. One notable example is the use of recurrent neural networks (RNNs) for…