301 citations · 518 across the 5 of their papers we have counts for
5 papers
Machine learning for climate physics and simulations
Ching-Yao Lai, Pedram Hassanzadeh, Aditi Sheshadri +3
We discuss the emerging advances and opportunities at the intersection of machine learning (ML) and climate physics, highlighting the use of ML techniques, including supervised, un…
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…
Explainable Artificial Intelligence for Bayesian Neural Networks: Towards trustworthy predictions of ocean dynamics
Mariana C. A. Clare, Maike Sonnewald, Redouane Lguensat +2
The trustworthiness of neural networks is often challenged because they lack the ability to express uncertainty and explain their skill. This can be problematic given the increasin…
Bridging observation, theory and numerical simulation of the ocean using Machine Learning
Maike Sonnewald, Redouane Lguensat, Daniel C. Jones +3
Progress within physical oceanography has been concurrent with the increasing sophistication of tools available for its study. The incorporation of machine learning (ML) techniques…
Will Artificial Intelligence supersede Earth System and Climate Models?
Christopher Irrgang, Niklas Boers, Maike Sonnewald +4
We outline a perspective of an entirely new research branch in Earth and climate sciences, where deep neural networks and Earth system models are dismantled as individual methodolo…