188 citations · 539 across the 17 of their papers we have counts for
7 papers · 1 filter
IPSL-AID: Generative Diffusion Models for Climate Downscaling from Global to Regional Scales
Kishanthan Kingston, Olivier Boucher, Freddy Bouchet +5
Effective adaptation and mitigation strategies for climate change require high-resolution projections to inform strategic decision-making. Conventional global climate models, which…
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…
Neural Fields for Fast and Scalable Interpolation of Geophysical Ocean Variables
J. Emmanuel Johnson, Redouane Lguensat, Ronan Fablet +2
Optimal Interpolation (OI) is a widely used, highly trusted algorithm for interpolation and reconstruction problems in geosciences. With the influx of more satellite missions, we h…
Semi-automatic tuning of coupled climate models with multiple intrinsic timescales: lessons learned from the Lorenz96 model
Redouane Lguensat, Julie Deshayes, Homer Durand +1
The objective of this study is to evaluate the potential for History Matching (HM) to tune a climate system with multi-scale dynamics. By considering a toy climate model, namely, t…
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…
Filtering Internal Tides From Wide-Swath Altimeter Data Using Convolutional Neural Networks
Redouane Lguensat, Ronan Fablet, Julien Le Sommer +5
The upcoming Surface Water Ocean Topography (SWOT) satellite altimetry mission is expected to yield two-dimensional high-resolution measurements of Sea Surface Height (SSH), thus a…