3 citations · 4 across the 3 of their papers we have counts for
8 papers
AI-boosted rare event sampling to characterize extreme weather
Amaury Lancelin, Alex Wikner, Laurent Dubus +5
Weather extremes pose major societal risks, especially in a changing climate, but due to their rarity, they are difficult to study using limited observations or complex climate mod…
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…
Rare events algorithm study of extreme double jet summers and their connection to heatwaves over the Northern Hemisphere
Valeria Mascolo, Francesco Ragone, Nili Harnik +1
Several large scale circulation patterns have been identified in relation to extreme Northern Hemisphere summer heatwaves. Three main ones are a double jet over Eurasia, a positive…
Tackling the Accuracy-Interpretability Trade-off in a Hierarchy of Machine Learning Models for the Prediction of Extreme Heatwaves
Alessandro Lovo, Amaury Lancelin, Corentin Herbert +1
When performing predictions that use Machine Learning (ML), we are mainly interested in performance and interpretability. This generates a natural trade-off, where complex models g…
Gaussian Framework and Optimal Projection of Weather Fields for Prediction of Extreme Events
Valeria Mascolo, Alessandro Lovo, Corentin Herbert +1
Extreme events are the major weather-related hazard for humanity. It is then of crucial importance to have a good understanding of their statistics and to be able to forecast them.…
The role of edge states for early-warning of tipping points
Johannes Lohmann, Alfred B. Hansen, Alessandro Lovo +3
Tipping points (TP) are often described as low-dimensional bifurcations, and are associated with early-warning signals (EWS) due to critical slowing down (CSD). CSD is an increase…