collaborators

17 papers

physics.ao-ph20263 cited

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…

physics.ao-ph2026

Rigorous uncertainty quantification of probabilistic AI weather forecasts with conformal prediction

Anna Asch, Raphael Rossellini, Pedram Hassanzadeh +1

Probabilistic weather forecasting is undergoing rapid transformation with artificial intelligence (AI). In traditional numerical weather prediction, computing power can limit how w…

physics.flu-dyn2026

Semi-analytical eddy-viscosity and backscattering closures for 2D geophysical turbulence

Yifei Guan, Pedram Hassanzadeh

Physics-based eddy-viscosity and backscattering closures are widely used for large-eddy simulation (LES) of geophysical turbulence, but their key parameters are often chosen empiri…

cs.LG2026

Designing probabilistic AI monsoon forecasts to inform agricultural decision-making

Colin Aitken, Rajat Masiwal, Adam Marchakitus +7

Hundreds of millions of farmers make high-stakes decisions under uncertainty about future weather. Forecasts can inform these decisions, but available choices and their risks and b…

physics.geo-ph2026

Prediction of Extreme Events in Multiscale Simulations of Geophysical Turbulence using Reinforcement Learning

Yifei Guan, Lucas Amoudruz, Sergey Litvinov +4

Accurate subgrid-scale closures are essential for weather/climate models, where predicting extreme events is critical. Traditional closures have structural errors, e.g., producing…

cs.LG2026

Decision-oriented benchmarking to transform AI weather forecast access: Application to the Indian monsoon

Rajat Masiwal, Colin Aitken, Adam Marchakitus +9

Artificial intelligence weather prediction (AIWP) models now often outperform traditional physics-based models on common metrics while requiring orders-of-magnitude less computing…