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From the 1 of 4 linked papers with an AI index.

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4 papers

stat.ME2026

Spatiotemporally Consistent Multivariate Bias Correction for Climate Projections via Nested Vine Copulas

Theresa Meier, Erwan Koch, Valérie Chavez-Demoulin +1

The paper introduces GN-VBC, a multivariate bias correction method that separates deterministic spatiotemporal effects using GAMs and captures joint dependencies with nested vine c…

physics.ao-ph2026

SwAIther-Precip: Lead-Time-Aware Bias Correction Enables Kilometer-Scale Downscaling of Global AI Precipitation Forecasts over Switzerland

Dan Assouline, Erwan Koch, Federico Amato +5

Skillful medium-range precipitation forecasting at kilometer scale remains challenging over complex terrain because precipitation arises from multiscale nonlinear processes that gl…

physics.ao-ph2026

Investigating the Robustness of Extreme Precipitation Super-Resolution Across Climates

Louise Largeau, Tom Beucler, David Leutwyler +3

The coarse spatial resolution of gridded climate models, such as general circulation models, limits their direct use in projecting socially relevant variables like extreme precipit…

physics.ao-ph2025

Improving Predictions of Convective Storm Wind Gusts through Statistical Post-Processing of Neural Weather Models

Antoine Leclerc, Erwan Koch, Monika Feldmann +2

Issuing timely severe weather warnings helps mitigate potentially disastrous consequences. Recent advancements in Neural Weather Models (NWMs) offer a computationally inexpensive a…