physics.ao-ph · 2026-10-02 · No. 131
Atmospheric and Oceanic Physics, 2026-10-02.
2 new papers in physics.ao-ph. Titles, authors,
abstracts. Links to arXiv. Want this in your inbox every morning? Subscribe →
01 — The papers
2 entries-
01
AI Emulation of Stochastic Sudden Stratospheric Warming with Interpretable Latent Structure
C. Daniel Boscu, Daniel Hernandez, Fabio Alvarez Ventura, Justin Finkel, Ashesh Chattopadhyay, Pedram Hassanzadeh,...
physics.ao-ph · cs.LG
Rare weather regime transitions pose a challenge for data-driven modeling due to class imbalance. In this study, we develop a probabilistic deep learning emulator for a prototypical system with regime transitions, the stochastic Holton--Mass model of stratospheric variability, and analyze the structure of its learned latent space. The Holton--Mass model exhibits two metastable regimes, a strong and a weak polar vortex, maintained by nonlinear...
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02
Varda-single-1.0: deterministic data-driven weather forecasting at 1 km resolution over Switzerland's complex topography
Alberto Pennino, Francesco Zanetta, Michele Cattaneo, Claire Merker, Radi Radev, Jonas Bhend, Louis Frey, Hugues de...
physics.ao-ph · cs.LG
We present Varda-single-1.0, a medium-range data-driven weather prediction system built for the Alpine domain. It provides hourly deterministic regional forecasts on a mesh of 1 km resolution and global forecasts on a 31 km mesh. The system comprises two independently trained stretched-grid Graph Transformer models with encoder-processor-decoder architecture, developed in the Anemoi framework: a 6-hourly autoregressive forecaster and a...
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