arXiv:2608. 12271v1 Announce Type: new Abstract: Global weather reanalyses and forecasts resolve the evolving atmospheric state on coarse grids, but site-specific applications require predictions at arbitrary locations where near-surface conditions also depend on unresolved terrain and land-surface properties.
By Pedro Sousa (Department of Computer Science, University of Cambridge), Will Tebbutt (Department of Engineering, University of Cambridge), Sadiq Jaffer (Department of Computer Science, University of Cambridge), Robin Young (Department of Computer Science, University of Cambridge), Anil Madhavapeddy (Department of Computer Science, University of Cambridge), Richard E. Turner (Department of Engineering, University of Cambridge)
arXiv:2607. 03279v1 Announce Type: new Abstract: Accurate regional weather prediction requires resolving fine-scale structure while remaining consistent with global dynamics.
By Wiktor Kamzela, Jakub Kubiak, Adam Dobosz, J\k{e}drzej Miczke, Anatol Kaczmarek, Piotr Wyrwi\'nski, Wojciech Stefaniak, Wojciech Kot{\l}owski
Varda‑single‑1.0 is a medium‑range, data‑driven weather prediction system designed for Switzerland’s Alpine region, delivering hourly deterministic forecasts at 1 km resolution and global forecasts at 31 km. It uses two independently trained stretched‑grid Graph Transformer models—an autoregressive forecaster and a temporal downscaler—trained through a curriculum that starts with ERA5 reanalysis, proceeds to a 20‑year regional reanalysis, and ends with fine‑tuning on operational analyses. Over a one‑year verification, Varda‑single matches or surpasses MeteoSwiss’s numerical weather prediction baselines for most key metrics, though it underestimates local wind peaks and produces smoother convective precipitation fields.
whyItMatters":"The system demonstrates that high‑resolution machine‑learning models can rival traditional numerical weather prediction in complex terrain, offering a complementary tool for operational forecasting and research."
By Alberto Pennino, Francesco Zanetta, Michele Cattaneo, Claire Merker, Radi Radev, Jonas Bhend, Louis Frey, Hugues de Laroussilhe, Oph\'elia Miralles, Carlos Osuna, Daniele Nerini, Andreas Pauling, Daniel Hupp, Ulrich Hamann, Mary McGlohon, Marti Bosch, Luca Lanzilao, Marco Arpagaus, Lukas Jansing, Daniel Leuenberger, Mark A. Liniger, Katrin Ehlert, Matthew Chantry, H\aa{}vard Homleid Haugen, Gert Mertes, Ana Prieto Nemesio, Mario Santa Cruz, Jasper Wijnands, Gabriel Moldovan, Harrison Cook, Oliver Fuhrer
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 glob...
arXiv:2605. 16163v2 Announce Type: replace-cross Abstract: Skillful medium-range precipitation forecasting at kilometer scale remains challenging over complex terrain because precipitation arises from multiscale nonlinear processes that global models cannot explicitly resolve at affordable cost.
By Dan Assouline, Erwan Koch, Federico Amato, Filippo Quarenghi, Daniele Nerini, Thibaut Loiseau, Kyle van de Langemheen, Tom Beucler
arXiv:2605. 13566v2 Announce Type: replace Abstract: Land Surface Temperature (LST) is a key variable for various applications, such as urban climate and ecology studies.
By Solomiia Kurchaba, Angela Meyer