4 citations · 5 across the 5 of their papers we have counts for
5 papers · 1 filter
Varda-single-1.0: deterministic data-driven weather forecasting at 1 km resolution over Switzerland's complex topography
Alberto Pennino, Francesco Zanetta, Michele Cattaneo +28
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…
Efficient Analog-Initialized Latent Transport for Spatially Coherent Probabilistic Downscaling from Global to Kilometer Scales
Ophélia Miralles
Probabilistic downscaling must represent kilometer-scale structure left unresolved by a deterministic regional prediction. We introduce an analog-initialized latent transport metho…
Exploring the role of input data on hail nowcast skill using spatiotemporal neural networks
George Pacey, Ophélia Miralles, Ulrich Hamann +1
Hail can cause large financial losses and poses risks to public safety, making reliable nowcasts essential for timely warnings. Deep-learning approaches have emerged as a strong al…
HourGlass: A probabilistic data-driven temporal downscaler for global and regional weather forecasting
Magnus Sikora Ingstad, Mariana C. A. Clare, Olav Ersland +16
Many forecast applications require high frequency temporal resolution, yet most state-of-the-art data-driven weather forecasting systems operate at 6-hourly resolution. Although di…
Observation-guided Interpolation Using Graph Neural Networks for High-Resolution Nowcasting in Switzerland
Ophélia Miralles, Daniele Nerini, Jonas Bhend +2
Recent advances in neural weather forecasting have shown significant potential for accurate short-term forecasts. However, adapting such gridded approaches to smaller, topographica…