From the 1 of 4 linked papers with an AI index.
4 papers
HourGlass: A probabilistic data-driven temporal downscaler for global and regional weather forecasting
Magnus Sikora Ingstad, Mariana C. A. Clare, Olav Ersland +16
HourGlass is a probabilistic, data‑driven method that downscales 6‑hourly weather forecasts to hourly resolution, preserving small‑scale spatial detail and temporal consistency.
Enhancing a high resolution data-driven weather prediction model with surface descriptors
à smund Bakketun, Håvard Homleid Haugen, Jostein Blyverket +2
We study the importance of surface characteristics when forecasting near-surface variables with a data-driven weather prediction model. To target the challenge of predicting small-…
Pointwise is Pointless? A Multimodal Ablation Study for Precipitation Nowcasting with Graph Neural Networks
Ophélia Miralles, Máté Mile, Christoffer Artturi +2
Sparse point observations are increasingly available for precipitation nowcasting, but it is unclear how much they improve dense radar-field forecasts. We partially address this qu…
High-Resolution Probabilistic Data-Driven Weather Modeling with a Stretched-Grid
Even Marius Nordhagen, Håvard Homleid Haugen, HÃ¥vard Homleid Haugen +12
We present a probabilistic data-driven weather model providing ensembles of high spatial resolution realizations of 87 variables at arbitrary ensemble size and forecast length. The…