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20232026
most citedRegional data-driven weather modeling with a global stretched-grid

5 citations · 7 across the 6 of their papers we have counts for

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physics.ao-ph2026

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…

physics.ao-ph2026

Enhancing a high resolution data-driven weather prediction model with surface descriptors

Åsmund 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-…

physics.ao-ph2025★ 1 cited

High-Resolution Probabilistic Data-Driven Weather Modeling with a Stretched-Grid

Even Marius Nordhagen, Håvard Homleid Haugen, Magnus Sikora Ingstad +9

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…

physics.ao-ph2024★ 5 cited

Regional data-driven weather modeling with a global stretched-grid

Thomas Nils Nipen, Håvard Homleid Haugen, Magnus Sikora Ingstad +11

A data-driven model (DDM) suitable for regional weather forecasting applications is presented. The model extends the Artificial Intelligence Forecasting System by introducing a str…

physics.ao-ph2023★ 1 cited

Evaluation of forecasts by a global data-driven weather model with and without probabilistic post-processing at Norwegian stations

John Bjørnar Bremnes, Thomas N. Nipen, Ivar A. Seierstad

During the last two years, tremendous progress in global data-driven weather models trained on numerical weather prediction (NWP) re-analysis data has been made. The most recent mo…