activity
20242026
most citedAIFS -- ECMWF's data-driven forecasting system

75 citations · 99 across the 14 of their papers we have counts for

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Showing 2024Show all

5 papers · 1 filter

physics.ao-ph2024★ 9 cited

AIFS-CRPS: Ensemble forecasting using a model trained with a loss function based on the Continuous Ranked Probability Score

Simon Lang, Mihai Alexe, Mariana C. A. Clare +15

Over the last three decades, ensemble forecasts have become an integral part of forecasting the weather. They provide users with more complete information than single forecasts as…

physics.ao-ph2024★ 3 cited

GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations

Mihai Alexe, Eulalie Boucher, Peter Lean +11

We introduce GraphDOP, a new data-driven, end-to-end forecast system developed at the European Centre for Medium-Range Weather Forecasts (ECMWF) that is trained and initialised exc…

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-ph2024★ 5 cited

Data driven weather forecasts trained and initialised directly from observations

Anthony McNally, Christian Lessig, Peter Lean +11

Skilful Machine Learned weather forecasts have challenged our approach to numerical weather prediction, demonstrating competitive performance compared to traditional physics-based…

physics.ao-ph2024★ 75 cited

AIFS -- ECMWF's data-driven forecasting system

Simon Lang, Mihai Alexe, Matthew Chantry +13

Machine learning-based weather forecasting models have quickly emerged as a promising methodology for accurate medium-range global weather forecasting. Here, we introduce the Artif…