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arXiv (Cornell University)
GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations
December 2024 • Mihai Alexe, Eulalie Boucher, Peter Lean, Ewan Pinnington, Patrick Laloyaux, A. P. McNally, Simon Lang, Matthew Chantry, C. J. Burrows, Marcin Chrust…
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 exclusively from Earth System observations, with no physics-based (re)analysis inputs or feedbacks. GraphDOP learns the correlations between observed quantities - such as brightness temperatures from polar orbiters and geostationary satellites - and geophysical quantities of interest (that are measured by conventional observations), to form…
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