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Towards machine learning in operational weather forecasting

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Machine learning has emerged as a powerful tool in a variety of applications. Recently academia, meteorological centres and technology companies alike have asked the question of whether machine learning can be a force for good in weather forecasting. First I will review the recent flurry of work in this domain, which run the gamut from the incremental to the systemic. Building on this I will highlight some of the approaches that ECMWF are exploring for incorporating machine learning into a weather forecasting workflow. Finally I will look forward to the roadmap and challenges ahead for taking these approaches into operations.

This talk is part of the Geophysical and Environmental Processes series.

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