Data assimilation or machine learning?

Bonavita, Massimo ; Geer, Alan ; Laloyaux, Patrick ; Massart, Sébastien ; Chrust, Marcin

Année de publication
<p align="justify">Machine learning and deep learning (ML/DL) techniques have made remarkable advances in recent years in a large and ever-growing number of disparate application areas, such as natural language processing, computer vision, autonomous vehicles, healthcare, finance and many others. These advances have been driven by the huge increase in available data, the corresponding increase in computing power and the emergence of more effective and efficient algorithms. In Earth sciences in general, and numerical weather prediction (NWP) and climate prediction in particular, ML/DL uptake has been slow at first, but interest is rapidly growing. Today innovative applications of standard ML/DL tools and ideas are becoming increasingly common, and ECMWF has recently set out its approach in a 'roadmap for the next 10 years' (Düben et al., 2021).</p>

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