|Title||Machine learning at ECMWF: A roadmap for the next 10 years|
|Publication Type||Technical memorandum|
|Secondary Title||ECMWF Technical Memoranda|
|Authors||Düben, P, Modigliani, U, Geer, A, Siemen, S, Pappenberger, F, Bauer, P, Brown, A, Palkovic, M, Raoult, B, Wedi, N, Baousis, V|
During the last decade, artificial intelligence (AI), machine learning, and data volume have developed at an unprecedented pace, and it is now evident that many scientific disciplines will need to revise their work modes to become more data centric in order to make the most out of these developments. AI and machine learning offer great opportunities throughout the workflow of numerical weather prediction (NWP) and climate services, and the science community is currently exploring how the new capabilities of AI and machine learning will change the future of Earth system science. First results show great potential.