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Here, we demonstrate that data-driven methods are now positioned to contribute to the next wave of major advances in atmospheric science. We show that data-driven models can predict important meteorological quantities of interest to society such as global high resolution precipitation fields (0.25\u00b0) and can deliver accurate forecasts of the future state of the atmosphere without prior knowledge of the laws of physics and chemistry. We also show how these data-driven methods can be scaled to run on supercomputers with up to 1024 modern graphics processing units and beyond resulting in rapid training of data-driven models, thus supporting a cycle of rapid research and innovation. Taken together, these two results illustrate the significant potential of data-driven methods to advance atmospheric science and operational weather forecasting.<\/jats:p>","DOI":"10.1177\/10943420211039818","type":"journal-article","created":{"date-parts":[[2021,8,18]],"date-time":"2021-08-18T22:50:31Z","timestamp":1629327031000},"page":"130-140","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":8,"title":["Data-driven global weather predictions at high resolutions"],"prefix":"10.1177","volume":"36","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9003-4076","authenticated-orcid":false,"given":"John A","family":"Taylor","sequence":"first","affiliation":[{"name":"CSIRO Data61, Canberra, ACT, Australia"},{"name":"College of Engineering and Computer Science, The Australian National University, Canberra, ACT, Australia"},{"name":"Defence Science and Technology Group, Department of Defence, Canberra, ACT, Australia"}]},{"given":"Pablo","family":"Larraondo","sequence":"additional","affiliation":[{"name":"Fenner School of Environment and Society, The Australian National University, Canberra, ACT, Australia"}]},{"given":"Bronis R","family":"de Supinski","sequence":"additional","affiliation":[{"name":"Livermore Computing, Lawrence Livermore National Laboratory, Livermore, CA, USA"}]}],"member":"179","published-online":{"date-parts":[[2021,8,18]]},"reference":[{"key":"bibr1-10943420211039818","unstructured":"Abadi M, Agarwal A, Barham P, et al. 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