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The digital revolution of Earth-system science


Computational science is crucial for delivering reliable weather and climate predictions. However, despite decades of high-performance computing experience, there is serious concern about the sustainability of this application in the post-Moore/Dennard era. Here, we discuss the present limitations in the field and propose the design of a novel infrastructure that is scalable and more adaptable to future, yet unknown computing architectures.

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Fig. 1: Typical production workflow in operational numerical weather prediction.
Fig. 2: Comparison between observed and simulated satellite imagery.
Fig. 3: Conceptual view of an efficient software infrastructure for the Earth-system digital twin.
Fig. 4: Expected contribution of main system developments necessary to achieve key science and computing technology performance goals.


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The authors are grateful to P. Lopez for providing Fig. 2, M. Fielding and M. Janiskova for the illustrations of simulation-observation fusion in Box 1, and to the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) and NASA for providing the satellite data used to produce Fig. 2 and the figure in Box 1.

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P.B. conceived and organized the manuscript. P.B., P.D., T.H., T.Q., T.S. and N.W. contributed to the writing and revision of the manuscript.

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Correspondence to Peter Bauer.

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Peer review information Nature Computational Science thanks Jana Sillmann and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Fernando Chirigati was the primary editor on this Perspective and managed its editorial process and peer review in collaboration with the rest of the editorial team.

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Bauer, P., Dueben, P.D., Hoefler, T. et al. The digital revolution of Earth-system science. Nat Comput Sci 1, 104–113 (2021).

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