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The quiet revolution of numerical weather prediction

Nature volume 525, pages 47–55 (2015)Cite this article

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Abstract

Advances in numerical weather prediction represent a quiet revolution because they have resulted from a steady accumulation of scientific knowledge and technological advances over many years that, with only a few exceptions, have not been associated with the aura of fundamental physics breakthroughs. Nonetheless, the impact of numerical weather prediction is among the greatest of any area of physical science. As a computational problem, global weather prediction is comparable to the simulation of the human brain and of the evolution of the early Universe, and it is performed every day at major operational centres across the world.

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Figure 1: A measure of forecast skill at three-, five-, seven- and ten-day ranges, computed over the extra-tropical northern and southern hemispheres.
Figure 2: Physical processes of importance to weather prediction.
Figure 3: Schematic diagram of 36-h ensemble forecasts used to estimate the probability of precipitation over the UK.
Figure 4: Schematic of the ensemble analysis and forecast cycle.
Figure 5: CPU and power requirements as a function of NWP model resolution.
Figure 6: Key challenge areas for NWP in the future.

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Acknowledgements

We thank C. Jakob and M. Miller for motivating us to write this paper. We are grateful to E. Källén, F. Rabier and A. Simmons for comments and to L. Magnusson for input and figures.

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Authors and Affiliations

  1. European Centre for Medium-Range Weather Forecasts, Shinfield Park, Reading, RG2 9AX, UK

    Peter Bauer & Alan Thorpe

  2. Environment Canada, Trans-Canada Highway Dorval, Québec, H9P 1J3, Canada

    Gilbert Brunet

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P.B. led the writing of the paper and conceived the ideas of Figs 5 and 6. All authors contributed to writing the manuscript and assembled the remaining figures.

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Correspondence to Peter Bauer.

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Bauer, P., Thorpe, A. & Brunet, G. The quiet revolution of numerical weather prediction. Nature 525, 47–55 (2015). https://doi.org/10.1038/nature14956

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