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Rémi Lam, Álvaro Sánchez‐González, Matthew Willson, Peter Wirnsberger, Meire Fortunato, Ferran Alet, Suman V. Ravuri, Timo Ewalds, Zach Eaton-Rosen, Weihua Hu and 8 more
Global medium-range weather forecasting is critical to decision-making across many social and economic domains. Traditional numerical weather prediction uses increased compute resources to improve forecast accuracy but does not directly use historical weather data to improve the underlying model. Here, we introduce GraphCast, a machine learning-based method trained directly from reanalysis data. It predicts hundreds of weather variables for the next 10 days at 0.25° resolution globally in under 1 minute. GraphCast significantly outperforms the most accurate operational deterministic systems on 90% of 1380 verification targets, and its forecasts support better severe event prediction, including tropical cyclone tracking, atmospheric rivers, and extreme temperatures. GraphCast is a key advance in accurate and efficient weather forecasting and helps realize the promise of machine learning for modeling complex dynamical systems.
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Lam, R., Sánchez‐González, Á., Willson, M., Wirnsberger, P., Fortunato, M., Alet, F., Ravuri, S. V., Ewalds, T., Eaton-Rosen, Z., Hu, W., Merose, A., Hoyer, S., Holland, G., Vinyals, O., Stott, J., Pritzel, A., Mohamed, S., & Battaglia, P. (2023). Learning skillful medium-range global weather forecasting. Science, 382(6677), 1416–1421. https://doi.org/10.1126/science.adi2336
Lam, Rémi, et al. "Learning skillful medium-range global weather forecasting." Science, vol. 382, no. 6677, 2023, pp. 1416–1421, https://doi.org/10.1126/science.adi2336.
Lam, Rémi, Álvaro Sánchez‐González, Matthew Willson, Peter Wirnsberger, Meire Fortunato, Ferran Alet, Suman V. Ravuri, et al. "Learning skillful medium-range global weather forecasting." Science 382, no. 6677 (2023): 1416–1421. https://doi.org/10.1126/science.adi2336.
Lam R., Sánchez‐González Á., Willson M. [и др.] Learning skillful medium-range global weather forecasting // Science. — 2023. — Vol. 382, № 6677. — P. 1416–1421. — URL: https://doi.org/10.1126/science.adi2336
@article{lam2023learning,
title = {{Learning skillful medium-range global weather forecasting}},
author = {Rémi Lam and Álvaro Sánchez‐González and Matthew Willson and Peter Wirnsberger and Meire Fortunato and Ferran Alet and Suman V. Ravuri and Timo Ewalds and Zach Eaton-Rosen and Weihua Hu and Alexander Merose and Stephan Hoyer and George Holland and Oriol Vinyals and Jacklynn Stott and Alexander Pritzel and Shakir Mohamed and Peter Battaglia},
journal = {Science},
year = {2023},
volume = {382},
number = {6677},
pages = {1416--1421},
doi = {10.1126/science.adi2336},
url = {https://doi.org/10.1126/science.adi2336}
}TY - JOUR AU - Lam, Rémi AU - Sánchez‐González, Álvaro AU - Willson, Matthew AU - Wirnsberger, Peter AU - Fortunato, Meire AU - Alet, Ferran AU - Ravuri, Suman V. AU - Ewalds, Timo AU - Eaton-Rosen, Zach AU - Hu, Weihua AU - Merose, Alexander AU - Hoyer, Stephan AU - Holland, George AU - Vinyals, Oriol AU - Stott, Jacklynn AU - Pritzel, Alexander AU - Mohamed, Shakir AU - Battaglia, Peter TI - Learning skillful medium-range global weather forecasting JO - Science VL - 382 IS - 6677 SP - 1416 EP - 1421 PY - 2023 DA - 2023/11/14 DO - 10.1126/science.adi2336 UR - https://doi.org/10.1126/science.adi2336 ER -
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