Articles | Volume 18, issue 15
https://doi.org/10.5194/gmd-18-4789-2025
https://doi.org/10.5194/gmd-18-4789-2025
Development and technical paper
 | 
04 Aug 2025
Development and technical paper |  | 04 Aug 2025

Correction of sea surface biases in the NEMO ocean general circulation model using neural networks

Andrea Storto, Sergey Frolov, Laura Slivinski, and Chunxue Yang

Related authors

Deploying machine learning components coupled to Earth System Models with OASIS3-MCT (v6) and Eophis (v1.1)
Alexis Barge, Julien Le Sommer, Andrea Storto, and Sophie Valcke
Geosci. Model Dev., 19, 10345–10363, https://doi.org/10.5194/gmd-19-10345-2026,https://doi.org/10.5194/gmd-19-10345-2026, 2026
Short summary
Quantifying freshwater fluxes from Major rivers and assessing their impact on the Atlantic Ocean
Louis Kern, Thomas Vaujour, Julia Pfeffer, Andrea Storto, Camille Szczypta, Gilles Garric, Claire Sirere, Gilles Larnicol, Chunxue Yang, Romain Bourdalle-Badie, and Stéphanie Guinehut
Ocean Sci., 22, 3457–3477, https://doi.org/10.5194/os-22-3457-2026,https://doi.org/10.5194/os-22-3457-2026, 2026
Short summary
Comparing Surface and Subsurface Marine Heatwaves in Ocean Reanalyses
Vincenzo de Toma, Andrea Storto, Ronan McAdam, Antonietta Capotondi, and Chunxue Yang
EGUsphere, https://doi.org/10.5194/egusphere-2026-5747,https://doi.org/10.5194/egusphere-2026-5747, 2026
This preprint is open for discussion and under review for Ocean Science (OS).
Short summary
North Atlantic sea level budget revisited
Zhe Song, Anny Cazenave, William Llovel, Andrea Storto, and Marie Bouih
Ocean Sci., 22, 2903–2914, https://doi.org/10.5194/os-22-2903-2026,https://doi.org/10.5194/os-22-2903-2026, 2026
Short summary
Quantitative evaluation of mesoscale eddies in the North Atlantic using satellite altimetry and ocean reanalyses
Paolo Mauriello, Gregory C. Smith, Andrea Storto, and Chunxue Yang
Ocean Sci., 22, 2863–2902, https://doi.org/10.5194/os-22-2863-2026,https://doi.org/10.5194/os-22-2863-2026, 2026
Short summary

Cited articles

Agarwal, N., Small, R. J., Bryan, F. O., Grooms, I., and Pegion, P. J.: Impact of stochastic ocean density corrections on air-sea flux variability, Geophys. Res. Lett., 50, e2023GL104248, https://doi.org/10.1029/2023GL104248, 2023. 
Balmaseda, M. A., Dee, D., Vidard, A., and Anderson, D. L. T.: A multivariate treatment of bias for sequential data assimilation: Application to the tropical oceans, Q. J. Roy. Meteor. Soc., 133, 167–179, https://doi.org/10.1002/qj.12, 2007. 
Barnier, B., Madec, G., Penduff, T., Molines, J.-M., Treguier, A.-M., Le Sommer, J., Beckmann, A., Biastoch, A., Böning, C., Dengg, J., Derval, C., Durand, E., Gulev, S., Remy, E., Talandier, C., Theetten, S., Maltrud, M., McClean, J., and De Cuevas, B.: Impact of partial steps and momentum advection schemes in a global ocean circulation model at eddy-permitting resolution, Ocean Dynam., 56, 543–567, https://doi.org/10.1007/s10236-006-0082-1, 2006. 
Bonavita, M. and Laloyaux, P.: Machine learning for model error inference and correction, J. Adv. Model. Earth Sy., 12, e2020MS002232, https://doi.org/10.1029/2020MS002232, 2020. 
Brodeau, L., Barnier, B., Treguier, A.-M., Penduff, T., and Gulev, S.: An ERA40-based atmospheric forcing for global ocean circulation models, Ocean Model., 31, 88–104, https://doi.org/10.1016/j.ocemod.2009.10.005, 2010. 
Download
Short summary

Inaccuracies in air–sea heat fluxes severely degrade the accuracy of ocean numerical simulations. Here, we use artificial neural networks to correct air–sea heat fluxes as a function of oceanic and atmospheric state predictors. The correction successfully improves surface and subsurface ocean temperatures beyond the training period and in prediction experiments.

Share
Altmetrics
Final-revised paper
Preprint