Articles | Volume 22, issue 5
https://doi.org/10.5194/os-22-3415-2026
https://doi.org/10.5194/os-22-3415-2026
Research article
 | 
27 Oct 2026
Research article |  | 27 Oct 2026

Diapycnal mixing in submesoscale-permitting simulations of the deep Brazil Basin

Yonglin Huang, Annalisa Bracco, Kurt Polzin, and Jonathan Gula

Related authors

Thermohaline gradients and frontal regimes in the northwestern Tropical Atlantic
Dante C. Napolitano, Jonathan Gula, Solange Coadou-Chaventon, Sabrina Speich, Cesar B. Rocha, James C. McWilliams, Dongxiao Zhang, and Xavier Carton
Ocean Sci., 22, 2425–2447, https://doi.org/10.5194/os-22-2425-2026,https://doi.org/10.5194/os-22-2425-2026, 2026
Short summary
Estimating the variability of deep-ocean particle flux collected by sediment traps using satellite data and machine learning
Théo Picard, Chelsey A. Baker, Jonathan Gula, Ronan Fablet, Laurent Mémery, and Richard Lampitt
Biogeosciences, 22, 4309–4331, https://doi.org/10.5194/bg-22-4309-2025,https://doi.org/10.5194/bg-22-4309-2025, 2025
Short summary
Predicting particle catchment areas of deep-ocean sediment traps using machine learning
Théo Picard, Jonathan Gula, Ronan Fablet, Jeremy Collin, and Laurent Mémery
Ocean Sci., 20, 1149–1165, https://doi.org/10.5194/os-20-1149-2024,https://doi.org/10.5194/os-20-1149-2024, 2024
Short summary
Cloud-based framework for inter-comparing submesoscale-permitting realistic ocean models
Takaya Uchida, Julien Le Sommer, Charles Stern, Ryan P. Abernathey, Chris Holdgraf, Aurélie Albert, Laurent Brodeau, Eric P. Chassignet, Xiaobiao Xu, Jonathan Gula, Guillaume Roullet, Nikolay Koldunov, Sergey Danilov, Qiang Wang, Dimitris Menemenlis, Clément Bricaud, Brian K. Arbic, Jay F. Shriver, Fangli Qiao, Bin Xiao, Arne Biastoch, René Schubert, Baylor Fox-Kemper, William K. Dewar, and Alan Wallcraft
Geosci. Model Dev., 15, 5829–5856, https://doi.org/10.5194/gmd-15-5829-2022,https://doi.org/10.5194/gmd-15-5829-2022, 2022
Short summary

Cited articles

Auclair, F., Benshila, R., Bordois, L., Boutet, M., Brémond, M., Caillaud, M., Cambon, G., Capet, X., Debreu, L., Ducousso, N., Dufois, F., Dumas, F., Ethé, C., Gula, J., Hourdin, C., Illig, S., Jullien, S., Le Corre, M., Le Gac, S., Le Gentil, S., Lemarié, F., Marchesiello, P., Mazoyer, C., Morvan, G., Nguyen, C., Penven, P., Person, R., Pianezze, J., Pous, S., Renault, L., Roblou, L., Sepulveda, A., and Theetten, S.: Coastal and Regional Ocean COmmunity model, Zenodo [code], https://doi.org/10.5281/zenodo.7415055, 2024. a
Barrier, N., Verley, P., Lett, C., and Mullon, C.: Ichthyop: A Lagrangian tool for modelling ichthyoplankton dynamics, Zenodo, https://doi.org/10.5281/zenodo.22080784, 2026. a
Bracco, A., Choi, J., Joshi, K., Luo, H., and McWilliams, J. C.: Submesoscale currents in the northern Gulf of Mexico: Deep phenomena and dispersion over the continental slope, Ocean Model., 101, 43–58, https://doi.org/10.1016/j.ocemod.2016.03.002, 2016. a
Brum, A. L., Lima de Azevedo, J. L., and Dengler, M.: Energetics of eddy–mean flow interactions in the deep western boundary current off the northeastern coast of Brazil, Deep-Sea Res. Part I, 193, 103965, https://doi.org/10.1016/j.dsr.2023.103965, 2023. a
Buijsman, M. C., Waterhouse, A. F., Zaron, E. D., Yadidya, B., Xu, C., Whitley, V., Wenegrat, J. O., Wang, J., Wallcraft, A. J., Varma, D., Tchonang, B. C., Siyanbola, O., Shriver, J. F., Sheremet, V. A., Send, U., Raja, K. J., Polzin, K., Ngodock, H. E., Moulin, A. J., Meiners, G., Lucas, A. J., Lankhorst, M., Kuehl, J. J., Kelly, S. M., Kachelein, L., Huang, Y., Griffin, C., Girton, J. B., Farrar, J. T., Delpech, A., Chen, Z., Chassignet, E. P., Carrier, M. J., Bracco, A., Arbic, B. K., Andres, M., and Abdulfatai, M. A.: A Multiagency Experiment on Internal Wave Energy, Mixing, and Interactions and Their Representation in Global Ocean Models and Operational Forecasts, B. Am. Meteorol. Soc., 107, E158–E182, https://doi.org/10.1175/BAMS-D-24-0174.1, 2026. a
Download
Short summary
We compared five high-resolution simulations with observations from the Brazil Basin to test how models represent deep-ocean mixing above rough seafloor. By tracking virtual particles, we found that the simulations reproduce strong mixing near the bottom, and higher resolution produces enhanced mixing in the ocean interior. Our results indicate that smoothed seafloor details weaken wave breaking and leave too much energy in eddies, making them more intense than they likely are in the real ocean.
Share