Articles | Volume 17, issue 18
https://doi.org/10.5194/gmd-17-6967-2024
https://doi.org/10.5194/gmd-17-6967-2024
Development and technical paper
 | 
19 Sep 2024
Development and technical paper |  | 19 Sep 2024

Spurious numerical mixing under strong tidal forcing: a case study in the south-east Asian seas using the Symphonie model (v3.1.2)

Adrien Garinet, Marine Herrmann, Patrick Marsaleix, and Juliette Pénicaud

Related authors

Optimizing physical scheme selection in RegCM5 for improved air–sea fluxes over Southeast Asia
Quentin Desmet, Marine Herrmann, and Thanh Ngo-Duc
EGUsphere, https://doi.org/10.5194/egusphere-2025-1579,https://doi.org/10.5194/egusphere-2025-1579, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
Short summary
Modeling Indian Ocean circulation to study marine debris dispersion: insights into high-resolution and Stokes drift effects with Symphonie 3.6.6
Lisa Weiss, Marine Herrmann, Patrick Marsaleix, Matthieu Bompoil, and Christophe Maes
EGUsphere, https://doi.org/10.5194/egusphere-2025-1918,https://doi.org/10.5194/egusphere-2025-1918, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
Short summary
Surface circulation characterization along the middle southern coastal region of Vietnam from high-frequency radar and numerical modeling
Thanh Huyen Tran, Alexei Sentchev, Thai To Duy, Marine Herrmann, Sylvain Ouillon, and Kim Cuong Nguyen
Ocean Sci., 21, 1–18, https://doi.org/10.5194/os-21-1-2025,https://doi.org/10.5194/os-21-1-2025, 2025
Short summary
Mechanisms and intraseasonal variability in the South Vietnam Upwelling, South China Sea: the role of circulation, tides, and rivers
Marine Herrmann, Thai To Duy, and Patrick Marsaleix
Ocean Sci., 20, 1013–1033, https://doi.org/10.5194/os-20-1013-2024,https://doi.org/10.5194/os-20-1013-2024, 2024
Short summary
New insights into the South China Sea throughflow and water budget seasonal cycle: evaluation and analysis of a high-resolution configuration of the ocean model SYMPHONIE version 2.4
Ngoc B. Trinh, Marine Herrmann, Caroline Ulses, Patrick Marsaleix, Thomas Duhaut, Thai To Duy, Claude Estournel, and R. Kipp Shearman
Geosci. Model Dev., 17, 1831–1867, https://doi.org/10.5194/gmd-17-1831-2024,https://doi.org/10.5194/gmd-17-1831-2024, 2024
Short summary

Related subject area

Oceanography
A new global high-resolution wave model for the tropical ocean using WAVEWATCH III version 7.14
Axelle Gaffet, Xavier Bertin, Damien Sous, Héloïse Michaud, Aron Roland, and Emmanuel Cordier
Geosci. Model Dev., 18, 1929–1946, https://doi.org/10.5194/gmd-18-1929-2025,https://doi.org/10.5194/gmd-18-1929-2025, 2025
Short summary
sedInterFoam 1.0: a three-phase numerical model for sediment transport applications with free surfaces
Antoine Mathieu, Yeulwoo Kim, Tian-Jian Hsu, Cyrille Bonamy, and Julien Chauchat
Geosci. Model Dev., 18, 1561–1573, https://doi.org/10.5194/gmd-18-1561-2025,https://doi.org/10.5194/gmd-18-1561-2025, 2025
Short summary
The Ross Sea and Amundsen Sea Ice–Sea Model (RAISE v1.0): a high-resolution ocean–sea ice–ice shelf coupling model for simulating the Dense Shelf Water and Antarctic Bottom Water in the Ross Sea, Antarctica
Zhaoru Zhang, Chuan Xie, Chuning Wang, Yuanjie Chen, Heng Hu, and Xiaoqiao Wang
Geosci. Model Dev., 18, 1375–1393, https://doi.org/10.5194/gmd-18-1375-2025,https://doi.org/10.5194/gmd-18-1375-2025, 2025
Short summary
Sensitivity of the tropical Atlantic to vertical mixing in two ocean models (ICON-O v2.6.6 and FESOM v2.5)
Swantje Bastin, Aleksei Koldunov, Florian Schütte, Oliver Gutjahr, Marta Agnieszka Mrozowska, Tim Fischer, Radomyra Shevchenko, Arjun Kumar, Nikolay Koldunov, Helmuth Haak, Nils Brüggemann, Rebecca Hummels, Mia Sophie Specht, Johann Jungclaus, Sergey Danilov, Marcus Dengler, and Markus Jochum
Geosci. Model Dev., 18, 1189–1220, https://doi.org/10.5194/gmd-18-1189-2025,https://doi.org/10.5194/gmd-18-1189-2025, 2025
Short summary
HIDRA3: a deep-learning model for multipoint ensemble sea level forecasting in the presence of tide gauge sensor failures
Marko Rus, Hrvoje Mihanović, Matjaž Ličer, and Matej Kristan
Geosci. Model Dev., 18, 605–620, https://doi.org/10.5194/gmd-18-605-2025,https://doi.org/10.5194/gmd-18-605-2025, 2025
Short summary

Cited articles

Adcroft, A. and Campin, J.-M.: Rescaled Height Coordinates for Accurate Representation of Free-Surface Flows in Ocean Circulation Models, Ocean Model., 7, 269–284, https://doi.org/10.1016/j.ocemod.2003.09.003, 2004. a
Alfieri, L., Burek, P., Dutra, E., Krzeminski, B., Muraro, D., Thielen, J., and Pappenberger, F.: GloFAS – global ensemble streamflow forecasting and flood early warning, Hydrol. Earth Syst. Sci., 17, 1161–1175, https://doi.org/10.5194/hess-17-1161-2013, 2013. a
Alford, M. H., Gregg, M. C., and Ilyas, M.: Diapycnal Mixing in the Banda Sea: Results of the First Microstructure Measurements in the Indonesian Throughflow, Geophys. Res. Lett., 26, 2741–2744, https://doi.org/10.1029/1999GL002337, 1999. a
Álvarez, Ó., Izquierdo, A., González, C. J., Bruno, M., and Mañanes, R.: Some Considerations about Non-Hydrostatic vs. Hydrostatic Simulation of Short-Period Internal Waves. A Case Study: The Strait of Gibraltar, Cont. Shelf Res., 181, 174–186, https://doi.org/10.1016/j.csr.2019.05.016, 2019. a
Apel, J. R., Holbrook, J. R., Liu, A. K., and Tsai, J. J.: The Sulu Sea Internal Soliton Experiment, J. Phys. Oceanogr., 15, 1625–1651, https://doi.org/10.1175/1520-0485(1985)015<1625:TSSISE>2.0.CO;2, 1985. a, b, c
Download
Short summary
Mixing is a crucial aspect of the ocean, but its accurate representation in computer simulations is made challenging by errors that result in unwanted mixing, compromising simulation realism. Here we illustrate the spurious effect that tides can have on simulations of south-east Asia. Although they play an important role in determining the state of the ocean, they can increase numerical errors and make simulation outputs less realistic. We also provide insights into how to reduce these errors.
Share