Articles | Volume 15, issue 5
https://doi.org/10.5194/gmd-15-1995-2022
https://doi.org/10.5194/gmd-15-1995-2022
Model description paper
 | 
09 Mar 2022
Model description paper |  | 09 Mar 2022

Empirical Lagrangian parametrization for wind-driven mixing of buoyant particles at the ocean surface

Victor Onink, Erik van Sebille, and Charlotte Laufkötter

Related authors

Quantifying Variability in Lagrangian Particle Dispersal in Ocean Ensemble Simulations: an Information Theory Approach
Claudio M. Pierard, Siren Rühs, Laura Gómez-Navarro, Michael C. Denes, Florian Meirer, Thierry Penduff, and Erik van Sebille
EGUsphere, https://doi.org/10.5194/egusphere-2024-3847,https://doi.org/10.5194/egusphere-2024-3847, 2024
Short summary
Flow patterns, hotspots and connectivity of land-derived substances at the sea surface of Curaçao in the Southern Caribbean
Vesna Bertoncelj, Furu Mienis, Paolo Stocchi, and Erik van Sebille
EGUsphere, https://doi.org/10.5194/egusphere-2024-3112,https://doi.org/10.5194/egusphere-2024-3112, 2024
Short summary
The (non)effect of personalization in climate texts on the credibility of climate scientists: a case study on sustainable travel
Anna Leerink, Mark Bos, Daan Reijnders, and Erik van Sebille
Geosci. Commun., 7, 201–214, https://doi.org/10.5194/gc-7-201-2024,https://doi.org/10.5194/gc-7-201-2024, 2024
Short summary
Possible provenance of IRD by tracing late Eocene Antarctic iceberg melting using a high-resolution ocean model
Mark Vinz Elbertsen, Erik van Sebille, and Peter Kristian Bijl
EGUsphere, https://doi.org/10.5194/egusphere-2024-1596,https://doi.org/10.5194/egusphere-2024-1596, 2024
Short summary
Designing and evaluating a public engagement activity about sea level rise
Nieske Vergunst, Tugce Varol, and Erik van Sebille
EGUsphere, https://doi.org/10.5194/egusphere-2024-1649,https://doi.org/10.5194/egusphere-2024-1649, 2024
Short summary

Related subject area

Oceanography
DalROMS-NWA12 v1.0, a coupled circulation–ice–biogeochemistry modelling system for the northwest Atlantic Ocean: development and validation
Kyoko Ohashi, Arnaud Laurent, Christoph Renkl, Jinyu Sheng, Katja Fennel, and Eric Oliver
Geosci. Model Dev., 17, 8697–8733, https://doi.org/10.5194/gmd-17-8697-2024,https://doi.org/10.5194/gmd-17-8697-2024, 2024
Short summary
A revised ocean mixed layer model for better simulating the diurnal variation in ocean skin temperature
Eui-Jong Kang, Byung-Ju Sohn, Sang-Woo Kim, Wonho Kim, Young-Cheol Kwon, Seung-Bum Kim, Hyoung-Wook Chun, and Chao Liu
Geosci. Model Dev., 17, 8553–8568, https://doi.org/10.5194/gmd-17-8553-2024,https://doi.org/10.5194/gmd-17-8553-2024, 2024
Short summary
Evaluating an accelerated forcing approach for improving computational efficiency in coupled ice sheet–ocean modelling
Qin Zhou, Chen Zhao, Rupert Gladstone, Tore Hattermann, David Gwyther, and Benjamin Galton-Fenzi
Geosci. Model Dev., 17, 8243–8265, https://doi.org/10.5194/gmd-17-8243-2024,https://doi.org/10.5194/gmd-17-8243-2024, 2024
Short summary
An optimal transformation method for inferring ocean tracer sources and sinks
Jan D. Zika and Taimoor Sohail
Geosci. Model Dev., 17, 8049–8068, https://doi.org/10.5194/gmd-17-8049-2024,https://doi.org/10.5194/gmd-17-8049-2024, 2024
Short summary
PPCon 1.0: Biogeochemical-Argo profile prediction with 1D convolutional networks
Gloria Pietropolli, Luca Manzoni, and Gianpiero Cossarini
Geosci. Model Dev., 17, 7347–7364, https://doi.org/10.5194/gmd-17-7347-2024,https://doi.org/10.5194/gmd-17-7347-2024, 2024
Short summary

Cited articles

Berloff, P. S. and McWilliams, J. C.: Material transport in oceanic gyres. Part III: Randomized stochastic models, J. Phys. Oceanogr., 33, 1416–1445, 2003. a, b, c
Boufadel, M., Liu, R., Zhao, L., Lu, Y., Özgökmen, T., Nedwed, T., and Lee, K.: Transport of oil droplets in the upper ocean: impact of the eddy diffusivity, J. Geophys. Res.-Oceans, 125, e2019JC015727, https://doi.org/10.1029/2019JC015727, 2020. a, b, c
Brickman, D. and Smith, P.: Lagrangian stochastic modeling in coastal oceanography, J. Atmos. Ocean. Tech., 19, 83–99, 2002. a, b, c, d, e
Brignac, K. C., Jung, M. R., King, C., Royer, S.-J., Blickley, L., Lamson, M. R., Potemra, J. T., and Lynch, J. M.: Marine debris polymers on main Hawaiian Island beaches, sea surface, and seafloor, Environ. Sci. Technol., 53, 12218–12226, 2019. a
Brunner, K., Kukulka, T., Proskurowski, G., and Law, K. L.: Passive buoyant tracers in the ocean surface boundary layer: 2. Observations and simulations of microplastic marine debris, J. Geophys. Res.-Oceans, 120, 7559–7573, 2015. a, b, c, d
Download
Short summary
Turbulent mixing is a vital process in 3D modeling of particle transport in the ocean. However, since turbulence occurs on very short spatial scales and timescales, large-scale ocean models generally have highly simplified turbulence representations. We have developed parametrizations for the vertical turbulent transport of buoyant particles that can be easily applied in a large-scale particle tracking model. The predicted vertical concentration profiles match microplastic observations well.