The LOCEAN laboratory is highly involved in the development and application of a wide array of open source numerical models. This includes ocean, sea ice and marine biogeochemical models as well their coupling in general circulation and Earth system models. Such models have diverse applications from operational oceanography to centennial/millennial-scale climate projections. Our research encompasses the development of model code and configurations, the performance of simulations and broader model assessment and evaluation.

The physical ocean

NEMO (Nucleus for European Modelling of the Ocean) is a state-of-the-art modelling framework for research activities and forecasting services in ocean and climate sciences, developed collaboratively by a European consortium (ITA-FRA-GBR).

The NEMO ocean model has 3 major components:

  • NEMO-[glossary_exclude]OCE[/glossary_exclude] models the ocean dynamics/thermodynamics and solves the primitive equations
  • NEMO-ICE (SI³: Sea-Ice Integrated Initiative) represents sea-ice, at large scales, essentially horizontal drift, growth and melt and influence on radiation balance.
  • NEMO-TOP (Tracers in the Ocean Paradigm) models oceanic tracer transport and biogeochemical processes (using PISCES)

CROCO (“Coastal and Regional Ocean COmmunity Model”) is a new oceanic modelling system built upon ROMS_AGRIF and the non-hydrostatic kernel of SNH (under testing), gradually including algorithms from MARS3D (sediments) and HYCOM (vertical coordinates). An important objective for CROCO is to resolve very fine scales (especially in the coastal area), and their interactions with larger scales. It is the oceanic component of a complex coupled system including various components, e.g., atmosphere, surface waves, marine sediments, biogeochemistry and ecosystems.

Sea ice

SI³ (Sea-Ice Integrated Initiative) is a 2+1D continuum sea ice model, splitting horizontal drift (ice dynamics) and vertical processes (thermodynamics). Ice dynamics are resolved using a 2D continuum mechanics equation, expressing the balance between external (wind, currents, …), Coriolis and internal (rheology) stresses. Ice thermodynamics encompass all processes related to ice growth and melt and assumed purely vertical. Equations for the conservation of mass, energy and salt are resolved in the snow-ice system, accounting for specific sea ice phenomena, in particular snow, melt ponds, and brine inclusions. At current resolution, variations in ice thickness are far from resolved. To address this issue, sea ice coverage is horizontally split into several (say 5) thickness categories to and other properties, upon which many or the parameterised processes depend non-linearly. SI³ (historically LIM) is the reference sea ice component of NEMO.

Marine biogeochemistry

PISCES (Pelagic Interactions Scheme for Carbon and Ecosystem Studies) is an ocean biogeochemical model that simulates the lower trophic levels of marine ecosystems (phytoplankton and {micro,meso}zooplankton) and the biogeochemical cycles of carbon and of the main nutrients (P, N, Fe, and Si). The model is designed for use across diverse timescales, from seasonal to interannual prediction studies, to projections of paleooceanographic and climatic change. PISCES can be used within both global (e.g. NEMO) and regional (e.g. CROCO) ocean configurations and run with fixed or variable phytoplankton stoichiometry. Developmental branches of the model include the addition of isotopic tracers, further micronutrients and coupling to higher trophic ecosystem models.

References

NEMO

  • Madec, G. (2015). NEMO ocean engine. France: Institut Pierre-Simon Laplace (IPSL).

More informations:

CROCO

More informations:

LIM

  • Fichefet, T., & Maqueda, M. A. M. (1997). Sensitivity of a global sea ice model to the treatment of ice thermodynamics and dynamics. Journal of Geophysical Research: Oceans, 102(C6), 12609–12646. https://doi.org/10.1029/97JC00480
  • Goosse, H., & Fichefet, T. (1999). Importance of ice-ocean interactions for the global ocean circulation: A model study. Journal of Geophysical Research: Oceans, 104(C10), 23337–23355. https://doi.org/10.1029/1999JC900215
  • Rousset, C., Vancoppenolle, M., Madec, G., Fichefet, T., Flavoni, S., Barthélemy, A., et al. (2015). The Louvain-La-Neuve sea ice model LIM3.6: global and regional capabilities. Geoscientific Model Development, 8, 2991– 3005. https://doi.org/10.5194/gmd-8-2991-2015
  • Vancoppenolle, M., Fichefet, T., Goosse, H., Bouillon, S., Madec, G., & Maqueda, M. A. M. (2009). Simulating the mass balance and salinity of Arctic and Antarctic sea ice. 1. Model description and validation. Ocean Modelling, 27(1), 33–53. https://doi.org/10.1016/j.ocemod.2008.10.005
  • Vancoppenolle, M., Fichefet, T., & Goosse, H. (2009). Simulating the mass balance and salinity of Arctic and Antarctic sea ice. 2. Importance of sea ice salinity variations. Ocean Modelling, 27(1), 54–69. https://doi.org/10.1016/j.ocemod.2008.11.003

PISCES

  • Aumont, O., Maier‐Reimer, E., Blain, S., & Monfray, P. (2003). An ecosystem model of the global ocean including Fe, Si, P colimitations. Global Biogeochemical Cycles, 17(2). https://doi.org/10.1029/2001GB001745
  • Aumont, O., Ethé, C., Tagliabue, A., Bopp, L., & Gehlen, M. (2015). PISCES-v2: an ocean biogeochemical model for carbon and ecosystem studies. Geosci. Model Dev., 8(8), 2465–2513. https://doi.org/10.5194/gmd-8-2465-2015
  • Aumont, O., Maury, O., Lefort, S., & Bopp, L. (2018). Evaluating the Potential Impacts of the Diurnal Vertical Migration by Marine Organisms on Marine Biogeochemistry. Global Biogeochemical Cycles, 32(11), 1622–1643. https://doi.org/10.1029/2018GB005886
  • Kwiatkowski, L., Aumont, O., Bopp, L., & Ciais, P. (2018). The Impact of Variable Phytoplankton Stoichiometry on Projections of Primary Production, Food Quality, and Carbon Uptake in the Global Ocean. Global Biogeochemical Cycles, 32(4), 516–528. https://doi.org/10.1002/2017GB005799

Recent Earth system model implementations

  • Boucher, O., Servonnat, J., Albright, A. L., Aumont, O., Balkanski, Y., Bastrikov, V., et al. (2020). Presentation and Evaluation of the IPSL-CM6A-LR Climate Model. Journal of Advances in Modeling Earth Systems, 12(7), 1–52. https://doi.org/10.1029/2019MS002010
  • Séférian, R., Nabat, P., Michou, M., Saint‐Martin, D., Voldoire, A., Colin, J., et al. (2019). Evaluation of CNRM Earth System Model, CNRM-ESM2-1: Role of Earth System Processes in Present-Day and Future Climate. Journal of Advances in Modeling Earth Systems, 11(12), 4182–4227. https://doi.org/10.1029/2019MS001791
  • Sellar, A. A., Jones, C. G., Mulcahy, J. P., Tang, Y., Yool, A., Wiltshire, A., et al. (2019). UKESM1: Description and Evaluation of the U.K. Earth System Model. Journal of Advances in Modeling Earth Systems, 11(12), 4513–4558. https://doi.org/10.1029/2019MS001739
  • Swart, N. C., Cole, J. N. S., Kharin, V. V., Lazare, M., Scinocca, J. F., Gillett, N. P., et al. (2019). The Canadian Earth System Model version 5 (CanESM5.0.3). Geoscientific Model Development, 12(11), 4823–4873. https://doi.org/10.5194/gmd-12-4823-2019

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