Geoscientific Model Development (Jul 2023)

The mixed-layer depth in the Ocean Model Intercomparison Project (OMIP): impact of resolving mesoscale eddies

  • A. M. Treguier,
  • C. de Boyer Montégut,
  • A. Bozec,
  • E. P. Chassignet,
  • B. Fox-Kemper,
  • A. McC. Hogg,
  • A. McC. Hogg,
  • D. Iovino,
  • A. E. Kiss,
  • A. E. Kiss,
  • J. Le Sommer,
  • Y. Li,
  • P. Lin,
  • C. Lique,
  • H. Liu,
  • G. Serazin,
  • D. Sidorenko,
  • Q. Wang,
  • X. Xu,
  • S. Yeager

DOI
https://doi.org/10.5194/gmd-16-3849-2023
Journal volume & issue
Vol. 16
pp. 3849 – 3872

Abstract

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The ocean mixed layer is the interface between the ocean interior and the atmosphere or sea ice and plays a key role in climate variability. It is thus critical that numerical models used in climate studies are capable of a good representation of the mixed layer, especially its depth. Here we evaluate the mixed-layer depth (MLD) in six pairs of non-eddying (1∘ grid spacing) and eddy-rich (up to 1/16∘) models from the Ocean Model Intercomparison Project (OMIP), forced by a common atmospheric state. For model evaluation, we use an updated MLD dataset computed from observations using the OMIP protocol (a constant density threshold). In winter, low-resolution models exhibit large biases in the deep-water formation regions. These biases are reduced in eddy-rich models but not uniformly across models and regions. The improvement is most noticeable in the mode-water formation regions of the Northern Hemisphere. Results in the Southern Ocean are more contrasted, with biases of either sign remaining at high resolution. In eddy-rich models, mesoscale eddies control the spatial variability in MLD in winter. Contrary to a hypothesis that the deepening of the mixed layer in anticyclones would make the MLD larger globally, eddy-rich models tend to have a shallower mixed layer at most latitudes than coarser models do. In addition, our study highlights the sensitivity of the MLD computation to the choice of a reference level and the spatio-temporal sampling, which motivates new recommendations for MLD computation in future model intercomparison projects.