Ocean transport diagnostics#

Overview#

This recipe computes three ocean transport diagnostics for a CMIP6 model:

  • Ocean heat transport: the northward ocean heat transport in the Atlantic-Arctic basin, from the hfbasin variable. It is shown as a profile against latitude (in PW).

  • ACC transport: the Antarctic Circumpolar Current transport through the Drake Passage, from the mfo variable. It is shown as a time series (in Tg s-1).

  • SSH gradient: the magnitude of the horizontal sea surface height gradient, from the zos variable. It is shown as a map. Strong gradients mark ocean fronts such as the Gulf Stream, so this map helps to check the Gulf Stream separation.

Available recipes and diagnostics#

Recipes are stored in esmvaltool/recipes/

  • recipe_ocean_transport.yml

Diagnostics are stored in esmvaltool/diag_scripts/ocean/

  • diagnostic_ssh_gradient.py: computes and plots the SSH gradient magnitude.

The ocean heat transport and ACC transport diagnostics use standard preprocessors together with the monitor/multi_datasets.py plot script.

User settings in recipe#

  1. Script diagnostic_ssh_gradient.py

    The script has no settings. It expects zos regridded to a regular latitude/longitude grid with the time axis kept, because the script computes the gradient magnitude for each time step and then averages over time.

The ocean heat transport and ACC transport diagnostics are controlled through the preprocessors and the monitor/multi_datasets.py plot options in the recipe.

Variables#

  • hfbasin (ocean, monthly, latitude basin time)

  • mfo (ocean, monthly, oline time)

  • zos (ocean, monthly, longitude latitude time)

Observations and reformat scripts#

The recipe runs on a CMIP6 model alone. The SSH gradient can also be compared with the ORAS5 reanalysis. ORAS5 is read on the fly by ESMValCore (project native6) and needs the oras5_mesh_T.nc grid file, passed through the horizontal_grid facet. More details in the ESMValCore documentation on ORAS5. See the commented example in the recipe.

References#

  • de Mora, L., Yool, A., Palmieri, J., Sellar, A., Kuhlbrodt, T., Popova, E., Jones, C., and Allen, J. I.: BGC-val: a model- and grid-independent Python toolkit to evaluate marine biogeochemical models, Geosci. Model Dev., 11, 4215-4240, https://doi.org/10.5194/gmd-11-4215-2018, 2018.

Example plots#

../_images/ocean_heat_transport.png

Fig. 362 Northward ocean heat transport in the Atlantic-Arctic basin (MPI-ESM1-2-LR).#

../_images/acc_drake_transport.png

Fig. 363 ACC transport through the Drake Passage (MPI-ESM1-2-LR).#

../_images/ssh_gradient.png

Fig. 364 Sea surface height gradient magnitude (MPI-ESM1-2-LR).#