whigg/upperoceanseasonality

A manuscript published in Geophysical Research Letters.

Seasonality of submesoscale dynamics in the Kuroshio Extension

Authors

Cesar B. Rocha¹, Sarah T. Gille¹ , Teresa K. Chereskin¹, and Dimitris Menemenlis².

1: Scripps Institution of Oceanography, University of California San Diego, La Jolla, CA, USA.

2: [Earth Sciences Division, Jet Propulsion Laboratory](Earth Sciences Division, Jet Propulsion Laboratory), California Institute of Technology, Pasadena, CA, USA.

Key Points

• Upper-ocean submesoscale (10-100 km) turbulence and inertia-gravity waves undergo strong seasonal cycles that are out of phase.
• Submesoscale turbulence dominates the horizontal velocity and sea-surface height variability in late winter/early spring.
• Submesoscale inertia-gravity waves dominate the horizontal velocity and sea-surface height variability in late summer/early fall.

Abstract

Recent studies show that the vigorous seasonal cycle of the mixed layer modulates upper-ocean submesoscale turbulence. Here we provide model-based evidence that the seasonally-changing upper-ocean stratification in the Kuroshio Extension also modulates submesoscale (here 10-100 km) inertia-gravity waves. Summertime re-stratification weakens submesoscale turbulence but enhances inertia-gravity waves near the surface. Thus, submesoscale turbulence and inertia-gravity waves undergo vigorous out-of-phase seasonal cycles. These results imply a strong seasonal modulation of the accuracy of geostrophic velocity diagnosed from submesoscale sea-surface height delivered by the Surface Water and Ocean Topography (SWOT) satellite mission.

Status

The paper was published in in Geophysical Research Letters, doi: 10.1002/2016GL071349. Supporting information and figures are also available. Comments, questions, and suggestions are extremely welcome and warmly appreciated. Feedback can be submitted through github issues or via e-mail to Cesar Rocha ([email protected]).

Code

The analysis for this paper has been performed on NASA's Pleiades Supercomputer. The project uses two small pieces of code developed by the first author and available on github: llctools and pyspec. Those codes leverage on the Scientific Python stack. Specific processing and plotting codes are available on Jupyter notebooks.

Once the heavy computations are performed on Pleiades and the output files are saved in netCDF4, the whole subsequent processing and plotting and LaTeX compiling is performed in a single-button reproducible workflow using nbflow. The draft is built online and published using gh-puslisher.

Data

The LLC outputs can be obtained from the ECCO project. The gridded altimeter data were produced by Ssalto/Duacs and distributed by AVISO, with support from CNES. The Argo Roemmich-Gilson climatology can be downloaded from the SIO Argo group. KEO mooring data are available from NOAA PMEL. KESS mooring data are available from the US KESS project.

Support

This research was funded by NSF (OCE1357047) and NASA (NNX13AE44G,NNX13AE85G,NNX16AH67G).

Acknowledgments

William R. Young provided helpful feedback on the first draft. Thanks to our colleagues at the NASA Advanced Supercomputing Division and the MITgcm and SciPy communities for their awesome support.