Internal-wave strain and internal-wave-driven turbulent mixing for the global ocean will be mapped using the WOCE (World Ocean Circulation Experiment) hydrographic data set of more than 18,000 CTD (Conductivity, Temperature and Depth) profiles. Diapycnal diffusivities will be estimated using a strain-only version of a fine-scale parameterization which has been found to agree with the shear-and-strain version to within a factor of 2. The proposed work represents a more than 5-fold expansion in coverage. These mixing predictions will be compared with those from density-overturn analysis being conducted by Luther and Decloedt (2010) on the same data set. Refinements to the fine-scale parameterization will be made based on recent advances and insights.
This project expands on previous work which used shear and strain from ~3500 Lowered ADCP (Acoustic Doppler Current Profiler)and CTD profiles. That work found that (i) most of the ocean was characterized by small diffusivities consistent with direct but sparse microstructure measurements, and (ii) turbulence was extremely heterogeneous, with hotspots associated with abrupt topography. Sampling was sufficient to infer global-average diapycnal velocities as a function of depth and latitude from the vertical advective-diffusive equation. However, much of the ocean was undersampled and statistics were inadequate to characterize the meridional overturning circulation by individual basin. The proposed analysis will provide a much more comprehensive geography of ocean mixing. Inferences of the thermohaline circulation basin-by-basin will test if the bulk of the overturning occurs in the Indian Ocean as inverse budgets suggest. With higher vertical resolution, finer binning of internal wave strain will be possible. Concerns that the scaling falls short near strong forcing will be addressed by comparison with density-overturn analysis of the same data set. It remains to be seen whether ocean mixing is dominated by weak widespread internal-wave-driven mixing or very intense hotspots.
Quantifying and understanding of ocean mixing remains one of the most vexing problems in physical oceanography. Its correct parameterization in general circulation models (GCMs) is critical to correctly reproducing a wide range of features on timescales of months to millennia, linking it not just to the circulation but also weather prediction, biogeochemical cycles and longterm climate. As a member of the Climate Processes Team on Representing Internal-Wave Driven Mixing in Global Ocean Models, the PI is working closely with numerical modelers to improve sub-grid-scale parameterizations for internal-wave-driven turbulent mixing in GCMs. As with the earlier work, the PI will be available to help other researchers with their implementations of the fine-scale parameterization in other data sets. Predictions from this work will be publicly available to the community. The PI will work with outreach resources at APL-U of Washington to better educate the general public in the roles of waves and mixing in physical oceanography.
