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Ocean Surface Topography from Space
Physical and Biological Dynamics of Nonlinear Mesoscale Eddies: Satellite Observations, In Situ Measurements, and Numerical Simulations on a Global Scale


Dennis McGillicuddy, Jr. - (Woods Hole Oceanographic Institution)

Geochemical estimates of new production surpass the apparent rate of nutrient supply by vertical mixing by a factor of two or more in subtropical oceans, which constitute some of the largest biomes on earth. One possible mechanism to supply the missing nutrient locally is intermittent upwelling by mesoscale eddies and submesoscale processes. Growing evidence suggests that such episodic processes can have a large impact on mean biogeochemical cycles, so they must be included in our conceptual models and resolved in our numerical models. The overall goal of the proposed research is to investigate the role of mesoscale and submesoscale dynamics on biogeochemical fluxes in the open ocean. The general approach is to use a three-dimensional coupled physical and biogeochemical model together with in situ observations and a full complement of remotely sensed information (altimetry, ocean color, scatterometry, and sea surface temperature) to study the biological and chemical ramifications of spatially and temporally intermittent physical processes.

Recent progress in identifying and tracking mesoscale eddies with satellite altimetry has facilitated construction of a global atlas of eddy trajectories, amplitudes, and sizes. Use of the derived eddy-centric coordinates to merge altimetric data with other remotely sensed properties such as satellite ocean color, sea surface temperature, and ocean vector winds is now providing unprecedented opportunities for investigation of the physical and biological dynamics of mesoscale phenomena. Thus far, detailed coupled physical-biological studies of this type in a few regions suggest that the strongest eddy-driven signal in surface ocean color is advection of the mean chlorophyll gradient by the azimuthal rotation of the eddies. However, an emerging global analysis indicates eddy impacts on surface ocean chlorophyll vary regionally and seasonally. The mechanisms underlying these variations are not yet known. Moreover, the near-surface manifestation of mesoscale eddies in ocean color data may not always reveal the physical-biological dynamic in its entirety, insofar as large amplitude biological responses can take place deep in the euphotic zone where they are only partially detected by satellite. Thus, in order to develop a more complete understanding of the role of mesoscale eddies in upper ocean ecosystem dynamics and biogeochemical cycling, detailed analysis of altimetric and other satellite observations together with subsurface in situ measurements and numerical simulations is needed.

Our specific objectives are to:

  1. Update and maintain the global database of altimetrically-derived eddy trajectories and collocated weekly composites of satellite observations of sea level, wind stress, surface temperature, and ocean color transformed into eddy-centric coordinates.
  2. Compile and transform Argo float data into altimetrically-determined eddy-centric coordinates to elucidate the impact of eddy disturbances on hydrographic properties.
  3. Using the data products generated in (1) and (2), quantify the mechanisms of physical-biological interaction at the mesoscale and how these vary regionally.
  4. Conduct global eddy-resolving (0.1-degree) coupled physical-biological-biogeochemical simulations.
  5. Evaluate the mean state predicted by the model and compare with in situ and remotely sensed measurements and results from other models.
  6. Examine phenomenology of physical-biological-biogeochemical coupling at the mesoscale, comparing with observations from (3).
  7. Partition the simulated biogeochemical fluxes into mean vs. eddy-driven components, quantifying the impacts of mesoscale processes in biogeochemical cycling in the ocean.
  8. Develop parameterizations for mesoscale biogeochemical processes for inclusion into coarse resolution climate models.

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