ABSTRACT

Once the large-scale ocean circulation was viewed as a sluggish continuous flow. Thanks to new satellite and in situ observations, powerful numerical models, and advances in theory, it is now understood that ocean mesoscale turbulence, the highly energetic, nonlinear jumble of waves, eddies, and jets which characterizes ocean currents on scales of 20-500 km, is an essential component of ocean circulation, transport, and marine ecosystems. Because this turbulence draws its energy from instabilities of the large-scale flow, its properties are themselves sensitive to changes in climate. This project seeks to answer the question: how, and on what timescales, do large-scale changes in global climate affect the properties of ocean mesoscale turbulence? As such, the proposed work has the potential to transform how the climate community views mesoscale turbulence. Because most ocean climate models are too coarse to resolve the mesoscale, the effects of mesoscale turbulence are parameterized. As a result, mesoscale turbulence is reduced to a "parameter" to be tuned, rather than an emergent, dynamic part of the Earth system. The project is aimed at deepening basic physical understanding of the processes that regulate the properties of mesoscale turbulence and the timescales on which these properties respond to changes in climate. Consideration of this two-way interaction will lead to a richer understanding of the role of the ocean in the climate system, opening the door to new mechanisms for climate feedbacks. The project will also lead to methodological advances in Big Data computational tools for oceanography. The curriculum development will address the need for students to develop strong computational skills and, in particular, the capability to handle Big Data, to meet the emerging challenges of 21st century science. It will also promote active learning and the use of data in the oceanography classroom. The open-source nature of the teaching materials will encourage wide adoption. Strong interaction between research and education is guaranteed, because the same tools used in the research will be incorporated into the curriculum, both evolving together throughout the project.

The research component of this CAREER award will examine the link between climate change, baroclinic instability, mesoscale eddy properties (kinetic energy and length scales), and mesoscale mixing, using a hierarchy of models and observations. Idealized process models will build a theoretical foundation of understanding of how changes in surface wind and buoyancy forcing lead to changes in mesoscale turbulence. Decadal variability in mesoscale statistics and baroclinic instability will also be examined in satellite and hydrographic observations. Finally, the theoretical framework and statistical analysis will be applied to global, eddy-resolving climate model simulations of greenhouse warming. To facilitate this work, Python-based computational tools for rapid data processing will be developed. These tools will be integrated into education through development of an open-source curriculum in "Big Data Oceanography," in which the computational skills necessary to study global, high-resolution datasets are taught side-by-side with core ocean science concepts. These modules will be deployed and assessed in an undergraduate course and disseminated widely online and at education conferences.

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