This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5).
The transport of tracers in baroclinic flows will be investigated, using the perspective of the modified Lagrangian mean approach of Nakamura. The approach has been developed and applied thus far to the case of a purely two-dimensional cascade of tracer variance to ultimate dissipation by small-scale diffusion. In most flows of atmospheric and oceanic interest, the cascade is three-dimensional: even though the balanced flows are layerwise two-dimensional, they have baroclinic shear. In consequence, the cascade of tracer variance down to fine horizontal scales is accompanied by a cascade of vertical scales which, in practice, are much finer. Consequently, in almost all such circumstances it is vertical, not horizontal, diffusion that arrests the cascade. It is the core intention of this research to assess the implications of this for our understanding of large-scale transport. Theory suggests one can still define an effective diffusivity for quasi-horizontal transport, with the equivalent area of the tilted tracer contours replacing the .equivalent length of the two-dimensional case. Further, the theory also provides an expression for the net vertical (diabatic) transport, though the interpretation of this expression is not so clear. Output from a series of numerical simulations of transport in stratospheric and oceanic flows will be used to demonstrate, to assess, and to facilitate further development of, the theoretical predictions.
This study will address an obvious shortcoming of current two-dimensional theories of transport by balanced flows in the atmosphere and ocean and will lead to a deeper understanding of chaotic transport in baroclinic flows.
The broader impacts include, from a theoretical and conceptual viewpoint, wide application of the results in geophysical fluid dynamics and, more practically, permit the quantitative assessment of horizontal and vertical transport rates in the atmosphere and ocean. A graduate student will be trained.
