Cascading refers to the process by which dense continental shelf waters pass onto the continental slope and then sink to an equilibrium depth. This is the way that much of the ocean's deepest waters are formed, for example in the Weddell Sea off Antarctica. As such, it is important for shaping the global meridional overturning circulation, and thus it is influential for climate in general. It is argued that in most cases, cascading occurs in settings where current variability is dominated by the eddy field. This study seeks to understand cascading in the presence of wind and/or topographic effects. This work will support the PhD research and career preparation of a graduate student.
When water becomes denser over the shelf (due to cooling, brine rejection or evaporation), the resulting convection and cross-shelf density gradient lead to an eddy field that drives cascading across the shelf edge. This process is well understood in simple geometries when there are no complicating effects due to winds. Also, the behavior of dense slope currents (and their related eddies), such as those generated at the Denmark Strait or at Gibraltar, is also well-studied. This project will focus on two other aspects of the cascading problem. 1) A shelf-edge alongshore current is found off East Greenland, and these flow features are not uncommon globally. This project will address the stability of these currents, and, more importantly, the ability of the resulting eddy field to expedite cascading. 2) Winds are an important driver over much of the coastal ocean, so it makes sense to ask how they affect cross-shelf transports in a region where intense surface cooling creates eddies that contribute to cascading. It appears likely that wind and buoyancy forcing will couple nonlinearly, so that we should not think about a simple linear superposition of the two effects. Thus, this project will attack the question of how these two important forcing agents (plus irregular topography) affect each other. The approach used to address these problems involves multiple runs of idealized (meaning, for example, simple geometries, but using a realistic range of parameters such as forcing amplitude) numerical models, followed by a dynamically based scaling analysis that encapsulates the results quantitatively and that clarifies the processes involved.
