Research Direction: Humans depend on inland waters to survive. Lakes contribute to a healthy environment, supply sustainable cities with enough water, and are an Essential Climate Variable according to the World Meteorological Organization. However, drinking water reservoirs are shrinking across the globe, while lake temperatures are rising and becoming increasingly hostile to life. Quantifying the physical processes affecting these aquatic systems will enable us to create solutions to these global problems.
Our research program uses mathematical models to solve fluid mechanics challenges. We construct these physical models from a combination of theory, laboratory measurements, and numerical simulations. Our current research focuses on physical processes in lakes, which have many analogues in other systems such as oceanography and geophysics. By combing new advances in data science and laboratory methods, we model the fundamental mixing processes in the environment.
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Winter Mixing Processes: Recent research has highlighted both the importance and lack of understanding of winter processes in ice-covered lakes. We have made progress on some of these processes: brine rejection, cold-water convection, and radiatively driven convection. However, it remains unclear how and when these processes will dominate the convective transport in these systems. |
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Laboratory-data assimilation: Our understanding of lakes is currently limited by our data. Data from field studies and laboratory experiments are often sparse compared to the resolution required to characterize the controlling processes, such as mixing. We use new data science techniques to assimilate data from the laboratory into numerical models. The ability to accurately integrate laboratory data into a numerical code provides access to data that laboratory experiments cannot measure in systems that would be inaccessible by computer simulations alone. |
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Stratified turbulence: Historically, vortex rings were used to model turbulent eddies in a much more chaotic environment. We returned to this problem, implementing modern experimental and numerical techniques to quantify how vortex rings mix a stratification. We demonstrated that the repetitive impact of a vortex ring on a stratified interface will result in self-similar mixing. |