Join us on Wednesday, June 16th at noon PST for a seminar about Ocean Dynamics with presentations by Miguel Jimenez-Urias, Postdoctoral Fellow of Earth and Planetary Sciences at Johns Hopkins University, and Laure Zanna, Professor of Mathematics and Atmosphere/Ocean Science at New York University.
Zoom link: https://umich.zoom.us/j/92607163508
“Oceanic stirring and Mixing of Passive Scalars: A Novel Closure”
Abstract: Tracers that help regulate biogeochemical cycles in the ocean and atmosphere have complex spatial distributions due to the combined effect of stirring by the multi-scale shearing motions that are ubiquitous and persistent in the ocean, and the small-scale diffusive mixing resulting in spatially inhomogeneous, enhanced mixing rates. Computer models need to parameterize the effect of shear dispersion due to restrictions on computer power and numerical stability when running climate-scale ocean simulations. Such parameterizations, however, fail to represent scale dependency, an assumption not strictly applicable to the ocean. In this talk, we present new results describing scale-dependency of shear-dispersion by idealized oceanic flows that can lead to a better understanding and representation of tracer distribution in the oceans.
Miguel Jimenez-Urias is a computational physical oceanographer interested in improving our understanding of ocean circulation, through the use of theory, computer simulations and global ocean circulation models. He is currently a postdoctoral fellow at Johns Hopkins University.
“Blending Machine Learning and Physics to Improve Climate Models”
Abstract: Numerical simulations used for weather and climate predictions solve approximations of the governing laws of fluid motions on a grid. Ultimately, uncertainties in climate predictions originate from the poor or lacking representation of processes, such as ocean turbulence and clouds that are not resolved on the grid of global climate models. The representation of these unresolved processes has been a bottleneck in improving climate simulations and projections.
The Data Science Coast to Coast (DS C2C) seminar series is co-hosted by the eScience Institute, along with data science institutes at New York University, Rice University, Stanford University, University of California – Berkeley, University of Michigan and the Academic Data Science Alliance (ADSA).
In the first half of 2021, we will host five seminars, each featuring one faculty member and one postdoctoral fellow from two universities. Each speaker will give a 20-minute talk about ongoing projects and motivating issues, followed by 20 minutes of discussion with the audience. These seminars will be the launching point for follow-on research discussion meetings which will hopefully lead to fruitful collaborative research.