2022 Ocean Mixing Gordon Research Conference and Gordon Research Seminar

Abstract

We request ONR funding to support the Gordon Research Conference on Ocean Mixing. Turbulent mixing results from complex and chaotic,motions that span a large range of spatial and temporal scales. As such, it is particularly challenging to measure and model (e.g.,,turbulence remains unsolved as one of the Clay Mathematics Institutes $1M Millennium Prize Problems). Yet it has vast and important,consequences. In the ocean, turbulent mixing controls transport of heat, freshwater, dissolved gasses, and pollutants. It is crucial, for ocean biology because it both determines the flow field for the smallest plankton, and it sets large-scale gradients of nutrien,t availability. It is also central to understanding the energetics of the ocean and reducing the uncertainties in global circulation, and climate models: recent work has shown that the spatial and temporal non-homogeneity in deep-ocean mixing may play a critical ro,le in climate; understanding the physics that drives the distribution of deep-ocean mixing intensity is critical. Yet even after a h,alf a century of efforts to understand its global distribution, observations are still sparse; a variety of direct and indirect meth,ods are still needed to characterize the dynamical processes that lead to turbulence, and inferences of mixing from larger scale bud,gets. As such, the physics of ocean mixing is actively studied using a variety of observational techniques (direct measure of veloci,ty and temperature fluctuations at the smallest (mm) scales, inferences from large-scale turbulent overturns, observations of net mi,xing by purposeful dye release) numerical and theoretical approaches, as well as laboratory experiments. Finally, the consequences o,f mixing for larger scale climate models (which do not directly resolve mixing) are addressed by turning dynamical insights of the p,reviously mentioned work into practical parameterizations. As a concrete example, using different mixing schemes in numerical climat,e models changes predicted tropical ocean temperatures by more than a degree and predicted sea level rise by more than 30 cm. Mixing, is one of the greatest sources of uncertainty plaguing todays models with impact of great societal relevance. The purpose and scope, of this Gordon Research Conference is to provide a forum for discussion of the rapidly evolving field of ocean mixing. Emphasis is,threefold: observations of mixing in the world, new insights into dynamics that control mixing rates, and impacts of mixing on regio,nal and global circulation and budgets. The latter two include development of parameterizations to turn dynamical insights into usef,ul things to include in regional models and global numerical climate models. Through ONR support, this Ocean Mixing GRC will: (1) pr,ovide a needed forum to improve the broader communitys understanding of turbulent mixing in the ocean, and with it a variety of dee,p and broad implications for everything from climate change to global nutrient patterns that underlie our fisheries. The GRC format,encourages precisely the sort of interdisciplinary thinking and collaboration that is so vital to addressing these societal issues.,(2) help our scientific community be the most vibrant,versity, which, while improved in recent years, still needs an influx of new people, a broadening of ties amongst domestic and inter,national collaborators, and increased interdisciplinary interactions. ONR support will explicitly be used to expand the demographic,, professional and geographic diversity of participants by supporting attendance of under-represented and under-resourced groups who

Document Details

Document Type
DoD Grant Award
Publication Date
Apr 01, 2022
Source ID
N000142212251

Entities

People

  • Jonathan D. Nash

Organizations

  • Gordon Research Conferences
  • Office of Naval Research
  • United States Navy

Tags

Fields of Study

  • Environmental science

Readers

  • Academic Conference Management
  • Ocean-Atmosphere Mesoscale Modeling, Data Assimilation, and Flux Boundary Layers
  • Systems Analysis and Design

Technology Areas

  • AI & ML