University of Cambridge > Talks.cam > Isaac Newton Institute Seminar Series > Modeling of unresolved scales with data-inferred stochastic processes

Modeling of unresolved scales with data-inferred stochastic processes

Add to your list(s) Download to your calendar using vCal

If you have a question about this talk, please contact Mustapha Amrani.

Institute distinguished event

I will discuss a data-driven stochastic approach to modeling unresolved scales, in which feedback from micro-scale processes is represented by a network of Markov processes. The Markov processes are conditioned on macro-scale model variables, and their properties are inferred from pre-computed high-resolution (micro-scale resolving) simulations. These processes are designed to emulate, in a statistical sense, the feedback observed in the high-resolution simulations, thereby providing a statistical-dynamical coupling between micro- and macro-scale models. This work is primarily aimed at applications in atmosphere-ocean science (stochastic parameterizations of atmospheric convection and of mesoscale oceanic eddies).

This talk is part of the Isaac Newton Institute Seminar Series series.

Tell a friend about this talk:

This talk is included in these lists:

Note that ex-directory lists are not shown.

 

© 2006-2024 Talks.cam, University of Cambridge. Contact Us | Help and Documentation | Privacy and Publicity