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SUMMARY:Modeling of unresolved scales with data-inferred stochastic proces
 ses - Crommelin\, D (Centrum voor Wiskunde en Informatica (CWI))
DTSTART:20140317T113000Z
DTEND:20140317T121000Z
UID:TALK51456@talks.cam.ac.uk
CONTACT:Mustapha Amrani
DESCRIPTION:I will discuss a data-driven stochastic approach to modeling u
 nresolved scales\, in which feedback from micro-scale processes is represe
 nted by a network of Markov processes. The Markov processes are conditione
 d on macro-scale model variables\, and their properties are inferred from 
 pre-computed high-resolution (micro-scale resolving) simulations. These pr
 ocesses are designed to emulate\, in a statistical sense\, the feedback ob
 served in the high-resolution simulations\, thereby providing a statistica
 l-dynamical coupling between micro- and macro-scale models. This work is p
 rimarily aimed at applications in atmosphere-ocean science (stochastic par
 ameterizations of atmospheric convection and of mesoscale oceanic eddies).
  \n
LOCATION:Seminar Room 1\, Newton Institute
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