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SUMMARY:Quantifying uncertainty and improving reduced-order predictions of
  partially observed turbulent dynamical systems - Branicki\, M (New York U
 niversity)
DTSTART:20131029T134000Z
DTEND:20131029T141500Z
UID:TALK48551@talks.cam.ac.uk
CONTACT:Mustapha Amrani
DESCRIPTION:Co-author: A. J. Majda (Courant Institute\, NYU)\n\nThe issue 
 of mitigating model error in reduced-order prediction of high-dimensional 
 dynamics  is particularly important when dealing with turbulent geophysica
 l systems with rough energy spectra and intermittency near the resolution 
 cut-off of the corresponding numerical models. I will discuss a new framew
 ork which allows for information-theoretic quantification of uncertainty a
 nd mitigation of model error in imperfect stochastic/statistical predictio
 ns of non-Gaussian\, multi-scale dynamics. In particular\, I will outline 
 the utility of this framework in derivation of a sufficient condition for 
 improving imperfect predictions via a popular but heuristic Multi Model En
 semble approach. Time permitting\, the role and validity of 'fluctuation-d
 issipation' arguments for improving imperfect predictions of externally pe
 rturbed non-autonomous turbulent systems will also be addressed.\n
LOCATION:Seminar Room 1\, Newton Institute
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