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Quantification of Forecast Uncertainty and Data Assimilation using Wiener’s Polynomial Chaos Expansion 
Monday, 30 June 2014,  3:00 -  5:00
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Speaker: Lakshmivarahan, S.

George Lynn Cross Research Professor

School of Computer Science

University of Oklahoma, USA

Date: Monday, Jun 30, 2014

Time: 3 p.m.

Venue: Industrial Interface Bldg., Kodihalli.

 

Abstract:

Uncertainty in the dynamical forecast can arise from the uncertainty in three sources: initial/boundary conditions, parameters and forcing. By  expressing the uncertainty in the sources using the Wiener polynomial chaos expansion and using the orthogonality properties of Hermite polynomials, we can readily express the model forecast uncertainty. We also discuss the application of this to dynamic data assimilation using ensemble methods.

 

Location Venue: Conference Hall, C-MMACS New Bldg.
Contact Dr. Krishnamohan

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