Paper Info
Title
Inversion of airborne contaminants in a regional model
Abstract
We are interested in a DDDAS problem of localization of airborne contaminant releases in regional atmospheric transport models from sparse observations. Given measurements of the contaminant over an observation window at a small number of points in space, and a velocity field as predicted for example by a mesoscopic weather model, we seek an estimate of the state of the contaminant at the begining of the observation interval that minimizes the least squares misfit between measured and predicted contaminant field, subject to the convection-diffusion equation for the contaminant. Once the “initial” conditions are estimated by solution of the inverse problem, we issue predictions of the evolution of the contaminant, the observation window is advanced in time, and the process repeated to issue a new prediction, in the style of 4D-Var. We design an appropriate numerical strategy that exploits the spectral structure of the inverse operator, and leads to efficient and accurate resolution of the inverse problem. Numerical experiments verify that high resolution inversion can be carried out rapidly for a well-resolved terrain model of the greater Los Angeles area.
Year
DOI
Venue
2006
10.1007/11758532_64
International Conference on Computational Science (3)
Keywords
DocType
Volume
inverse operator,contaminant field,observation interval,airborne contaminant release,sparse observation,observation window,regional model,appropriate numerical strategy,inverse problem,accurate resolution,dddas problem,high resolution,velocity field,convection diffusion equation,atmospheric circulation,initial condition,least square
Conference
3993
ISSN
ISBN
Citations 
0302-9743
3-540-34383-0
7
PageRank 
References 
Authors
0.75
3
6
Name
Order
Citations
PageRank
Volkan Akcelik1374.73
George Biros293877.86
Andrei Drăgănescu3667.90
Omar Ghattas469761.43
Judith Hill5363.74
Bart van Bloemen Waanders670.75