Book chapter
Ensemble–Based Data Assimilation for Atmospheric Chemical Transport Models
Computational Science – ICCS 2005, pp.648-655
Lecture Notes in Computer Science, volume 3515, Springer Berlin Heidelberg
2005
DOI: 10.1007/11428848_84
Abstract
The task of providing an optimal analysis of the state of the atmosphere requires the development of dynamic data-driven systems (d3as) that efficiently integrate the observational data and the models. In this paper we discuss fundamental aspects of nonlinear ensemble data assimilation applied to atmospheric chemical transport models. We formulate autoregressive models for the background errors and show how these models are capable of capturing flow dependent correlations. Total energy singular vectors describe the directions of maximum errors growth and are used to initialize the ensembles. We highlight the challenges encountered in the computation of singular vectors in the presence of stiff chemistry and propose solutions to overcome them. Results for a large scale simulation of air pollution in East Asia illustrate the potential of nonlinear ensemble techniques to assimilate chemical observations.
Details
- Title: Subtitle
- Ensemble–Based Data Assimilation for Atmospheric Chemical Transport Models
- Creators
- Adrian Sandu - Department of Computer Science, Virginia Polytechnic Institute and State University, BlacksburgEmil M Constantinescu - Department of Computer Science, Virginia Polytechnic Institute and State University, BlacksburgWenyuan Liao - Department of Computer Science, Virginia Polytechnic Institute and State University, BlacksburgGregory R Carmichael - Center for Global and Regional Environmental Research, The University of Iowa, Iowa CityTianfeng Chai - Center for Global and Regional Environmental Research, The University of Iowa, Iowa CityJohn H Seinfeld - Department of Chemical Engineering, California Institute of Technology, PasadenaDacian Dăescu - Department of Mathematics and Statistics, Portland State University,
- Resource Type
- Book chapter
- Publication Details
- Computational Science – ICCS 2005, pp.648-655
- Publisher
- Springer Berlin Heidelberg; Berlin, Heidelberg
- Series
- Lecture Notes in Computer Science; volume 3515
- DOI
- 10.1007/11428848_84
- eISSN
- 1611-3349
- ISSN
- 0302-9743
- Language
- English
- Date published
- 2005
- Academic Unit
- Nursing; Chemical and Biochemical Engineering; Civil and Environmental Engineering
- Record Identifier
- 9984003966602771
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