Journal article
Assessment of ensemble-based chemical data assimilation in an idealized setting
Atmospheric environment (1994), Vol.41(1), pp.18-36
2007
DOI: 10.1016/j.atmosenv.2006.08.006
Abstract
Data assimilation is the process of integrating observational data and model predictions to obtain an optimal representation of the state of the atmosphere. As more chemical observations in the troposphere are becoming available, chemical data assimilation is expected to play an essential role in air quality forecasting, similar to the role it has in numerical weather prediction (NWP). Considerable progress has been made recently in the development of variational tools for chemical data assimilation. In this paper, we assess the performance of the ensemble Kalman filter (EnKF). Results in an idealized setting show that EnKF is promising for chemical data assimilation.
Details
- Title: Subtitle
- Assessment of ensemble-based chemical data assimilation in an idealized setting
- Creators
- Emil M Constantinescu - Department of Computer Science, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061, USAAdrian Sandu - Department of Computer Science, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061, USATianfeng Chai - Center for Global and Regional Environmental Research, The University of Iowa, Iowa City, IA 52240, USAGregory R Carmichael - Center for Global and Regional Environmental Research, The University of Iowa, Iowa City, IA 52240, USA
- Resource Type
- Journal article
- Publication Details
- Atmospheric environment (1994), Vol.41(1), pp.18-36
- DOI
- 10.1016/j.atmosenv.2006.08.006
- ISSN
- 1352-2310
- eISSN
- 1873-2844
- Publisher
- Elsevier Ltd
- Language
- English
- Date published
- 2007
- Academic Unit
- Civil and Environmental Engineering; Nursing; Chemical and Biochemical Engineering
- Record Identifier
- 9984003983102771
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