Computer Science Technical Reports
CS at VT

Ensemble-based chemical data assimilation I: An idealized setting

Constantinescu, Emil M and Sandu, Adrian and Chai, Tianfeng and Carmichael, Gregory R (2006) Ensemble-based chemical data assimilation I: An idealized setting. Technical Report TR-06-06, Computer Science, Virginia Tech.

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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. 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.

Item Type:Departmental Technical Report
Keywords:data assimilation, ensemble Kalman filter, chemical and transport models, atmospheric models
Subjects:Computer Science > Numerical Analysis
ID Code:743
Deposited By:Constantinescu, Mr. Emil M.
Deposited On:05 April 2006