Articles | Volume 16, issue 5
Research article
17 Mar 2016
Research article |  | 17 Mar 2016

Variational data assimilation for the optimized ozone initial state and the short-time forecasting

Soon-Young Park, Dong-Hyeok Kim, Soon-Hwan Lee, and Hwa Woon Lee

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Cited articles

Balgovind, R., Dalcher, A., Ghil, M., and Kalnay, E.: A Stochastic-Dynamic Model for the Spatial Structure of Forecast Error Statistics, Mon. Weather Rev., 111, 701–722,<0701:Asdmft>2.0.Co;2, 1983.
Bocquet, M., Elbern, H., Eskes, H., Hirtl, M., Žabkar, R., Carmichael, G. R., Flemming, J., Inness, A., Pagowski, M., Pérez Camaño, J. L., Saide, P. E., San Jose, R., Sofiev, M., Vira, J., Baklanov, A., Carnevale, C., Grell, G., and Seigneur, C.: Data assimilation in atmospheric chemistry models: current status and future prospects for coupled chemistry meteorology models, Atmos. Chem. Phys., 15, 5325–5358,, 2015.
Boisgontier, H., Mallet, V., Berroir, J. P., Bocquet, M., Herlin, I., and Sportisse, B.: Satellite data assimilation for air quality forecast, Simul. Model. Pract. Th., 16, 1541–1545,, 2008.
Byun, D. W. and Ching, J. K. S.: Science algorithms of the EPA models-3 Community Multiscale Air Quality (CMAQ) modeling system, EPA/600/R-99/030, US EPA, Research Triangle Park, USA, 1999.
Carmichael, G. R., Sandu, A., Chai, T., Daescu, D. N., Constantinescu, E. M., and Tang, Y.: Predicting air quality: Improvements through advanced methods to integrate models and measurements, J. Comput. Phys., 227, 3540–3571,, 2008.
Short summary
In order to improve the predictability of air quality, we optimize initial ozone state throughout the 4D-Var data assimilation. Previously developed code for the data assimilation has been modified to consider background error in matrix form, and various numerical tests are conducted. A surface observational assimilation is conducted and the statistical results for the 12 h assimilation periods show a 49.4 % decrease in RMSE and a 59.9 % increase in IOA.
Final-revised paper