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Volume 9, issue 8 | Copyright
Geosci. Model Dev., 9, 2893-2908, 2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

Methods for assessment of models 26 Aug 2016

Methods for assessment of models | 26 Aug 2016

EnKF and 4D-Var data assimilation with chemical transport model BASCOE (version 05.06)

Sergey Skachko et al.
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Revised manuscript accepted for GMD
Cited articles
Anderson, E. and Järvinen, H.: Variational quality control, Q. J. Roy. Meteor. Soc., 125, 697–722,, 1999.
Anderson, J. L.: Localization and Sampling Error Correction in Ensemble Kalman Filter Data Assimilation, Mon. Weather Rev., 140, 2359–2371,, 2012.
Bocquet, M., Elbern, H., Eskes, H., Hirtl, M., vZabkar, 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.
Brasseur, G. and Solomon, S.: Aeronomy of the middle atmosphere: chemistry and physics of the stratosphere and mesosphere, Springer Netherlands, Dordrecht, Reidel,, 1986, 2005.
Publications Copernicus
Short summary
In the present work, we performed a comparison of two broadly used data assimilation algorithms, 4D-Var and EnKF, applied to a state-of-the-art atmospheric chemistry transport model. The comparison is carried out using carefully calibrated error statistics. The paper discusses the advantages and disadvantages of each method applied to real-life conditions of a numerical atmospheric chemistry data assimilation.
In the present work, we performed a comparison of two broadly used data assimilation algorithms,...