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Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
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Volume 9, issue 8
Geosci. Model Dev., 9, 2893-2908, 2016
https://doi.org/10.5194/gmd-9-2893-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
Geosci. Model Dev., 9, 2893-2908, 2016
https://doi.org/10.5194/gmd-9-2893-2016
© 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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Cited articles  
Anderson, E. and Järvinen, H.: Variational quality control, Q. J. Roy. Meteor. Soc., 125, 697–722, https://doi.org/10.1002/qj.49712555416, 1999.
Anderson, J. L.: Localization and Sampling Error Correction in Ensemble Kalman Filter Data Assimilation, Mon. Weather Rev., 140, 2359–2371, https://doi.org/10.1175/MWR-D-11-00013.1, 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, https://doi.org/10.5194/acp-15-5325-2015, 2015.
Brasseur, G. and Solomon, S.: Aeronomy of the middle atmosphere: chemistry and physics of the stratosphere and mesosphere, Springer Netherlands, Dordrecht, Reidel, https://doi.org/10.1007/1-4020-3824-0, 1986, 2005.
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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,...
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