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Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
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Volume 7, issue 4
Geosci. Model Dev., 7, 1451-1465, 2014
https://doi.org/10.5194/gmd-7-1451-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
Geosci. Model Dev., 7, 1451-1465, 2014
https://doi.org/10.5194/gmd-7-1451-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.

Methods for assessment of models 16 Jul 2014

Methods for assessment of models | 16 Jul 2014

Comparison of the ensemble Kalman filter and 4D-Var assimilation methods using a stratospheric tracer transport model

S. Skachko et al.
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Cited articles  
Anderson, J. L.: Spatially and temporally varying adaptive covariance inflation for ensemble filters, Tellus A, 61, 72–83, 2009.
Bannister, R. N.: A review of forecast error covariance statistics in atmospheric variational data assimilation. I: Characteristics and measurements of forecast error covariances, Q. J. Roy. Meteorol. Soc., 134, 1951–1970, 2008.
Buehner, M., Houtekamer, P. L., Charette, C., Mitchell, H. L., and He, B.: Intercomparison of Variational Data Assimilation and the Ensemble Kalman Filter for Global Deterministic NWP. Part I: Description and Single-Observation Experiments, Mon. Weather Rev., 138, 1550–1566, 2010a.
Buehner, M., Houtekamer, P. L., Charette, C., Mitchell, H. L., and He, B.: Intercomparison of Variational Data Assimilation and the Ensemble Kalman Filter for Global Deterministic NWP. Part II: One-Month Experiments with Real Observations, Mon. Weather Rev., 138, 1567–1586, 2010b.
Constantinescu, E. M., Sandu, A., Chai, T., and Carmichael, G. R.: Ensemble-based chemical data assimilation. I: General approach, Q. J. Roy. Meteorol. Soc., 133, 1229–1243, 2007a.
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