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Gérald Desroziers, Loïk Berre, Vincent Chabot, and Bernard Chapnik

improve them. The use of an ensemble of assimilations is a way to optimize the description of background error covariance matrix 𝗕. Ensembles of assimilations can be based on an explicit perturbation of observations in order to provide implicit background perturbations, representative of background errors, from which useful statistics can be deduced. They are implemented, or planned to be implemented, in operational centers such as the ECMWF ( Isaksen et al. 2007 ) or Météo-France ( Berre et al. 2007

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Derek J. Posselt and Tomislava Vukicevic

model. Because cloud microphysical processes in nature directly feed back to cloud-scale (and larger) dynamics, we plan to run MCMC-based studies of parameter sensitivity using 2D and 3D versions of the GCE model. In addition, we note that, because the PDFs produced by the inversion are conditional and depend on the chosen model and observations, use of observations more directly related to the details of the particle size distribution (e.g., radar reflectivity) will change the nature of the

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Junjie Liu, Hong Li, Eugenia Kalnay, Eric J. Kostelich, and Istvan Szunyogh

: Sequential data assimilation with a nonlinear quasi-geostrophic model using Monte Carlo methods to forecast error statistics. J. Geophys. Res. , 99 , (C5) . 10143 – 10162 . Holm , E. , E. Anderson , A. Beljaars , P. Lopez , J-F. Mahfouf , A. J. Simmons , and J-N. Thepaut , 2002 : Assimilation and modeling of the hydrological cycle: ECMWF’s status and plans. ECMWF Tech. Memo. 383, 55 pp . Houtekamer , P. L. , and H. L. Mitchell , 2001 : A sequential ensemble Kalman filter

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