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  • Auligné T, Lorenc AC, Michel Y, Montmerle T, Jones A, Hu M, Dudhia J. 2010. Summary of the Cloud Analysis Workshop, 1–3 Sept, NCAR, Boulder, CO, USA. Bull. Am. Meteorol. Soc. in press.
  • Bannister RN. 2008. A review of forecast-error covariance statistics in atmospheric variational data assimilation. I: Characteristics and measurements of forecast-error covariances. Q. J. R. Meteorol. Soc. 134: 19511970.
  • Barker DM, Huang W, Guo YR, Bourgeois AJ, Xiao QN. 2004. A three-dimensional variational data assimilation system for MM5: Implementation and initial results. Mon. Weather Rev. 132 897914.
  • Berre L. 2000. Estimation of synoptic and mesoscale forecast error cavariances in a limited-area model. Mon. Weather Rev. 128: 644667.
  • Berre L, Vignes O. 2002. ‘Humidity assimilation experiments with the HIRLAM 3D-Var’. In Proceedings of the ECMWF/GEWEX workshop on humidity analysis, 8–11 July. ECMWF: Reading, UK. 6978.
  • Berre L, Stefanescu SE, Belo Pereira M. 2006. The representation of the analysis effect in three error simulation techniques. Tellus 58A: 196209.
  • Berre L, Pannekoucke O, Desroziers G, Stefanescu SE, Chapnik B, Raynaud L.. 2007. ‘A variational assimilation ensemble and the spatial filtering of its error covariances: Increase of sample size by local spatial averaging’. In Proceedings of workshop on flow-dependent aspects of data assimilation, 11–13 June. ECMWF: Reading, UK. 151168.
  • Brousseau P, Bouttier F, Hello G, Seity Y, Fischer C, Berre L, Montmerle T, Auger L, Malardel S. 2008. ‘A prototype convective-scale data assimilation system for operation: The AROME-RUC’. HIRLAM Tech. Report 68. 2330.
  • Caron J-F, Fillion L. 2010. An examination of background-error correlations between mass and rotational wind over precipitation regions. Mon. Weather Rev. 138: 563578.
  • Courtier P, Thépaut J-N, Hollingsworth A. 1994. A strategy for operational implementation of 4D-Var using an incremental approach. Q. J. R. Meteorol. Soc. 120: 13671387.
  • Courtier P, Andersson E, Heckley W, Pailleux J, Vasiljevic D, Hollingsworth A, Fisher M, Rabier F. 1998. The ECMWF implementation of three-dimensional variational assimilation (3D-Var). I: Formulation. Q. J. R. Meteorol. Soc. 124: 17831807.
  • Daley R. 1991. Atmospheric data analysis. Cambridge University Press: Cambridge, UK.
  • Derber JC, Bouttier F. 1999. A reformulation of the background-error covariance in the ECMWF global data assimilation system. Tellus 51A: 195221.
  • Desroziers G, Berre L, Pannekoucke O, Stefanescu S, Brousseau P, Auger L, Chapnik B, Raynaud L. 2008. 'Flow-dependent error covariances from variational assimilation ensembles on global and regional domains'. HIRLAM Tech. Report 68. 522.
  • Fillion L, Belair S. 2004. Tangent-linear aspects of the Kain-Fritsch moist-convective parameterization scheme. Mon. Weather Rev. 132: 24772494.
  • Fischer C, Montmerle T, Berre L, Auger L, Stefanescu S. 2005. An overview of the variational assimilation in the ALADIN/France numerical weather-prediction system wave-driven circulation of the mesosphere. Q. J. R. Meteorol. Soc. 131: 34773492.
  • Fisher M. 2003. ‘Background error modelling’. In Proceedings of seminar on recent developments in data assimilation for atmosphere and ocean. ECMWF: Reading, UK. 4563.
  • Fisher M, Leutbecher M, Kelly GA. 2005. On the equivalence between Kalman smoothing and weak-constraint four-dimensional variational data assimilation. Q. J. R. Meteorol. Soc. 131: 32353246.
  • Houtekamer PL, Lefaivre L, Derome J, Ritchie H, Mitchell HL. 1996. A system simulation approach to ensemble prediction. Mon. Weather Rev. 124: 12251242.
  • Kucukkaraca E, Fisher M. 2006. 'Use of analysis ensembles in estimating flow-dependent background-error variances'. Tech. Memo. 492. ECMWF: Reading, UK.
  • Liu C, Xiao Q, Wang B. 2008. An ensemble-based four-dimensional variational data assimilation scheme. Part I: Technical formulation and preliminary test. Mon. Weather Rev. 136: 33633373.
  • Liu J, Li H, Kalnay E, Kostelich EJ, Szunyogh I. 2009. Univariate and multivariate assimilation of AIRS humidity retrievals with the local Ensemble Transform Kalman Filter. Mon. Weather Rev. 137: 39183932.
  • Lorenc AC, Roulstone I, White AA. 2003. ‘On the choice of control fields in Var’. Forecasting Research Tech. Report 419. Met Office: Exeter, UK.
  • Montmerle T, Lafore J-P, Berre L, Fischer C. 2006. Limited-area model error statistics over Western Africa: Comparisons with midlatitude results. Q. J. R. Meteorol. Soc. 132: 213230.
  • Montmerle T, Faccani C. 2009. Mesoscale assimilation of radial velocities from Doppler radar in a pre-operational framework. Mon. Weather Rev. 137: 19371953.
  • Pagé C, Fillion L, Zwack P. 2007. Diagnosing summertime mesoscale vertical motion: implications for atmospheric data assimilation. Mon. Weather Rev. 135: 20762094.
  • Pannekoucke O, Berre L, Desroziers G. 2007. Filtering properties of wavelets for the local background-error correlations. Q. J. R. Meteorol. Soc. 133: 363379.
  • Parrish DF, Derber JC, Purser RJ, Wu W-S, Pu Z-X. 1997. The NCEP global analysis system: recent improvements and future plans. J. Meteorol. Soc. Japan 75: 359365.
  • Raynaud L, Berre L, Desroziers G. 2009. Objective filtering of ensemble-based background-error variances. Q. J. R. Meteorol. Soc. 135: 11771199.
  • Wattrelot E, Caumont O, Pradier-Vabre S, Jurasek M, Haase G. 2008. ‘1D+3D-Var assimilation of radar reflectivities in the pre-operational AROME model at Météo-France’. In Proceedings of the European Radar Conference, Helsinki, Finland. 30 June–4 July.