Impact of the Different Components of 4DVAR on the Global Forecast System of the Meteorological Service of Canada

Stéphane Laroche Meteorological Research Division, Environment Canada, Dorval, Québec, Canada

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Pierre Gauthier Meteorological Research Division, Environment Canada, Dorval, Québec, Canada

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Monique Tanguay Meteorological Research Division, Environment Canada, Dorval, Québec, Canada

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Simon Pellerin Meteorological Research Division, Environment Canada, Dorval, Québec, Canada

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Josée Morneau Meteorological Service of Canada, Environment Canada, Dorval, Québec, Canada

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Abstract

A four-dimensional variational data assimilation (4DVAR) scheme has recently been implemented in the medium-range weather forecast system of the Meteorological Service of Canada (MSC). The new scheme is now composed of several additional and improved features as compared with the three-dimensional variational data assimilation (3DVAR): the first guess at the appropriate time from the full-resolution model trajectory is used to calculate the misfit to the observations; the tangent linear of the forecast model and its adjoint are employed to propagate the analysis increment and the gradient of the cost function over the 6-h assimilation window; a comprehensive set of simplified physical parameterizations is used during the final minimization process; and the number of frequently reported data, in particular satellite data, has substantially increased. The impact of these 4DVAR components on the forecast skill is reported in this article. This is achieved by comparing data assimilation configurations that range in complexity from the former 3DVAR with the implemented 4DVAR over a 1-month period. It is shown that the implementation of the tangent-linear model and its adjoint as well as the increased number of observations are the two features of the new 4DVAR that contribute the most to the forecast improvement. All the other components provide marginal though positive impact. 4DVAR does not improve the medium-range forecast of tropical storms in general and tends to amplify the existing, too early extratropical transition often observed in the MSC global forecast system with 3DVAR. It is shown that this recurrent problem is, however, more sensitive to the forecast model than the data assimilation scheme employed in this system. Finally, the impact of using a shorter cutoff time for the reception of observations, as the one used in the operational context for the 0000 and 1200 UTC forecasts, is more detrimental with 4DVAR. This result indicates that 4DVAR is more sensitive to observations at the end of the assimilation window than 3DVAR.

Corresponding author address: Dr. Stéphane Laroche, Data Assimilation and Satellite Meteorology Section, Environment Canada, 2121 Trans-Canada Highway, Dorval, QC H9P 1J3, Canada. Email: stephane.laroche@ec.gc.ca

Abstract

A four-dimensional variational data assimilation (4DVAR) scheme has recently been implemented in the medium-range weather forecast system of the Meteorological Service of Canada (MSC). The new scheme is now composed of several additional and improved features as compared with the three-dimensional variational data assimilation (3DVAR): the first guess at the appropriate time from the full-resolution model trajectory is used to calculate the misfit to the observations; the tangent linear of the forecast model and its adjoint are employed to propagate the analysis increment and the gradient of the cost function over the 6-h assimilation window; a comprehensive set of simplified physical parameterizations is used during the final minimization process; and the number of frequently reported data, in particular satellite data, has substantially increased. The impact of these 4DVAR components on the forecast skill is reported in this article. This is achieved by comparing data assimilation configurations that range in complexity from the former 3DVAR with the implemented 4DVAR over a 1-month period. It is shown that the implementation of the tangent-linear model and its adjoint as well as the increased number of observations are the two features of the new 4DVAR that contribute the most to the forecast improvement. All the other components provide marginal though positive impact. 4DVAR does not improve the medium-range forecast of tropical storms in general and tends to amplify the existing, too early extratropical transition often observed in the MSC global forecast system with 3DVAR. It is shown that this recurrent problem is, however, more sensitive to the forecast model than the data assimilation scheme employed in this system. Finally, the impact of using a shorter cutoff time for the reception of observations, as the one used in the operational context for the 0000 and 1200 UTC forecasts, is more detrimental with 4DVAR. This result indicates that 4DVAR is more sensitive to observations at the end of the assimilation window than 3DVAR.

Corresponding author address: Dr. Stéphane Laroche, Data Assimilation and Satellite Meteorology Section, Environment Canada, 2121 Trans-Canada Highway, Dorval, QC H9P 1J3, Canada. Email: stephane.laroche@ec.gc.ca

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  • Bélair, S., J. Mailhot, C. Girard, and P. Vaillancourt, 2005: Boundary layer and shallow cumulus clouds in a medium-range forecast of a large-scale weather system. Mon. Wea. Rev., 133 , 19381960.

    • Search Google Scholar
    • Export Citation
  • Buizza, R., 1994: Sensitivity of optimal unstable structures. Quart. J. Roy. Meteor. Soc., 120 , 429451.

  • Chouinard, C., C. Charette, J. Hallé, P. Gauthier, J. Morneau, and R. Sarrazin, 2001: The Canadian 3D-Var analysis scheme on model vertical coordinate. Preprints, 14th Conf. on Numerical Weather Prediction, Fort Lauderdale, FL, Amer. Meteor. Soc., 14–18.

  • Côté, J., S. Gravel, A. Staniforth, A. Patoine, M. Roch, and A. N. Staniforth, 1998: The operational CMC-MRB global environmental multiscale (GEM) model. Mon. Wea. Rev., 126 , 13731395.

    • Search Google Scholar
    • Export Citation
  • Courtier, P., J-N. Thépaut, and A. Hollingsworth, 1994: A strategy for operational implementation of 4D-Var using an incremental approach. Quart. J. Roy. Meteor. Soc., 120 , 13671387.

    • Search Google Scholar
    • Export Citation
  • Fisher, M., and E. Andersson, 2001: Developments in 4D-Var and Kalman filtering. ECMWF Tech. Memo. 347, 38 pp.

  • Gauthier, P., C. Charette, L. Fillion, P. Koclas, and S. Laroche, 1999a: Implementation of a 3D variational data assimilation system at the Canadian Meteorological Centre. Part I: The global analysis. Atmos.–Ocean, 37 , 103156.

    • Search Google Scholar
    • Export Citation
  • Gauthier, P., M. Buehner, and L. Fillion, 1999b: Background-error statistics modelling in a 3D variational data assimilation scheme: Estimation and impact on the analysis. Proc. ECMWF Workshop on Diagnosis of Data Assimilation Systems, Reading, United Kingdom, ECMWF, 131–145.

  • Gauthier, P., C. Chouinard, and B. Brasnett, 2003: Quality control: Methodology and applications. Data Assimilation for the Earth System, R. Swinbank, V. Shutyaev, and W. A. Lahoz, Eds., NATO Science Series, IV: Earth and Environmental Sciences, Vol. 26, Kluwer Academic, 177–187.

    • Search Google Scholar
    • Export Citation
  • Gauthier, P., M. Tanguay, S. Laroche, S. Pellerin, and J. Morneau, 2007: Extension of 3DVAR to 4DVAR: Implementation of 4DVAR at the Meteorological Service of Canada. Mon. Wea. Rev., 135 , 23392354.

    • Search Google Scholar
    • Export Citation
  • Gilbert, J. C., and C. Lemaréchal, 1989: Some numerical experiments with variable-storage quasi-Newton algorithms. Math. Program., 45 , 407435.

    • Search Google Scholar
    • Export Citation
  • Järvinen, H., E. Andersson, and F. Bouttier, 1999: Variational assimilation of time sequences of surface observations with serially correlated errors. Tellus, 51A , 469488.

    • Search Google Scholar
    • Export Citation
  • Laroche, S., M. Tanguay, and Y. Delage, 2002: Linearization of a simplified planetary boundary layer parameterization. Mon. Wea. Rev., 130 , 20742087.

    • Search Google Scholar
    • Export Citation
  • Mahfouf, J-F., 2005: Linearization of a simple moist convection scheme for large-scale NWP models. Mon. Wea. Rev., 133 , 16551670.

  • Mahfouf, J-F., and F. Rabier, 2000: The ECMWF operational implementation of four dimensional variational assimilation. Part II: Experimental results with improved physics. Quart. J. Roy. Meteor. Soc., 126 , 11711190.

    • Search Google Scholar
    • Export Citation
  • Rabier, F., H. Järvinen, E. Klinker, J-F. Mahfouf, and A. Simmons, 2000: The ECMWF operational implementation of four dimensional variational assimilation. Part I: Experimental results with simplified physics. Quart. J. Roy. Meteor. Soc., 126 , 11431170.

    • Search Google Scholar
    • Export Citation
  • Tanguay, M., and S. Polavarapu, 1999: The adjoint of the semi-Lagrangian treatment of the passive tracer equation. Mon. Wea. Rev., 127 , 551564.

    • Search Google Scholar
    • Export Citation
  • Thépaut, J-N., R. N. Hoffman, and P. Courtier, 1993: Interactions of dynamics and observations in a four-dimensional variation assimilation. Mon. Wea. Rev., 121 , 33933414.

    • Search Google Scholar
    • Export Citation
  • Thépaut, J-N., P. Courtier, G. Belaud, and G. Lemaître, 1996: Dynamical structure functions in a four-dimensional variational assimilation: A case-study. Quart. J. Roy. Meteor. Soc., 122 , 535561.

    • Search Google Scholar
    • Export Citation
  • Zadra, A., M. Buehner, S. Laroche, and J-F. Mahfouf, 2004: Impact of the GEM model simplified physics on the extratropical singular vectors. Quart. J. Roy. Meteor. Soc., 130 , 25412569.

    • Search Google Scholar
    • Export Citation
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