Climate Dynamics

, Volume 36, Issue 11–12, pp 2313–2337 | Cite as

Diagnostic budget study of the internal variability in ensemble simulations of the Canadian RCM

  • Oumarou Nikiema
  • René Laprise


Due to the chaotic and nonlinear nature of the atmospheric dynamics, it is known that small differences in the initial conditions (IC) of models can grow and affect the simulation evolution. In this study, we perform a quantitative diagnostic budget calculation of the various diabatic and dynamical contributions to the time evolution and spatial distribution of internal variability (IV) in simulations with the nested Canadian Regional Climate Model. We establish prognostic budget equations of the IV for the potential temperature and the relative vorticity fields. For both of these variables, the IV equations present similar terms, notably terms relating to the transport of IV by ensemble-mean flow and to the covariance of fluctuations acting on the gradient of the ensemble-mean state. We show the skill of these equations to diagnose the IV that took place in an ensemble of 20 3-month (summer season) simulations that differed only in their IC. Our study suggests that the dominant terms responsible for the large increase of IV are either the covariance term involving the potential temperature fluctuations and diabatic heating fluctuations, or the covariance of inter-member fluctuations acting upon ensemble-mean gradients. Our results also show that, on average, the third-order terms are negligible, but they can become important when the IV is large.


Internal variability equations Regional climate models Ensemble of simulations North American domain 



This research was done as the Masters project of the first author, as a project within the Canadian Regional Climate Modelling and Diagnostic (CRCMD) Network, which is financially supported by the Canadian Foundation for Climate and Atmospheric Science (CFCAS) and the Ouranos Consortium. Ouranos also provided local facilities. The authors are indebted to Dr. G. J. Boer (CCCma) for suggesting the diagnostic methodology. We would like to thank to Mourad Labassi and Abderrahim Khaled for maintaining user-friendly local computing facility, and to Mrs Adelina Alexandru for allowing us to use her simulated data.


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Copyright information

© Springer-Verlag 2010

Authors and Affiliations

  1. 1.Canadian Network for Regional Climate Modelling and Diagnostics, Centre ESCER, Département des Sciences de la Terre et de l’ AtmosphèreUQAMMontrealCanada

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