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Ensemble forecasting at NMC: the generation of perturbations
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    On December 7 1992, NMC started operational ensemble forecasting (Tracton et al., 1993). The ensemble forecast configuration implemented provides 14 independent forecasts every day verifying on days one through ten. In this paper we briefly review existing methods for creating perturbations for ensemble forecasting. We point out that a regular analysis cycle is a "breeding ground" for fast growing modes. Based on this observation, we devise a simple and inexpensive method to generate growing modes of the atmosphere. The new method, "Breeding of Growing Modes", or BGM, consists of one additional, perturbed short-range forecast, introduced on top of the regular analysis in an analysis cycle. The difference between the control and perturbed six hour ("first guess") forecast is scaled back to the size of the initial perturbation and then reintroduced onto the new atmospheric analysis. Thus, the perturbation evolves along with the time dependent analysis fields, ensuring that after a few days of cycling, the perturbation field consists of a superposition of fast growing modes corresponding to the contemporaneous atmosphere, similar to the errors "bred" by the analysis cycle. We argue that the results of the BGM method are comparable to those that can be obtained using the linear adjoint method suggested by Lorenz (1965) to generate the fastest growing perturbations, only as long as the perturbations are linear. When the perturbations are nonlinear, however, the BGM method provides a more faithful reproduction of the error growth that takes place in the analysis cycle than the Lorenz method. In particular, fast growing but low-energy and therefore mostly irrelevant perturbations, such as those associated with convection, are filtered out in both the analysis cycle and the BGM method. However, they would dominate the spectrum of fast growing perturbations in the Lorenz method if the physical parameterizations of the primitive equations model were faithfully included. This, and its low cost and simplicity, are advantages that the BGM method has over Lorenz' method, which is also used experimentally at other centers (ECMWF, NCAR). Preliminary results indicate that ensembles of just two BGM forecasts achieve better results than much larger Monte Carlo or Lagged Average Forecast ensembles. Therefore, the operational ensemble configuration at NMC is based on the BGM method to generate efficient initial perturbations.

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