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Kirstin Kober and George C. Craig

the perturbation method is applicable in any atmospheric model that allows for calculation of the relevant physical process information. The observational data used to evaluate the forecasts and the selected case studies in which the parameterization is tested will be introduced briefly as well as the analysis strategy for the suggested method. a. Physically based stochastic perturbations in the boundary layer We propose a concept of process-based model error representation in terms of a

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Volkmar Wirth, Michael Riemer, Edmund K. M. Chang, and Olivia Martius

; moreover, the forecast became rather poor after a lead time of as little as 5 days. The latter result seems to be at odds with the commonly held view that large-scale phenomena such as RWPs should be predictable on a rather long time scale. However, this evaluation was for a single case only involving a single forecast model; further systematic studies are required to possibly generalize these results. Regarding the waveguide, several operational forecast models are fraught with a spurious decrease of

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Gabriel Wolf and Volkmar Wirth

appropriate in the current context is the wave activity flux of Takaya and Nakamura (2001) . One particular feature of this formulation is its phase independence; this means that it discounts individual troughs and ridges and focuses on the dynamics of the entire wave packet instead ( Danielson et al. 2006 ). Focus on the entire wave packet is desirable, for instance, when studying model errors as opposed to initial condition errors ( Gray et al. 2014 ), and it would be interesting to find out whether

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