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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
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
, heat content, and precipitable water in North Atlantic cyclones. Mass and Dotson (2010) considered the structure of the strongest cyclones in the northwestern United States. They found the strongest winds southeast of the cyclones and interestingly a cold temperature anomaly at 850 hPa in the center. A bent-back warm front was found to be a typical feature of these storms. Considering the structure of extratropical cyclones is also an important aspect when evaluating climate model simulations
, heat content, and precipitable water in North Atlantic cyclones. Mass and Dotson (2010) considered the structure of the strongest cyclones in the northwestern United States. They found the strongest winds southeast of the cyclones and interestingly a cold temperature anomaly at 850 hPa in the center. A bent-back warm front was found to be a typical feature of these storms. Considering the structure of extratropical cyclones is also an important aspect when evaluating climate model simulations
the strong gradients associated with such an intense system. In this study we investigate the sensitivity of SVs with respect to different modeling configurations in order to evaluate the dynamical relevance of SVs computed in one configuration but applied to another. For ensemble forecasts as well as for observation targeting, the actual analysis uncertainty is also relevant [ Barkmeijer et al. 1998 , 1999 ; Reynolds et al. 2007 ; Lawrence et al. 2009 ; see Berliner et al. (1999) for a
the strong gradients associated with such an intense system. In this study we investigate the sensitivity of SVs with respect to different modeling configurations in order to evaluate the dynamical relevance of SVs computed in one configuration but applied to another. For ensemble forecasts as well as for observation targeting, the actual analysis uncertainty is also relevant [ Barkmeijer et al. 1998 , 1999 ; Reynolds et al. 2007 ; Lawrence et al. 2009 ; see Berliner et al. (1999) for a
of the extratropical trajectories on the angular momentum budget can again be evaluated semiquantitatively from the trajectory analysis. The total Eulerian angular momentum change of the subtropical jet over Africa for the time period between 0600 UTC 7 January and 0000 UTC 9 January amounted to 4 × 10 11 s −1 . This number can be compared to the total change of angular momentum change along the trajectories for different time intervals prior to reaching the jet. The mean accumulated angular
of the extratropical trajectories on the angular momentum budget can again be evaluated semiquantitatively from the trajectory analysis. The total Eulerian angular momentum change of the subtropical jet over Africa for the time period between 0600 UTC 7 January and 0000 UTC 9 January amounted to 4 × 10 11 s −1 . This number can be compared to the total change of angular momentum change along the trajectories for different time intervals prior to reaching the jet. The mean accumulated angular
