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Marlene Baumgart, Michael Riemer, Volkmar Wirth, Franziska Teubler, and Simon T. K. Lang

1. Introduction Numerical weather prediction has improved remarkably over the last decades (e.g., Bauer et al. 2015 ). Occasionally, however, very poor medium-range forecasts do still occur ( Rodwell et al. 2013 ). Forecast errors arise due to errors in the initial conditions and due to model deficiencies (e.g., Palmer and Hagedorn 2006 ). After 1–2 forecast days, localized errors may form that start to affect the synoptic-scale flow (e.g., Davies and Didone 2013 ; Martínez-Alvarado et al

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Kirstin Kober and George C. Craig

physically based stochastic perturbations will be introduced as well as the mesoscale weather prediction model used in this study and the verifying observational data. In section 3 , the method will be applied in several case studies representing two different weather regimes to assess the structure of the perturbations, their impact on the precipitation fields, and the sensitivities in parameter settings of the perturbations scheme. Additionally, forecast quality of other variables will be assessed

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Hilke S. Lentink, Christian M. Grams, Michael Riemer, and Sarah C. Jones

1. Introduction The extratropical transition (ET) of tropical cyclones (TCs) is associated with high-impact weather, both locally and in downstream regions ( Jones et al. 2003 ; Evans et al. 2017 ). The local direct impact is mainly caused by strong wind gusts and excessive precipitation. These are not always well forecasted because a numerical weather prediction model is prone to small errors that evolve during the complex interaction between a poleward-moving TC and its environment. The

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