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Martin Weissmann, Florian Harnisch, Chun-Chieh Wu, Po-Hsiung Lin, Yoichiro Ohta, Koji Yamashita, Yeon-Hee Kim, Eun-Hee Jeon, Tetsuo Nakazawa, and Sim Aberson

forecasts by different models is presented in section 3 , followed by a discussion of the influence of T-PARC observations on ECMWF forecasts in midlatitudes over the Pacific and on the Northern Hemisphere in section 4 . The discussion and conclusions are presented in section 5 . 2. Model descriptions a. JMA GSM experiment description To evaluate the impact of the T-PARC 2008 special observations, experiments using the operational global 4D-Var system and the operational JMA global spectral model

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Lisa-Ann Quandt, Julia H. Keller, Olivia Martius, and Sarah C. Jones

information about surface impacts from available operational ensemble forecasts. We address the following research questions. Does low predictability of the blocking transfer to a low predictability of the associated high-impact weather? What are the main development scenarios of the block in the forecast? Can the scenarios be linked to specific impacts or a lack thereof? We focus on the three major developmental stages of the block’s life cycle: the onset phase, the mature stage, and the decay phase

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Maxi Boettcher and Heini Wernli

realistic model setting. And finally, it is unclear how well operational forecast models predict the generation, propagation, and intensification of a DRW. A first study dealing with this issue has been performed for the storm Lothar by Kenzelmann (2005) . They analyzed the 50 simulations of the ECMWF ensemble prediction system and identified a strong sensitivity of the track and intensity of the mature storm to its structure and position relative to the jet axis during the DRW propagation phase

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Lars Wiegand, Arwen Twitchett, Cornelia Schwierz, and Peter Knippertz

://www.wmo.int/pages/prog/arep/wwrp/new/thorpex_new.html ) established a new data archive called the THORPEX International Grand Global Ensemble (TIGGE) that comprises ensemble predictions from different meteorological centers. Daily updated TIGGE forecast products and verifications are provided by Matsueda and Nakazawa online ( http://tparc.mri-jma.go.jp/TIGGE/index.html ). TIGGE was initiated at a workshop at the ECMWF in 2005 ( Richardson et al. 2005 ) to enhance collaborations in the development of EPSs between operational centers and universities by

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Florian Harnisch and Martin Weissmann

collaboration with T-PARC, the Taiwanese Astra Jet was operated under the research program Dropwindsonde Observations for Typhoon Surveillance near the Taiwan Region (DOTSTAR), where dropsonde observations are deployed operationally on TCs that pose a threat to the Taiwanese island ( Wu et al. 2005 , 2007b ). This study investigates the benefit of T-PARC dropsonde observations in different locations on the basis of data denial experiments with the European Centre for Medium-Range Weather Forecasts (ECMWF

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Kirstin Kober, Annette M. Foerster, and George C. Craig

1. Introduction The skill of numerical forecasts of convective precipitation is limited by several sources of uncertainty that can be minimized, but never completely removed. The initial and the boundary conditions for the model integration have limited accuracy and additionally physical processes have to be approximated and truncated to the model’s grid. Furthermore, the atmosphere is chaotic and the physical nature of convection stochastic. Ensembles of different model integrations and their

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Julia H. Keller

and Torn 2008 ) and was successfully applied to investigate the effect of initial condition uncertainty (or perturbations) on short-range ensemble forecasts (e.g., Hawblitzel et al. 2007 ; Sippel and Zhang 2008 ; Torn and Hakim 2008 ; Torn 2010a , b ; Torn and Cook 2013 ) or for revealing the dynamical and physical dependencies in operational medium-range ensemble forecasts (e.g., Schumacher 2011 ; Chang et al. 2013 ; Zheng et al. 2013 ). The studies by Harr and Dea (2009) and Keller et

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Julia H. Keller, Sarah C. Jones, and Patrick A. Harr

analysis data, available at 10 and more pressure levels (referred to as vertical output resolution in the remainder). However, data from the operational ECMWF EPS is only available at nine pressure levels. Vertical velocity, which is crucial for the computation of the baroclinic conversion (cf. section 2c ), is only available at six pressure levels. This requires determination as to whether the coarse vertical output resolution of the ECMWF EPS forecast data is sufficient to adequately define the K e

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

. Res. , 101 , 1435 – 1456 , https://doi.org/10.1029/95JD02674 . 10.1029/95JD02674 Bauer , P. , A. Thorpe , and G. Brunet , 2015 : The quiet revolution of numerical weather prediction . Nature , 525 , 47 – 55 , https://doi.org/10.1038/nature14956 . 10.1038/nature14956 Boer , G. J. , 1984 : A spectral analysis of predictability and error in an operational forecast system . Mon. Wea. Rev. , 112 , 1183 – 1197 , https://doi.org/10.1175/1520-0493(1984)112<1183:ASAOPA>2.0.CO;2 . 10

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Kirstin Kober and George C. Craig

fully compressible equations of motion on an Arakawa-C grid that is chosen to have a horizontal resolution of 0.025° (approximately 2800 m) and 50 vertical levels by a terrain following coordinate system (Lorenz grid staggering). Model forecasts are computed over 24 h with a time step of 25 s. The domain over which the model is integrated is smaller than the operational version run at the Deutscher Wetterdienst (DWD) and is centered over Germany ( Fig. 1 ). Initial and boundary conditions are

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