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Peter Vogel, Peter Knippertz, Andreas H. Fink, Andreas Schlueter, and Tilmann Gneiting

tropical Africa. Despite only moderately negative skill in the raw forecasts, postprocessing can only achieve neutral skill here. This suggests that the discrepancy between the more frequent and lighter rain generally produced by convection schemes and the very concentrated, long-lived and intense mesoscale convective systems in reality is too large to be cured by a relatively simple statistical correction. The singularity of tropical Africa is also seen in Fig. 2a by Wheeler et al. (2017) using

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Peter Vogel, Peter Knippertz, Andreas H. Fink, Andreas Schlueter, and Tilmann Gneiting

( Lafore et al. 2017 ), but large parts of the tropical landmasses are dominated by convection that initiates from small-scale surface and boundary layer processes and sometimes is organized into mesoscale convective systems (MCSs). The latter depends mostly on the thermodynamic profile and vertical wind shear. Within this context, northern tropical Africa, particularly the semiarid Sahel, can be considered a region where precipitation forecasting is particularly challenging. The area consists of vast

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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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Tobias Selz, Lotte Bierdel, and George C. Craig

prediction, including error growth ( Lorenz 1969 ; Durran and Gingrich 2014 ; Weyn and Durran 2017 ) and the accuracy of numerical forecasting systems ( Skamarock 2004 ; Frehlich and Sharman 2008 ; Ricard et al. 2013 ; Skamarock et al. 2014 ). In a seminal paper, Nastrom et al. (1984) considered KE spectra based on flight-track data taken in the course of the Global Atmospheric Sampling Program (GASP), motivated in part by the expectation of a mesoscale energy gap ( Fiedler and Panofsky 1970

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Kevin Bachmann, Christian Keil, George C. Craig, Martin Weissmann, and Christian A. Welzbacher

simulation using conventional observations only by 1–3 h in forecast horizon. A case study shows that DE-DA-3DRad produces superior mesoscale structures, wind fields and probabilistic precipitation forecasts. However, the impact is considerably more short lived than in the idealized environment. These results are contrasted with forecasts using the currently operational KENDA setup at DWD (direct assimilation of conventional observations plus the LHN assimilation of radar precipitation, DE-DA-LHN). Both

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Tobias Selz

: Theoretical aspects of upscale error growth on the mesoscales: Idealized numerical simulations . Quart. J. Roy. Meteor. Soc. , 144 , 682 – 694 , . 10.1002/qj.3236 Buizza , R. , and M. Leutbecher , 2015 : The forecast skill horizon . Quart. J. Roy. Meteor. Soc. , 141 , 3366 – 3382 , . 10.1002/qj.2619 Craig , G. C. , and B. G. Cohen , 2006 : Fluctuations in an equilibrium convective ensemble. Part I: Theoretical formulation

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Andreas Schäfler, George Craig, Heini Wernli, Philippe Arbogast, James D. Doyle, Ron McTaggart-Cowan, John Methven, Gwendal Rivière, Felix Ament, Maxi Boettcher, Martina Bramberger, Quitterie Cazenave, Richard Cotton, Susanne Crewell, Julien Delanoë, Andreas Dörnbrack, André Ehrlich, Florian Ewald, Andreas Fix, Christian M. Grams, Suzanne L. Gray, Hans Grob, Silke Groß, Martin Hagen, Ben Harvey, Lutz Hirsch, Marek Jacob, Tobias Kölling, Heike Konow, Christian Lemmerz, Oliver Lux, Linus Magnusson, Bernhard Mayer, Mario Mech, Richard Moore, Jacques Pelon, Julian Quinting, Stephan Rahm, Markus Rapp, Marc Rautenhaus, Oliver Reitebuch, Carolyn A. Reynolds, Harald Sodemann, Thomas Spengler, Geraint Vaughan, Manfred Wendisch, Martin Wirth, Benjamin Witschas, Kevin Wolf, and Tobias Zinner

Multiaircraft and ground-based observations were made over the North Atlantic in the fall of 2016 to investigate the importance of diabatic processes for midlatitude weather. Progress in understanding the processes controlling midlatitude weather is one of the factors that have contributed to a continuous improvement in the skill of medium-range weather forecasts in recent decades ( Thorpe 2004 ; Richardson et al. 2012 ; Bauer et al. 2015 ). Additionally, numerical weather prediction (NWP

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Roderick van der Linden, Andreas H. Fink, Joaquim G. Pinto, and Tan Phan-Van

with thin, dashed lines. The orange dot denotes the location of the center of the ECMWF grid box that was used in the evaluation of the ensemble forecast (cf. Fig. 11 ). The green dot indicates the location of the Phu Lien radar station, and the blue dots denote the locations of the Bach Long Vy (WMO station ID 48839) and Beihai (WMO station ID 59644) radiosonde stations. According to D.-Q. Nguyen et al. (2014) , northeastern Vietnam can be separated into two distinct climate zones, termed N2 and

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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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Michael Maier-Gerber, Michael Riemer, Andreas H. Fink, Peter Knippertz, Enrico Di Muzio, and Ron McTaggart-Cowan

global and mesoscale ensemble forecasts of tropical cyclogenesis . Wea. Forecasting , 29 , 1181 – 1198 , . 10.1175/WAF-D-14-00028.1 McTaggart-Cowan , R. , G. D. Deane , L. F. Bosart , C. A. Davis , and T. J. Galarneau Jr. , 2008 : Climatology of tropical cyclogenesis in the North Atlantic (1948–2004) . Mon. Wea. Rev. , 136 , 1284 – 1304 , . 10.1175/2007MWR2245.1 McTaggart-Cowan , R. , T. J

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