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

forecasting ( Alley et al. 2019 ). Why is there so little progress in tropical weather forecasting, although many challenges have been realized for decades (e.g., Smith et al. 2001 )? First, initial uncertainties tend to be largest in equatorial regions ( Žagar 2017 ). This is caused by an insufficient observational network, data assimilation algorithms optimized for midlatitude conditions, and large model errors, which also contribute to a fast degradation of forecast quality ( Privé and Errico 2013

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Tobias Selz, Lucas Fischer, and George C. Craig

weather development from 19 to 23 July 2007, a period with an almost stationary low pressure system over Great Britain with southwesterly flow and heavy and strongly forced convection over central Europe. This experiment served as the control experiment for the predictability study of Selz and Craig (2015) , and we refer to this text for further details. For the present investigation, we only use data valid at 1400 UT 20 July 2007 and on a small subdomain (see below). b. Structure function

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

). To our knowledge, this present study is the first to rigorously and systematically assess the quality of ensemble forecasts for precipitation over northern tropical Africa. This is partly related to the fact that for this region ground verification data from rain gauge observations are infrequent on the Global Telecommunication System (GTS), the standard verification data source for NWP centers. Despite many advances in the generation of EPSs, ensembles share structural deficiencies such as

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Thomas Engel, Andreas H. Fink, Peter Knippertz, Gregor Pante, and Jan Bliefernicht

observational rainfall data are often lacking in Africa (e.g., Nicholson et al. 2003 ). The coverage of rain gauges is low (~1 for every 5000 km 2 ) and even shrinking in recent decades; data quality is sometimes questionable because of outdated instrumentation and manual readings. Frequent coding errors lead to erroneous extreme daily rainfall amounts, which do not get eliminated by simple quality controls in widely used datasets such as the NOAA Integrated Surface Database ( https

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

hour compared to DA experiments with only IC uncertainty when using the decorrelation scale, a metric to evaluate the ensemble dispersion (30 km at 5 h lead time, Fig. 4 ). The assimilation of radar data effectively reduces the displacement errors of convective cells at the initial time and outweighs existing synoptic-scale uncertainties. This emphasizes the potential of the direct assimilation of high-quality radar observations using an LETKF data assimilation system in a perfect-model approach

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

Center “Waves to Weather” (TRR 165), project A4: “Evolution and predictability of storm structure during extratropical transition of tropical cyclones.” Observational data were obtained in the framework of T-PARC. We thank the international consortium that supported the T-PARC field campaign and acknowledge the involvement of the U.S. National Science Foundation (NSF)–sponsored National Center for Atmospheric Research (NCAR) Earth Observing Laboratory (EOL) for data management and quality control

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Kirstin Kober and George C. Craig

variances are computed diagnostically by implementing the above equations in the parameterization in the COSMO model by Raschendorfer (2001) . c. Observational data The precipitation forecasts are compared with precipitation fields derived from radar observations. The German radar composite provided by the DWD is computed from quality controlled measurements of radar reflectivities obtained from 16 Doppler radars. The reflectivities are available every 5 min with 1-km horizontal resolution and

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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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Joël Arnault, Thomas Rummler, Florian Baur, Sebastian Lerch, Sven Wagner, Benjamin Fersch, Zhenyu Zhang, Noah Kerandi, Christian Keil, and Harald Kunstmann

.2238 Kumar , A. , F. Chen , M. Barlage , M. B. Ek , and D. Niyogi , 2014 : Assessing impacts of integrating MODIS vegetation data in the Weather Research and Forecasting (WRF) Model coupled to two different canopy-resistance approaches . J. Appl. Meteor. Climatol. , 53 , 1362 – 1380 , . 10.1175/JAMC-D-13-0247.1 Larsen , M. A. D. , J. H. Christensen , M. Drews , M. B. Butts , and J. C. Refsgaard , 2016 : Local control on precipitation in a

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Paolo Ghinassi, Georgios Fragkoulidis, and Volkmar Wirth

expectations can be fulfilled. Acknowledgments We thank the German Weather Service for providing access to the ECMWF data used in this study. We thank the three anonymous reviewers for their comments, which greatly improved the quality of our manuscript. The research leading to these results has been done within the Transregional Collaborative Research Center SFB/TRR 165 “Waves to Weather” funded by the German Science Foundation (DFG). APPENDIX Local Wavenumber through Wavelet Analysis Here we describe our

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