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024 7 _ |a 10.1002/qj.2947
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024 7 _ |a 0035-9009
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024 7 _ |a 1477-870X
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024 7 _ |a 2128/13887
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100 1 _ |a Heinze, Rieke
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245 _ _ |a Large-eddy simulations over Germany using ICON: A comprehensive evaluation
260 _ _ |a Weinheim [u.a.]
|c 2017
|b Wiley
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520 _ _ |a Large-eddy simulations (LES) with the new ICOsahedral Non-hydrostatic atmosphere model (ICON) covering Germany are evaluated for four days in spring 2013 using observational data from various sources. Reference simulations with the established Consortium for Small-scale Modelling (COSMO) numerical weather prediction model and further standard LES codes are performed and used as a reference. This comprehensive evaluation approach covers multiple parameters and scales focusing on boundary layer variables, clouds and precipitation. The evaluation points to the need to work on parameterisations influencing the surface energy balance, and possibly on ice cloud microphysics. The central purpose for the development and application of ICON in LES configuration is the use of simulation results to improve the understanding of moist processes, as well as their parameterisation in climate models. The evaluation thus aims at building confidence in the model's ability to simulate small- to meso-scale variability in turbulence, clouds, and precipitation. The results are encouraging: the high-resolution model much better matches the observed variability at small- to meso-scales than the coarser-resolved reference model. In its highest grid resolution, the simulated turbulence profiles are realistic, and column water vapour matches the observed temporal variability at short timescales. Despite being somewhat too large and too frequent, small cumulus clouds are well represented in comparison to satellite data, as is the shape of the cloud size spectrum. Variability of cloud water matches the satellite observations much better in ICON than in the reference model. In this sense, it is concluded that the model is fit for the purpose of using its output for parameterisation development, despite the potential to further improve important aspects of processes that are parameterised also in the high-resolution model.
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700 1 _ |a Brueck, Matthias
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700 1 _ |a Crewell, Susanne
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700 1 _ |a Deneke, Hartwig
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700 1 _ |a Di Girolamo, Paolo
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700 1 _ |a Evaristo, Raquel
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700 1 _ |a Fischer, Jürgen
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700 1 _ |a Frank, Christopher
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700 1 _ |a Friederichs, Petra
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700 1 _ |a Göcke, Tobias
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700 1 _ |a Hande, Luke
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700 1 _ |a Hanke, Moritz
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700 1 _ |a Hansen, Akio
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700 1 _ |a Hege, Hans-Christian
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700 1 _ |a Macke, Andreas
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700 1 _ |a Maurer, Vera
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700 1 _ |a Mayer, Bernhard
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700 1 _ |a Meyer, Catrin
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700 1 _ |a Muppa, Shravan K.
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700 1 _ |a Neggers, Roeland A. J.
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700 1 _ |a Orlandi, Emiliano
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700 1 _ |a Pantillon, Florian
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700 1 _ |a Pospichal, Bernhard
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700 1 _ |a Röber, Niklas
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700 1 _ |a Scheck, Leonhard
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700 1 _ |a Seifert, Axel
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700 1 _ |a Seifert, Patric
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700 1 _ |a Senf, Fabian
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700 1 _ |a Siligam, Pavan
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700 1 _ |a Simmer, Clemens
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700 1 _ |a Steinke, Sandra
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700 1 _ |a Stevens, Bjorn
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700 1 _ |a Wapler, Kathrin
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700 1 _ |a Weniger, Michael
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700 1 _ |a Wulfmeyer, Volker
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700 1 _ |a Zängl, Günther
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700 1 _ |a Zhang, Dan
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700 1 _ |a Quaas, Johannes
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773 _ _ |a 10.1002/qj.2947
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