Large-eddy simulations over Germany using ICON: a comprehensive evaluation

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  • 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 parametrizations influencing the surface energy balance, and possibly on ice cloud microphysics. The central purpose for the development and application of ICON in the LES configuration is the use of simulation results to improve the understanding of moist processes, as well as their parametrization in climate models. The evaluation thus aims at building confidence in the model's ability to simulate small- to mesoscale variability in turbulence, clouds and precipitation. The results are encouraging: the high-resolution model matches the observed variability much better at small- to mesoscales 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 time-scales. Despite being somewhat too large and too frequent, small cumulus clouds are well represented in comparison with 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 parametrization development, despite the potential to improve further some important aspects of processes that are also parametrized in the high-resolution model.
Metadaten
Author:Rieke Heinze, Anurag Dipankar, Cintia Carbajal Henken, Christopher Moseley, Odran Sourdeval, Silke Trömel, Xinxin Xie, Panos Adamidis, Felix Ament, Holger Baars, Christian Barthlott, Andreas Behrendt, Ulrich Blahak, Sebastian Bley, Slavko Brdar, Matthias Brueck, Susanne Crewell, Hartwig Deneke, Paolo Di Girolamo, Raquel Evaristo, Jürgen Fischer, Christopher Frank, Petra Friederichs, Tobias Göcke, Ksenia Gorges, Luke Hande, Moritz Hanke, Akio Hansen, Hans-Christian Hege, Corinna Hose, Thomas Jahns, Norbert Kalthoff, Daniel Klocke, Stefan Kneifel, Peter Knippertz, Alexander Kuhn, Thriza van Laar, Andreas Macke, Vera Maurer, Bernhard Mayer, Catrin I. Meyer, Shravan K. Muppa, Roeland A. J. Neggers, Emiliano Orlandi, Florian Pantillon, Bernhard Pospichal, Niklas Röber, Leonhard Scheck, Axel Seifert, Patric Seifert, Fabian Senf, Pavan Siligam, Clemens Simmer, Sandra Steinke, Bjorn Stevens, Kathrin Wapler, Michael Weniger, Volker Wulfmeyer, Günther Zängl, Dan Zhang, Johannes Quaas
Document Type:Article
Parent Title (English):Quarterly Journal of the Royal Meteorological Society
Volume:143
Issue:702
First Page:69
Last Page:100
Year of first publication:2017
DOI:https://doi.org/10.1002/qj.2947