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- ItemSeasonal variability of heterogeneous ice formation in stratiform clouds over the Amazon Basin(Hoboken, NJ : Wiley, 2014) Seifert, Patric; Kunz, Clara; Baars, Holger; Ansmann, Albert; Bühl, Johannes; Senf, Fabian; Engelmann, Ronny; Althausen, Dietrich; Artaxo, PauloBased on 11months of polarization lidar observations in the Amazon Basin near Manaus, Brazil (2.3°S, 60°W), the relationship between temperature and heterogeneous ice formation efficiency in stratiform clouds was evaluated in the cloud top temperature range between -40 and 0°C. Between -30 and 0°C, ice-containing clouds are a factor of 1.5 to 2 more frequent during the dry season. Free-tropospheric aerosol backscatter profiles revealed a twofold to tenfold increase in aerosol load during the dry season and a Monitoring Atmospheric Composition and Climate - Interim Implementation reanalysis data set implies that the aerosol composition during the dry season is strongly influenced by biomass burning aerosol, whereas other components such as mineral dust do not vary strongly between the seasons. The injection of smoke accompanied by the likely dispersion of biological material, soil dust, or ash particles was identified as a possible source for the increased ice formation efficiency during the dry season. Key Points A unique 1year stratiform cloud data set was obtained for the Amazon Basin During the dry season, ice forms more efficient than during the wet season Biomass burning aerosols must be the source of ice nuclei during the dry season.
- ItemLarge-eddy simulations over Germany using ICON: A comprehensive evaluation(Hoboken, NJ : Wiley, 2017) Heinze, Rieke; Dipankar, Anurag; Henken, Cintia Carbajal; Moseley, Christopher; Sourdeval, Odran; Trömel, Silke; Xie, Xinxin; Adamidis, Panos; Ament, Felix; Baars, Holger; Barthlott, Christian; Behrendt, Andreas; Blahak, Ulrich; Bley, Sebastian; Brdar, Slavko; Brueck, Matthias; Crewell, Susanne; Deneke, Hartwig; Di Girolamo, Paolo; Evaristo, Raquel; Fischer, Jürgen; Frank, Christopher; Friederichs, Petra; Göcke, Tobias; Gorges, Ksenia; Hande, Luke; Hanke, Moritz; Hansen, Akio; Hege, Hans-Christian; Hoose, Corinna; Jahns, Thomas; Kalthoff, Norbert; Klocke, Daniel; Kneifel, Stefan; Knippertz, Peter; Kuhn, Alexander; van Laar, Thriza; Macke, Andreas; Maurer, Vera; Mayer, Bernhard; Meyer, Catrin I.; Muppa, Shravan K.; Neggers, Roeland A.J.; Orlandi, Emiliano; Pantillon, Florian; Pospichal, Bernhard; Röber, Niklas; Scheck, Leonhard; Seifert, Axel; Seifert, Patric; Senf, Fabian; Siligam, Pavan; Simmer, Clemens; Steinke, Sandra; Stevens, Bjorn; Wapler, Kathrin; Weniger, Michael; Wulfmeyer, Volker; Zängl, Günther; Zhangl, Dan; Quaase, JohannesLarge-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.