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    Increasing Resolution and Resolving Convection Improve the Simulation of Cloud-Radiative Effects Over the North Atlantic
    (Hoboken, NJ : Wiley, 2020) Senf, Fabian; Voigt, Aiko; Clerbaux, Nicolas; Hünerbein, Anja; Deneke, Hartwig
    Clouds interact with atmospheric radiation and substantially modify the Earth's energy budget. Cloud formation processes occur over a vast range of spatial and temporal scales, which make their thorough numerical representation challenging. Therefore, the impact of parameter choices for simulations of cloud-radiative effects is assessed in the current study. Numerical experiments are carried out using the ICOsahedral Nonhydrostatic (ICON) model with varying grid spacings between 2.5 and 80 km and with different subgrid-scale parameterization approaches. Simulations are performed over the North Atlantic with either one-moment or two-moment microphysics and with convection being parameterized or explicitly resolved by grid-scale dynamics. Simulated cloud-radiative effects are compared to products derived from Meteosat measurements. Furthermore, a sophisticated cloud classification algorithm is applied to understand the differences and dependencies of simulated and observed cloud-radiative effects. The cloud classification algorithm developed for the satellite observations is also applied to the simulation output based on synthetic infrared brightness temperatures, a novel approach that is not impacted by changing insolation and guarantees a consistent and fair comparison. It is found that flux biases originate equally from clear-sky and cloudy parts of the radiation field. Simulated cloud amounts and cloud-radiative effects are dominated by marine, shallow clouds, and their behavior is highly resolution dependent. Bias compensation between shortwave and longwave flux biases, seen in the coarser simulations, is significantly diminished for higher resolutions. Based on the analysis results, it is argued that cloud-microphysical and cloud-radiative properties have to be adjusted to further improve agreement with observed cloud-radiative effects. © 2020. The Authors.
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    Hemispheric and Seasonal Contrast in Cloud Thermodynamic Phase From A‐Train Spaceborne Instruments
    (Hoboken, NJ : Wiley, 2021) Villanueva, Diego; Senf, Fabian; Tegen, Ina
    Aerosol-cloud interactions are an important source of uncertainty in current climate models. To understand and quantify the influence of ice-nucleating particles in cloud glaciation, it is crucial to have a reliable estimation of the hemispheric and seasonal contrast in cloud top phase, which is believed to result from the higher dust aerosol loading in boreal spring. For this reason, we locate and quantify these contrasts by combining three different A-Train cloud-phase products for the period 2007–2010. These products rely on a spaceborne lidar, a lidar-radar synergy, and a radiometer-polarimeter synergy. We show that the cloud-phase from the product combination is more reliable and that the estimation of the hemispheric and seasonal contrast has a lower error compared to the individual products. To quantify the contrast in cloud-phase, we use the hemispheric difference in ice cloud frequency normalized by the liquid cloud frequency in the southern hemisphere between −42 °C and 0 °C. In the midlatitudes, from −15 to −30 °C, the hemispheric contrasts increase with decreasing temperature. At −30 °C, the hemispheric contrast varies from 29% to 39% for the individual cloud-phase products and from 52% to 73% for the product combination. Similarly, in the northern hemisphere, we assess the seasonal contrast between spring and fall normalized by the liquid cloud frequency during fall. At −30 °C, the seasonal contrast ranges from 21% to 39% for the individual cloud-phase products and from 54% to 75% for the product combination.
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    Seasonal 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, Paulo
    Based 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.
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    Large-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, Johannes
    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.