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000829847 020__ $$a978-3-95806-273-3
000829847 037__ $$aFZJ-2017-03469
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000829847 1001_ $$0P:(DE-Juel1)156523$$aCosta, Anja$$b0$$eCorresponding author$$gfemale$$ufzj
000829847 245__ $$aMixed-phase and ice cloud observations with NIXE-CAPS$$f- 2017-05-04
000829847 260__ $$aJülich$$bForschungszentrum Jülich GmbH Zentralbibliothek, Verlag$$c2017
000829847 300__ $$axviii, 117 S.
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000829847 4900_ $$aSchriften des Forschungszentrums Jülich Reihe Energie & Umwelt / Energy & Environment$$v397
000829847 502__ $$aUniversität Wuppertal, Diss., 2017$$bDissertation$$cUniversität Wuppertal$$d2017
000829847 520__ $$aClouds are a main component in the climate system. They influence the energy balance of the atmosphere by changing the earth’s albedo and greenhouse effect, and redistribute energy by releasing and consuming latent heat in cloud particle nucleation and dissolution processes. Climate models therefore react sensitively on the implemented cloud parametrizations, which have to be under constant review to implement new insights into cloud formation and evolutionprocesses. Ice clouds pose a particular challenge for simulations: In mid-level and high clouds, several possible ways for cloud glaciation and ice particle formation compete. These processes produce particles that vary strongly in habits, concentrations and radiative properties. As long as it remains unclear which processes are active, how their influence is distributed globally, how these processes might change due to global warming, and what the properties of the produced ice particles are, ice clouds will remain a significant factor of uncertainty in climate predictions. Over the last years, a number of studies has been performed to examine these questions. The Jülich instrument NIXE-CAPS has contributed a unique ice particle concentration dataset that was used to evaluate global cloud simulations. This thesis presents the extension of the aforesaid dataset into mid-level clouds, where the partitioning of ice and supercooled liquid water becomes increasingly relevant. NIXE-CAPS provides three relevant characteristics of the observed clouds: particle number concentrations, particle size distributions and particle asphericity - especially of small particles with diameters below 50 $\mu$m, which have been rarely analysed so far. The analysis of this data set was extended, evaluated and accelerated in the course of this work: instrument comparisons, error estimations and new corrections complement earlier works with NIXE-CAPS. The improved algorithms allowed a reanalysis of previous measurements and resulted in a consistent data set covering 39 hours of measurements within high clouds (cirrus) and over 38 hours within mid-level clouds. With the NIXE-CAPS measurements, the following tasks were performed: The proportions of liquid, mixed-phase, ’small ice’, and ’large ice’ clouds were resolved for Arctic, mid-latitude and tropical observations. Also, the new model CLaMS-Ice was evaluated and improved with respect to its microphysical accuracy: It provides detailed cirrus cloud simulations over a wide range of meteorological conditions. It can thus be used for large-scale cirrus cloud simulations which is expected to lead to new insights regarding the global cirrus cloud cover’s climatological characteristics.
000829847 536__ $$0G:(DE-HGF)POF3-244$$a244 - Composition and dynamics of the upper troposphere and middle atmosphere (POF3-244)$$cPOF3-244$$fPOF III$$x0
000829847 536__ $$0G:(DE-Juel1)HITEC-20170406$$aHITEC - Helmholtz Interdisciplinary Doctoral Training in Energy and Climate Research (HITEC) (HITEC-20170406)$$cHITEC-20170406$$x1
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