Küchler, Nils ORCID: 0000-0001-6950-0036 (2019). Ground-based remote sensing of warm low-level stratified clouds - new perspectives and applications. PhD thesis, Universität zu Köln.

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Climate change and an increasing global population increase the pressure on the global community, in particular the Global North, to initiate drastic changes in mindset, lifestyle and resource management to sustain a habitable environment, to minimize natural hazards, and thereby, to protect those who are most vulnerable and least responsible for the current condition of our planet. Among others, the shift from fossil to renewable energy sources (renewables) plays a key role in transforming a high-carbon society into a zero-carbon one. The integration of renewables into existing energy systems or even the design of an energy system consisting of renewables only are still challenging tasks that require interdisciplinary research. Such research is conducted by the University of Cologne hosting the project Energy Transitions and Climate Change to support both specific and interdisciplinary research for investigating open questions and creating new ones related to renewable energies and climate change. Here, results of an interdisciplinary study are discussed investigating the uncertainty of predicted energy systems in Germany based on the analysis of Reanalysis data. Among others, this uncertainty depends on the accuracy of estimated solar energy from photovoltaic panels and is most sensitive to changes in direct solar radiation. Hence, to assesses the uncertainty of predicted energy systems based on reanalysis data, the accuracy of the latter itself, especially estimated solar radiation, must be characterized well. Uncertainties in direct solar radiation in reanalysis data depend to high extent on the prediction of clouds, especially those clouds that are abundant and have a high albedo at visible wavelengths such as stratocumulus clouds (Sc). Thus, understanding their formation and evolution constitutes an important topic for renewable energy applications. To evaluate models and parameterizations implemented into reanalysis, accurate observations of Sc are necessary, which is the main topic of this work: how accurately can we retrieve the liquid water content (LWC) of warm low-level stratified clouds, in particular Sc, using ground-based remote sensing? The three key publications of this cumulative thesis try to answer this question from different perspectives: Publication I evaluates the performance of a new W-band radar-radiometer (JOYRAD-94) that can be used to derive physical properties of clouds. It is shown, by comparing JOYRAD-94 to a co-located radar, that it is capable of measuring radar reflectivity at 94 GHz with an accuracy of about 0.5 dB. The comparison also revealed a new method to dealiase radar Doppler spectra using two co-located radars enabling cloud observations with both high vertical resolution and large unambiguous Doppler velocity. Additionally, JOYRAD-94 is equipped with a passive microwave radiometer (MWR) channel at 89 GHz enabling the retrieval of the liquid water path with an uncertainty of about 15 g/m² when the integrated water vapor is known with an accuracy of 2 kg/m² from an external source. Optimal beam matching between the radar and the radiometer of JOYRAD-94 is accomplished by receiving the active and passive signals over the same antenna. This is a novelty in ground-based remote sensing. The advantage of optimally matched beams for cloud remote sensing is discussed in Publication II that investigates how the accuracy of a commonly used LWC retrieval (henceforth StandFrisch), combining radar and MWR, changes when the instruments are displaced to each other, i.e. observe different cloud scenes. It is found that displacing the instruments by 10 m increases the relative retrieval uncertainty of retrieved LWC by 10 % in the entire profile. At 100 m displacement, the relative error reaches 30 %. Moreover, it is shown that studying LWC at cloud edges requires optimally matched beams, i.e. a displacement by 10 m does already yield unreasonable results. Publication III assess the accuracy of StandFrisch for various compositions of Sc. StandFrisch is capable of retrieving LWC in non-drizzling Sc. However, once drizzle is present, StandFrisch does not obtain reasonable estimates of LWC. Publication III provides a modification of StandFrisch, the ModFrisch, that allows retrieving LWC in both drizzling and non-drizzling Sc with an accuracy of 20 %. The findings of the three publications increase the accuracy of a commonly used LWC retrieval technique for warm low-level stratified clouds and characterize the retrieval's uncertainties. Therefore this thesis makes an important contribution to better understand micro-physical processes in Sc, which drive cloud formation and evolution. Moreover, more accurate LWC profiles can help to improve the evaluation of models and their parameterizations, which are, for example, implemented in reanalysis data. Well characterized models and their data are inevitable for various applications such as weather and climate predictions, as well as estimating future energy systems.

Item Type: Thesis (PhD thesis)
CreatorsEmailORCIDORCID Put Code
Küchler, Nilsnilskuechler@web.deorcid.org/0000-0001-6950-0036UNSPECIFIED
URN: urn:nbn:de:hbz:38-94374
Date: 18 March 2019
Language: English
Faculty: Faculty of Mathematics and Natural Sciences
Divisions: Faculty of Mathematics and Natural Sciences > Department of Geosciences > Institute for Geophysics and Meteorology
Subjects: Natural sciences and mathematics
Earth sciences
Uncontrolled Keywords:
Cloud liquid waterEnglish
remote senisingEnglish
radar radiometerEnglish
Date of oral exam: 28 October 2018
NameAcademic Title
Löhnert, UlrichPD Dr.
Refereed: Yes
URI: http://kups.ub.uni-koeln.de/id/eprint/9437


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