The aim of this work is to introduce a new type of fuzzy system AnYa. This system, unlike the classical fuzzy systems Takagi-Sugeno and Mamdani, uses a type of antecendent based on real data distribution. As part of the work there will be mentioned system programmed and its functionality will be verified on testing data.

In computer vision, it has in recent years become more popular to use point clouds to represent 3D data. To understand what a point cloud contains, methods like semantic segmentation can be used. Semantic segmentation is the problem of segmenting images or point clouds and understanding what the different segments are. An application for semantic segmentation of point clouds are e.g. autonomous driving, where the car needs information about objects in its surrounding. Our approach to the problem, is to project the point clouds into 2D virtual images using the Katz projection. Then we use pre-trained convolutional neural networks to semantically segment the images. To get the semantically segmented point clouds, we project back the scores from the segmentation into the point cloud. Our approach is evaluated on the semantic3D dataset. We find our method is comparable to state-of-the-art, without any fine-tuning on the Semantic3Ddataset.

The scale dependency of variance of total water mixing ratio is explored by analyzing data from a general circulation model (GCM), a numerical weather prediction model (NWP), and large-eddy simulations (LESs). For clarification, direct numerical simulation (DNS) data are additionally included, but the focus is placed on defining a general scaling behavior for scales ranging from global down to cloud resolving. For this, appropriate power-law exponents are determined by calculating and approximating the power density spectrum. The large-scale models (GCM and NWP) show a consistent scaling with a power-law exponent of approximately 22. For the high-resolution LESs, the slope of the power density spectrum shows evidence of being somewhat steeper, although the estimates are more uncertain. Also the transition between resolved and parameterized scales in a current GCM is investigated. Neither a spectral gap nor a strong scale break is found, but a weak scale break at high wavenumbers cannot be excluded. The evaluation of the parameterized total water variance of a state-of-the-art statistical scheme shows that the scale dependency is underestimated by this parameterization. This study and the discovered general scaling behavior emphasize the need for a development of scale-dependent parameterizations.

Observations from Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) and CloudSat satellites are used to evaluate clouds and precipitation in the ECHAM5 general circulation model. Active lidar and radar instruments on board CALIPSO and CloudSat allow the vertical distribution of clouds and their optical properties to be studied on a global scale. To evaluate the clouds modeled by ECHAM5 with CALIPSO and CloudSat, the lidar and radar satellite simulators of the Cloud Feedback Model Intercomparison Project’s Observation Simulator Package are used. Comparison of ECHAM5 with CALIPSO and CloudSat found large-scale features resolved by the model, such as the Hadley circulation, are captured well. The lidar simulator demonstrated ECHAM5 overestimates the amount of high-level clouds, particularly optically thin clouds. High-altitude clouds in ECHAM5 consistently produced greater lidar scattering ratios compared with CALIPSO. Consequently, the lidar signal in ECHAM5 frequently attenuated high in the atmosphere. The large scattering ratios were due to an underestimation of effective ice crystal radii in ECHAM5. Doubling the effective ice crystal radii improved the scattering ratios and frequency of attenuation. Additionally, doubling the effective ice crystal radii improved the detection of ECHAM5’s highest-level clouds by the radar simulator, in better agreement with CloudSat. ECHAM5 was also shown to significantly underestimate midlevel clouds and (sub)tropical low-level clouds. The low-level clouds produced were consistently perceived by the lidar simulator as too optically thick. The radar simulator demonstrated ECHAM5 overestimates the frequency of precipitation, yet underestimates its intensity compared with CloudSat observations. These findings imply compensating mechanisms inECHAM5 balance out the radiative imbalance caused by incorrect optical properties of clouds and consistently large hydrometeors in the atmosphere.

Die vorliegende Arbeit beschreibt die Entwicklung des hochauflösenden Atmosphärenmodells ASAMgpu. Dabei handelt es sich um ein sogenanntes Grobstrukturmodell bei dem gröbere Strukturen mit typischen Skalen von Deka- bis Kilometern in der atmosphärischen Grenzschicht explizit aufgelöst werden. Hochfrequentere Anteile und deren Dissipation müssen dabei entweder explizit mit einem Turbulenzmodell oder, wie im Falle des beschriebenen Modells, implizit behandelt werden. Dazu wurde der Advektionsoperator mit einem dissipativen Upwind-Verfahren dritter Ordnung diskretisiert. Das Modell beinhaltet ein Zwei-Momenten-Schema zur Beschreibung mikrophysikalischer Prozesse. Ein weiterer wichtiger Aspekt ist die verwendete thermodynamische Variable, die einige Vorteile herkömmlicher Ansätze vereint. Im Falle adiabatischer Prozesse stellt sie eine Erhaltungsgröße dar und die Quellen und Senken im Falle von Phasenumwandlungen sind leicht ableitbar. Außerdem können die benötigten Größen Temperatur und Druck explizit berechnet werden. Das gesamte Modell wurde in C++ implementiert und verwendet OpenGL und die OpenGL Shader Language (GLSL) um die nötigen Berechnungen auf Grafikkarten durchzuführen. Durch diesen Ansatz können genannte Simulationen, für die bisher Supercomputer nötig waren, sehr preisgünstig und energieeffizient durchgeführt werden. Neben der Modellbeschreibung werden die Ergebnisse einiger erfolgreicher Test-Simulationen, darunter drei Fälle mit mariner bewölkter Grenzschicht mit flacher Cumulusbewölkung, vorgestellt.

To date, no observation-based proxy for climate change has been successful in quantifying the feedbacks between clouds and climate. The most promising, yet demanding, avenue to gain confi dence in cloud–climate feedback estimates is to utilize observations and large-eddy simulations (LES) or cloud-resolving modeling (CRM) to improve cloud process parameterizations in large-scale models. Sustained and improved satellite observations are essential to evaluate large-scale models. A reanalysis of numerical prediction models with assimilation of cloud, aerosol, and precipitation observations would provide a valuable dataset for examining cloud interactions. The link between climate modeling and numerical weather prediction (NWP) may be exploited by evaluating how accurate cloud characteristics are represented by the parameterization schemes in NWP models. A systematic simplifi cation of large-scale models is an important avenue to isolate key processes linked to cloud–climate feedbacks and would guide the formulation of testable hypotheses for fi eld studies. Analyses of observation-derived correlations between cloud and aerosol properties in combination with modeling studies may allow aerosol–cloud interactions to be detected and quantifi ed. Reliable representations of cloud dynamic and physical processes in large-scale models are a prerequisite to assess aerosol indirect effects on a large scale with confi dence. To include aerosol indirect effects in a consistent manner, we recommend that a “radiative fl ux perturbation” approach be considered as a complement to radiative forcing.

Im Rahmen einer Diplomarbeit an der TU Bergakademie Freiberg wurden in 2014 die Grundlagen für die Auswertung von 3D-Punktwolken zur automatisierten Nachtragung des Risswerks gelegt. Um die dafür notwendigen 3D-Punktwolken möglichst wirtschaftlich zu erstellen, laufen seit 2015 Untersuchungen und Testmessungen zur Machbarkeit des untertägigen Einsatzes von mobil messenden Laserscannern. Im Folgenden werden verschiedene technische Ansätze sowie die Ergebnisse der Testmessungen und die weiteren geplanten Schritte vorgestellt. / As part of a thesis at the Technical University of Freiberg, a basis for the analysis of 3D point clouds was set for refining the mine map automatically. Since 2015 studies and test measurements have been running to create the necessary 3D point clouds as economically as possible, by using an underground mobile scanning system. Below the different technical approaches will be presented as well as the results of the test measurements and the next planned steps.

Within this Ph.D. thesis, the optical thickness and particle effective radius of cirrus and deep convective clouds (DCCs) are retrieved using passive remote sensing techniques. For this purpose, airborne and satellite measurements of spectral solar radiation combined with extensive radiative transfer simulations have been conducted. Data analyzed in this study were collected during the ML-CIRRUS and the ACRIDICON-CHUVA campaigns, which aimed to study natural and contrail cirrus over Europe and DCCs over the Amazon rainforest using the German High Altitude and Long Range Research Aircraft (HALO), respectively. During the campaigns, HALO was equipped with a comprehensive set of remote sensing and in situ instruments. In particular flights, closely collocated measurements with the overpasses of the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard of the Aqua satellite were carried out. A cirrus located above liquid water clouds and a DCC topped by an anvil cirrus are investigated. In general, the research framework can be divided into four parts. In the first part, the spectral upward radiances measured by the Spectral Modular Airborne Radiation Measurement System (SMART)-Albedometer aboard of HALO are compared with those measured by the MODIS. In the second part, a radiance ratio retrieval assuming a vertically homogeneous cloud is applied to obtain the cloud optical thickness and particle effective radius based on the measurements of SMART-Albedometer and MODIS. Multiple near-infrared wavelengths with different absorption characteristics are utilized in the retrieval in order to study the vertical structure of cloud particle sizes. In the third part, the retrieved cloud properties are compared with those derived from the MODIS cloud products. For the cirrus case, the retrieved values of particle effective radius are further compared to in situ data measured by the Cloud Combination Probe (CCP). To allow this comparison, a vertical weighting method is applied. Although the comparison results in a good agreement, retrievals using this conventional technique only provide information on cloud particle sizes from the upper layers, even if spectral measurements have been employed. The retrieved particle effective radius represents a vertically weighted value, where the upper cloud layers are weighted at most. In the fourth part, an extended technique based on Bayesian optimal estimation has been developed to obtain the full vertical profile of particle effective radius. For this purpose, a parameterization assuming the shape of the vertical profile with respect to a vertical coordinate within the cloud is applied. The information content of SMART-Albedometer measurements is analyzed to identify wavelengths that bring the most information pertaining to each retrieval parameter. The new retrieval technique is applied to the cirrus case to infer the profile of particle effective radius as a function of optical thickness. The comparison between the retrieved and the in situ profiles shows a good agreement with a deviation of about 5 % at the cloud top and increases to values of up to 15 % at the cloud base. The new retrieval technique has shown excellent skill in improving the study of the vertical profile of cloud microphysical properties, which can be applied in the future generation of airborne and satellite retrievals based on the measurements of passive remote sensing.:1. Introduction 2. Definitions 3. Measurements 4. Comparison of upward radiance 5. Retrieval of cloud optical thickness and particle effective radius 6. Comparison of cloud optical thickness and particle effective radius 7. Retrieval of the vertical profile of particle effective radius 8. Summary and conclusion

Simulations assuming open-pit mines and different cessation landscapes of open-pit mines with urbanization were performed with a non-hydrostatic meteorological model. The possible enhancement or counteracting of the atmospheric responses to these simultaneously occurring (= accumulated) land-use changes are examined applying a formula drived from the principle of superposition. Although accumulated land-use changes substantially affect the local water and energy fluxes and significantly influence cloud and precipitation microphysics, they do not necessarily provide more significant changes in these quantities than the change of different land-use types to only one land-use type (=single land-use changes). Where the atmospheric responses to accumulated land-use changes are enhanced or inhibited, depends on the thermal, dynamical and hydrologic characteristics of the undergoing accumulated land-use changes as well as on the land-use adjacent to the land-use conversion. In regions dominated by drier surfaces (e.g., agriculture), no enhancement or counteraction according to the principle of superposition could be detected in this study. / Simulationen mit einer Tagebaulandschaft sowie verschiedenen Tagebaufolgelandschaften inklusive Urbanisierung wurden mit einem nicht-hydrostatischen meteorologischen Modell durchgeführt. Eine mögliche Verstärkung oder Abschwächung der atmosphärischen Reaktion auf gleichzeitig auftretende (akkumulierte) Landnutzungsänderungen wird mittels einer auf dem Prinzip der Superposition erstellten Formel untersucht. Obgleich die akkumulierten Landnutzungsänderungen die lokalen Energie- und Wasserflüsse merklich sowie die Wolken und Niederschlagsmikrophysik signifikant beeinflussen, führen sie nicht notwendigerweise zu stärkeren Änderungen dieser Größen als einfache Landnutzungsänderungen. Wo sich akkumulierte Landnutzungsänderungen in ihrer Wirkung auf die Atmosphäre verstärken oder abschwächen, hängt davon ab, wie stark sich die dynamischen, hydrologischen und energetischen Eigenschaften der veränderten Landnutzung von der vorherigen und denen der Umgebung unterscheiden. In Regionen, die durch trockene Flächen charakterisiert sind (z.B. Ackerland), konnte in dieser Studie kein Verstärken oder Abschwächen im Sinne einer Abweichung vom Prinzip der Superposition festgestellt werden.

This thesis evaluates the limitations of passive airborne remote sensing methods to retrieve optical and microphysical properties of Arctic mixed-phase clouds. These limitations are circumvented using a synergy of passive and active remote sensing techniques, and large eddy simulations. Using this synergetic approach, the three-dimensional spatial distribution of the thermodynamic phase of two cloud case studies is characterized. The findings are subsequently applied to a statistical analysis of the cloud properties measured during the Arctic Cloud Observations Using airborne measurements during polar Day (ACLOUD) campaign.