With a nearly twice as strongly pronounced temperature increase compared to that of the Northern Hemisphere, the Arctic is especially susceptible to global climate change. The effect of clouds on the Arctic warming is especially uncertain, which is caused by misrepresented cloud microphysical processes in atmospheric models. This thesis aims at employing a scale- and definition-aware comparison of models and observations and will propose changes how to better parameterize Arctic clouds in atmospheric models. In the first part of this thesis, ECHAM6, which is the atmospheric component of the MPI-ESM global climate model, is compared to spaceborne lidar observations of clouds from the CALIPSO satellite. This comparison shows that ECHAM6 overestimates Arctic low-level, liquid containing clouds over snow- and ice-covered surfaces, which consequently leads to an overestimated amount of radiative energy received by the surface. Using sensitivity studies, it is shown that the probable cause of the model biases in cloud amount and phase is related to misrepresented cloud microphysical parameterization (i.e., parameterization of the Wegener-Bergeron-Findeisen process and of the cloud cover scheme) in ECHAM6. By revising those processes, a better representation of cloud amount and cloud phase is achieved, which helps to more accurately simulated the amount of radiative energy received by the Arctic in ECHAM6. The second part of this thesis will focus on a comparison of kilometer-scale simulation with the ICON model to aircraft observations from the ACLOUD campaign that took place in May/June 2017 over the sea ice-covered Arctic Ocean north of Svalbard, Norway. By comparing measurements of solar and terrestrial surface irradiances during ACLOUD flights to the respective quantities in ICON, it is shown that the model systematically overestimates the transmissivity of the mostly liquid clouds during the campaign. This model bias is traced back to the way cloud condensation nuclei get activated into cloud droplets in the two-moment, bulk microphysical scheme used. By parameterizing subgrid-scale vertical motion as a function of turbulent kinetic energy, a more realistic CCN activation into cloud droplets is achieved. This consequently results in an improved representation of cloud optical properties in the ICON simulations. Furthermore, the results of two studies to which contributions have been made during the Ph.D. will be summarized. In Petersik et al. 2018, the impact of subgrid-scale variability in clear-sky relative humidity on hygroscopic growth of aerosols in the aerosol-climate model ECHAM6-HAM2 has been explored. It was shown that the revised parameterization of hygroscopic growth of aerosols resulted in a stronger swelling of aerosol particles, which consequently causes an increased backscattering of solar radiation. In the study of Costa-Suros et al. 2019, it is explored whether it is possible to detect and attribute aerosol-cloud interactions in large-eddy simulation over Germany. It was shown that an increase in cloud droplet number concentration could be attributed to an increased aerosol load, while such an attribution was not possible for other cloud micro- and macrophysical variables.

From September 17 to October 5, 2012, a field campaign with focus on clouds, aerosols, radiation and dynamics and their interaction in clouds that was coordinated and organized by the Leipzig Institute for Meteorology took place at the Zugspitze mountain. / Vom 17. September bis 5. Oktober wurde vom Leipziger Institut eine Feldkampagne zur Untersuchung der Wechselwirkung von Aerosolen, Niederschlag und Strahlung insbesondere in Hinblick auf konvektive Wolken auf der Zugspitze koordiniert und organisiert.

This work discourses about methods of rendering volumetric data such as clouds or smoke in computer graphics and implementation of this feature to existing application. The first part is summary of techniques and tricks used in computer graphics to display such objects in scene, their pros and cons and the most used techniques of displaying volumetric data. Next part is more closely focused to choosed technique of rendering volumetric data with consideration of light behavior inside the volume (also called participating media) and basic relationships used used in computation. In following part of work there is short list of applications - renderers used to realistic rendering of scene, which are suitable for implementation of selected volumetric data rendering algorithm. Selected application - Blender is describled more deeply including its inner structure, especially rendering engine. Last part of work is dedicated to design, implementation and integration of rendering algorithm itself.

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This essay examines cloud depictions made by the Swedish artist Charlotte Wahlström (1849–1924) during the turn of the twentieth century. The purpose of the essay is to increase the knowledge of the works of a relatively unexplored female artist and discuss how an ecocritical perspective can bring new light to landscape painting during this period of time. The material consists of a selection of six landscape paintings with cloud motifs displayed at the exhibition Kvinnliga pionjärer – Visionära landskap at Prins Eugens Waldemarsudde in Stockholm. The analysis is based on formal aspects from Allan Ellenius’ scheme for image analysis combined with an ecocritical theoretical approach, which puts the cloud paintings in an Anthropocentric context. By painting, Wahlström positions herself to the clouds, which reflects the relation between human and nature. Wahlström’s cloud paintings tend to be seen as subjective mood paintings, on which human feelings are reflected, regardless of the stylistic depiction of the clouds. The result shows that an ecocritical focus enables an image analysis that puts the clouds and the nature in focus, free from human’s projection of her own feelings. Ecocriticism cannot, however, see beyond the fact that a painting is an artefact made by and regarded by humans, and in turn always subjective.

Aerosol particles acting as cloud condensation nuclei (CCN) or ice nucleating parti- cles (INP) play a major role in the formation and glaciation of clouds. Thereby they exert a strong impact on the radiation budget of the Earth. Data on abundance and properties of both particle types are sparse, especially for remote areas of the world, such as the Southern Ocean (SO). In this work, unique results from ship-borne aerosol-particle-related in situ measurements and filter sampling in the summertime SO region are presented. An overview of CCN and INP number concentrations on the Southern Ocean is provided and, using additional analyses on particle chemical composition and air-mass origin, insights regarding possible CCN and INP sources and origins are presented, with the help of a correlation analysis. CCN number concentrations spanned 2 orders of magnitude, e.g. for a supersaturation of 0.3 % values ranged roughly from 3 to 590 cm⁻³. CCN showed variable contributions of organic and inorganic material. No distinct size-dependence of the CCN hygroscopicity parameter was apparent, indicating homogeneous composition across sizes (critical dry diameter on average between 30 nm and 110 nm). The relative contribution of sea spray aerosol (SSA) to the CCN number concentration was on average small (below 35 %). Ambient INP number concentrations were measured in the temperature range from −4 to −27 °C using an immersion freezing method. Concentrations spanned up to 3 orders of magnitude, e.g. at −16 °C from 0.2 to 100 m⁻³. Elevated values (above 10 m⁻³ at −16 °C) were measured when the research vessel was in the vicinity of land (excluding Antarctica). Lower, more constant concentrations were measured on the open ocean. This, along with results of backward-trajectory analyses, hints towards terrestrial and/or coastal INP sources being dominant close to ice-free (non-Antarctic) land. In pristine marine areas INP may originate from both oceanic sources and/or long range transport. A correlation analysis yielded strong correlations between sodium mass concentration and particle number concentration in the coarse mode (larger 1 µm), unsurprisingly indicating a significant contribution of SSA to that mode. CCN number concentration was highly correlated with the number concentrations of Aitken (10 to 100 nm) and accumulation mode particles (100 to 1000 nm). This, together with a lack of correlation between sodium mass and Aitken and accumulation mode number concentrations, underlines the important contribution of non-SSA, probably secondarily formed particles, to the CCN population.:1 Introduction 2 Fundamentals 2.1 Aerosol particle activation 2.1.1 Köhler theory 2.1.2 κ-Köhler theory 2.2 Ice nucleation 2.2.1 Homogeneous Freezing 2.2.2 Heterogeneous Freezing 3 Campaign, instrumentation, and data handling 3.1 Antarctic Circum-navigation Expedition 3.2 In situ aerosol measurements 3.2.1 Aerosol number size distribution 3.2.2 Cloud condensation nuclei 3.3 Off-line aerosol characterisation 3.3.1 High-volume sampling 3.3.2 Low-volume sampling 3.3.3 Ice nucleation droplet array (INDA) 3.3.4 Analysis of chemical composition 3.4 Further resources 3.4.1 In-water organic compound measurements 3.4.2 Wind measurements 3.4.3 Air-mass origin analysis 3.4.4 Fluorescent particles 3.4.5 Correlation analysis 4 Results and Discussion 4.1 Aerosol particles and cloud condensation nuclei 4.1.1 Particle number size distributions 4.1.2 CCN number concentrations 4.1.3 CCN hygroscopicity 4.1.4 Air-mass origin for aerosol particle and CCN measurements 4.2 Ice nucleating particles 4.2.1 INP abundance 4.2.2 Air-mass origin for INP measurements 4.3 Chemical composition of sampled aerosol particles 4.4 Correlation analysis 5 Summary and Conclusions / Aerosolpartikel, die als Wolkennukleations- oder Eiskeime fungieren, spielen eine Schlüsselrolle in den Entstehungs- und Vereisungsprozessen von Wolken. Mit ihren wolkenrelevanten Eigenschaften haben diese beiden Arten von Aerosolpartikeln einen starken Einfluss auf den Strahlungshaushalt der Erde. Messungen ihrer Häufigkeit und Eigenschaften sind selten, inbesondere in den entlegenen Regionen der Erde wie beispielsweise dem Südlichen Ozean. In dieser Arbeit werden die Ergebnisse von in situ und filterbasierten Partikelmessungen einer Forschungsfahrt auf dem Südlichen Ozean in den Sommermonaten der Südhalbkugel gezeigt. Ein erstmaliger Überblick über die Anzahlkonzentrationen der Wolkennukleations- und Eiskeime über dem Südlichen Ozean wird gegeben. Unter Berücksichtigung weiterer Messergebnisse zur chemischen Zusammensetzung der Partikel und Betrachtungen zur Herkunft der Luftmassen werden Rückschlüsse auf die Herkunft und Quellen der gesammelten, wolkenrelevanten Aerosolpartikel gezogen, auch mit Hilfe einer Korrelationsanalyse. Die Anzahlkonzentration der Wolkennukleationskeime schwankte innerhalb von zwei Größenordnungen, beispielsweise zwischen 3 und 590 cm⁻³ bei 0.3 % Übersättigung. Die chemische Zusammensetzung der Wolkennukleationskeime variierte dabei stark, zwischen organischem und inorganischem Material. Der Hygroskopizitätsparameter zeigte keine Größenabhängigkeit, was für eine intern gemischte Population von Wolkennukleationskeimen spricht (kritische Partikeldurchmesser lagen im Mittel zwischen 30 und 110 nm). Der prozentuale Anteil von Seesalzpartikeln zur Anzahlkonzentration der Wolkennukleationskeime war im Mittel gering (kleiner 35 %). Die Anzahlkonzentration der Eiskeime wurden im Temperaturbereich −4 bis −27 °C mittels einer filterbasierten Immersionsgefriermethode bestimmt. Die Anzahlkonzentrationen schwankten dabei im Bereich von bis zu drei Größenordnungen, beispielsweise zwischen 0.2 und 100 m⁻³ bei einer Temperatur von −16 °C. In Küstennähe, mit Ausnahme von Antarktika, wurden erhöhte Anzahlkonzen- trationen (über 10 m⁻³ bei −16 °C) gemessen. Niedrigere, weniger variable Anzahlkonzentrationen wurden hingegen auf offener See gemessen. Diese Beobachtungen, zusammen mit den Ergebnissen zur Luftmassenherkunft, sprechen für eine Dominanz von terrestrischen und/oder küstennahen Quellen der Eiskeime in der Nähe von eisfreiem (nicht-Antarktischem) Festland. Dabei können in den unbe- rührten, marinen Regionen die Eiskeime aus dem Meer selbst und/oder Ferntransport stammen. Eine Korrelationsanalyse zeigte einen starken Zusammenhang zwischen der Massenkonzentration von Natrium und der Anzahlkonzentration an groben Aerosolpartikeln (größer 1 µm). Daraus folgt ein signifikanter Anteil an Seesalzpartikeln in dieser Partikelgröße. Die Anzahlkonzentration der Wolkennukleationskeime korrelierte stark mit den Anzahlkonzentrationen der Aitken- (10 bis 100 nm) bzw. Akkumulationskerne (100 bis 1000 nm). Diese Beobachtung, zusammen mit dem Fehlen einer Korrelation zwischen Natriummasse und Aitken- oder Akkumulationskernanzahl, unterstreicht die Relevanz von Partikeln die nicht Seesalz sind (vermutlich sekundär geformten Aerosolpartikel) für die Population der Wolkennukleationskeime.:1 Introduction 2 Fundamentals 2.1 Aerosol particle activation 2.1.1 Köhler theory 2.1.2 κ-Köhler theory 2.2 Ice nucleation 2.2.1 Homogeneous Freezing 2.2.2 Heterogeneous Freezing 3 Campaign, instrumentation, and data handling 3.1 Antarctic Circum-navigation Expedition 3.2 In situ aerosol measurements 3.2.1 Aerosol number size distribution 3.2.2 Cloud condensation nuclei 3.3 Off-line aerosol characterisation 3.3.1 High-volume sampling 3.3.2 Low-volume sampling 3.3.3 Ice nucleation droplet array (INDA) 3.3.4 Analysis of chemical composition 3.4 Further resources 3.4.1 In-water organic compound measurements 3.4.2 Wind measurements 3.4.3 Air-mass origin analysis 3.4.4 Fluorescent particles 3.4.5 Correlation analysis 4 Results and Discussion 4.1 Aerosol particles and cloud condensation nuclei 4.1.1 Particle number size distributions 4.1.2 CCN number concentrations 4.1.3 CCN hygroscopicity 4.1.4 Air-mass origin for aerosol particle and CCN measurements 4.2 Ice nucleating particles 4.2.1 INP abundance 4.2.2 Air-mass origin for INP measurements 4.3 Chemical composition of sampled aerosol particles 4.4 Correlation analysis 5 Summary and Conclusions

The Swedish Armed Forces setup of the Weather Research and Forecasting Model (WRF) has problems to forecast low clouds in stably stratified conditions when the ground is covered by snow. The aim of this thesis is to understand what causes this deficit. Simulations during January and February 2018 are here compared with observations from Sodankylä in northern Finland. It is revealed that neither type of planetary boundary layer parameterization chosen nor vertical or horizontal interpolation are responsible for the deficiency. Instead, our experiments show that, to first order, poor initialization of Stratocumulus (Sc) clouds from the host model, Atmospheric Model High Resolution (HRES), of the Integrated Forecast System (IFS) is the missing link. In situations when Sc clouds are missing in the IFS analysis, although they exist in reality, we use information from vertical soundings from Sodankylä. In the initialization process we used the fact that liquid potential temperature is constant in a well-mixed cloud. Initializing cloud water and cloud ice from IFS HRES and from soundings with different methods improves the model performance and the formation of very low artificial clouds at the first model level is prohibited.

Discrimination of different tree crowns based on their 3D shapes is essential for a wide range of forestry applications, and, due to its complexity, is a significant challenge. This study presents a modified 3D shape descriptor for the perception of different tree crown shapes in discrete-return LiDAR point clouds. The proposed methodology comprises of five main components, including definition of a local coordinate system, learning salient points, generation of simulated LiDAR point clouds with geometrical shapes, shape signature generation (from simulated LiDAR points as reference shape signature and actual LiDAR point clouds as evaluated shape signature), and finally, similarity assessment of shape signatures in order to extract the shape of a real tree. The first component represents a proposed strategy to define a local coordinate system relating to each tree to normalize 3D point clouds. In the second component, a learning approach is used to categorize all 3D point clouds into two ranks to identify interesting or salient points on each tree. The third component discusses generation of simulated LiDAR point clouds for two geometrical shapes, including a hemisphere and a half-ellipsoid. Then, the operator extracts 3D LiDAR point clouds of actual trees, either deciduous or evergreen. In the fourth component, a longitude-latitude transformation is applied to simulated and actual LiDAR point clouds to generate 3D shape signatures of tree crowns. A critical step is transformation of LiDAR points from their exact positions to their longitude and latitude positions using the longitude-latitude transformation, which is different from the geographic longitude and latitude coordinates, and labeled by their pre-assigned ranks. Then, natural neighbor interpolation converts the point maps to raster datasets. The generated shape signatures from simulated and actual LiDAR points are called reference and evaluated shape signatures, respectively. Lastly, the fifth component determines the similarity between evaluated and reference shape signatures to extract the shape of each examined tree. The entire process is automated by ArcGIS toolboxes through Python programming for further evaluation using more tree crowns in different study areas. Results from LiDAR points captured for 43 trees in the City of Surrey, British Columbia (Canada) suggest that the modified shape descriptor is a promising method for separating different shapes of tree crowns using LiDAR point cloud data. Experimental results also indicate that the modified longitude-latitude shape descriptor fulfills all desired properties of a suitable shape descriptor proposed in computer science along with leaf-off, leaf-on invariance, which makes this process autonomous from the acquisition date of LiDAR data. In summary, the modified longitude-latitude shape descriptor is a promising method for discriminating different shapes of tree crowns using LiDAR point cloud data.

<p>The formation of star clusters occurs in a complex environment and involve a large number of physical processes. One of the most important processes to consider is radiative feedback. The radiation released by forming stars heats the surrounding gas and suppresses the fragmentation of low mass objects. Ionizing radiation can also drive large scale outflows and disperse the surrounding gas. Owing to all this complexity, the use of numerical simulations to study cluster formation in molecular clouds has become commonplace. In order to study the effects of radiative feedback on cluster formation over larger spatial scales than previous studies, we present hydrodynamical simulations using the AMR code FLASH which make use of cluster particles. Unlike previous studies, these particles represent an entire star cluster rather than individual stars. We present a subgrid model for representing the radiative output of a star cluster which involves randomly sampling an IMF over time to populate the cluster. We show that our model is capable of reproducing the properties of observed clusters. The model was then incorporated into FLASH to examine the effects of radiative feedback on cluster formation in full hydrodynamical simulations. We find that the inclusion of radiative transfer can drive large scale outflows and decreases the overall star formation efficiency by a factor of 2. The inclusion of radiative feedback also increases the degree of subclustering. The use of cluster particles in hydrodynamical simulations represents a promising method for future studies of cluster formation and the large scale effects of radiative feedback.</p> / Master of Science (MSc)