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Institute
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Observational evidence exists that winds of massive stars are clumped. Many massive star systems are known as non-thermal particle production sites, as indicated by their synchrotron emission in the radio band. As a consequence they are also considered as candidate sites for non-thermal high-energy photon production up to gamma-ray energies. The present work considers the effects of wind clumpiness expected on the emitting relativistic particle spectrum in colliding wind systems, built up from the pool of thermal wind particles through diffusive particle acceleration, and taking into account inverse Compton and synchrotron losses. In comparison to a homogeneous wind, a clumpy wind causes flux variations of the emitting particle spectrum when the clump enters the wind collision region. It is found that the spectral features associated with this variability moves temporally from low to high energy bands with the time shift between any two spectral bands being dependent on clump size, filling factor, and the energy-dependence of particle energy gains and losses.
Clumping in Galactic WN stars : a comparison of mass loss rates from UV/optical & radio diagnostics
(2007)
The mass loss rates and other parameters for a large sample of Galactic WN stars have been revised by Hamann et al. (2006), using the most up-to date Potsdam Wolf-Rayet (PoWR) model atmospheres. For a sub-sample of these stars exist measurements of their radio free-free emission. After harmonizing the adopted distance and terminal wind velocities, we compare the mass loss rates obtained from the two diagnostics. The differences are discussed as a possible consequence of different clumping contrast in the line-forming and radio-emitting regions.
Stellar winds play an important role for the evolution of massive stars and their cosmic environment. Multiple lines of evidence, coming from spectroscopy, polarimetry, variability, stellar ejecta, and hydrodynamic modeling, suggest that stellar winds are non-stationary and inhomogeneous. This is referred to as 'wind clumping'. The urgent need to understand this phenomenon is boosted by its far-reaching implications. Most importantly, all techniques to derive empirical mass-loss rates are more or less corrupted by wind clumping. Consequently, mass-loss rates are extremely uncertain. Within their range of uncertainty, completely different scenarios for the evolution of massive stars are obtained. Settling these questions for Galactic OB, LBV and Wolf-Rayet stars is prerequisite to understanding stellar clusters and galaxies, or predicting the properties of first-generation stars. In order to develop a consistent picture and understanding of clumped stellar winds, an international workshop on 'Clumping in Hot Star Winds' was held in Potsdam, Germany, from 18. - 22. June 2007. About 60 participants, comprising almost all leading experts in the field, gathered for one week of extensive exchange and discussion. The Scientific Organizing Committee (SOC) included John Brown (Glasgow), Joseph Cassinelli (Madison), Paul Crowther (Sheffield), Alex Fullerton (Baltimore), Wolf-Rainer Hamann (Potsdam, chair), Anthony Moffat (Montreal), Stan Owocki (Newark), and Joachim Puls (Munich). These proceedings contain the invited and contributed talks presented at the workshop, and document the extensive discussions.
Clumping in O-star winds
(2007)
We have analyzed the spectra of seven Galactic O4 supergiants, with the NLTE wind code CMFGEN. For all stars, we have found that clumped wind models match well lines from different species spanning a wavelength range from FUV to optical, and remain consistent with Hα data. We have achieved an excellent match of the P V λλ1118, 1128 resonance doublet and N IV λ1718, as well as He II λ4686 suggesting that our physical description of clumping is adequate. We find very small volume filling factors and that clumping starts deep in the wind, near the sonic point. The most crucial consequence of our analysis is that the mass loss rates of O stars need to be revised downward significantly, by a factor of 3 and more compared to those obtained from smooth-wind models.
Recent studies of massive O-type stars present clear evidences of inhomogeneous and clumped winds. O-type (H-rich) central stars of planetary nebulae (CSPNs) are in some ways the low mass–low luminosity analogous of those massive stars. In this contribution, we present preliminary results of our on-going multi-wavelength (FUV, UV and optical) study of the winds of Galactic CSPNs. Particular emphasis will be given to the clumping factors derived by means of optical lines (Hα and Heii 4686) and “classic” FUV (and UV) lines.
The Arctic is a particularly sensitive area with respect to climate change due to the high surface albedo of snow and ice and the extreme radiative conditions. Clouds and aerosols as parts of the Arctic atmosphere play an important role in the radiation budget, which is, as yet, poorly quantified and understood. The LIDAR (Light Detection And Ranging) measurements presented in this PhD thesis contribute with continuous altitude resolved aerosol profiles to the understanding of occurrence and characteristics of aerosol layers above Ny-Ålesund, Spitsbergen. The attention was turned to the analysis of periods with high aerosol load. As the Arctic spring troposphere exhibits maximum aerosol optical depths (AODs) each year, March and April of both the years 2007 and 2009 were analyzed. Furthermore, stratospheric aerosol layers of volcanic origin were analyzed for several months, subsequently to the eruptions of the Kasatochi and Sarychev volcanoes in summer 2008 and 2009, respectively. The Koldewey Aerosol Raman LIDAR (KARL) is an instrument for the active remote sensing of atmospheric parameters using pulsed laser radiation. It is operated at the AWIPEV research base and was fundamentally upgraded within the framework of this PhD project. It is now equipped with a new telescope mirror and new detection optics, which facilitate atmospheric profiling from 450m above sea level up to the mid-stratosphere. KARL provides highly resolved profiles of the scattering characteristics of aerosol and cloud particles (backscattering, extinction and depolarization) as well as water vapor profiles within the lower troposphere. Combination of KARL data with data from other instruments on site, namely radiosondes, sun photometer, Micro Pulse LIDAR, and tethersonde system, resulted in a comprehensive data set of scattering phenomena in the Arctic atmosphere. The two spring periods March and April 2007 and 2009 were at first analyzed based on meteorological parameters, like local temperature and relative humidity profiles as well as large scale pressure patterns and air mass origin regions. Here, it was not possible to find a clear correlation between enhanced AOD and air mass origin. However, in a comparison of two cloud free periods in March 2007 and April 2009, large AOD values in 2009 coincided with air mass transport through the central Arctic. This suggests the occurrence of aerosol transformation processes during the aerosol transport to Ny-Ålesund. Measurements on 4 April 2009 revealed maximum AOD values of up to 0.12 and aerosol size distributions changing with altitude. This and other performed case studies suggest the differentiation between three aerosol event types and their origin: Vertically limited aerosol layers in dry air, highly variable hygroscopic boundary layer aerosols and enhanced aerosol load across wide portions of the troposphere. For the spring period 2007, the available KARL data were statistically analyzed using a characterization scheme, which is based on optical characteristics of the scattering particles. The scheme was validated using several case studies. Volcanic eruptions in the northern hemisphere in August 2008 and June 2009 arose the opportunity to analyze volcanic aerosol layers within the stratosphere. The rate of stratospheric AOD change was similar within both years with maximum values above 0.1 about three to five weeks after the respective eruption. In both years, the stratospheric AOD persisted at higher rates than usual until the measurements were stopped in late September due to technical reasons. In 2008, up to three aerosol layers were detected, the layer structure in 2009 was characterized by up to six distinct and thin layers which smeared out to one broad layer after about two months. The lowermost aerosol layer was continuously detected at the tropopause altitude. Three case studies were performed, all revealed rather large indices of refraction of m = (1.53–1.55) - 0.02i, suggesting the presence of an absorbing carbonaceous component. The particle radius, derived with inversion calculations, was also similar in both years with values ranging from 0.16 to 0.19 μm. However, in 2009, a second mode in the size distribution was detected at about 0.5 μm. The long term measurements with the Koldewey Aerosol Raman LIDAR in Ny-Ålesund provide the opportunity to study Arctic aerosols in the troposphere and the stratosphere not only in case studies but on longer time scales. In this PhD thesis, both, tropospheric aerosols in the Arctic spring and stratospheric aerosols following volcanic eruptions have been described qualitatively and quantitatively. Case studies and comparative studies with data of other instruments on site allowed for the analysis of microphysical aerosol characteristics and their temporal evolution.
Complex network theory provides an elegant and powerful framework to statistically investigate the topology of local and long range dynamical interrelationships, i.e., teleconnections, in the climate system. Employing a refined methodology relying on linear and nonlinear measures of time series analysis, the intricate correlation structure within a multivariate climatological data set is cast into network form. Within this graph theoretical framework, vertices are identified with grid points taken from the data set representing a region on the the Earth's surface, and edges correspond to strong statistical interrelationships between the dynamics on pairs of grid points. The resulting climate networks are neither perfectly regular nor completely random, but display the intriguing and nontrivial characteristics of complexity commonly found in real world networks such as the internet, citation and acquaintance networks, food webs and cortical networks in the mammalian brain. Among other interesting properties, climate networks exhibit the "small-world" effect and possess a broad degree distribution with dominating super-nodes as well as a pronounced community structure. We have performed an extensive and detailed graph theoretical analysis of climate networks on the global topological scale focussing on the flow and centrality measure betweenness which is locally defined at each vertex, but includes global topological information by relying on the distribution of shortest paths between all pairs of vertices in the network. The betweenness centrality field reveals a rich internal structure in complex climate networks constructed from reanalysis and atmosphere-ocean coupled general circulation model (AOGCM) surface air temperature data. Our novel approach uncovers an elaborately woven meta-network of highly localized channels of strong dynamical information flow, that we relate to global surface ocean currents and dub the backbone of the climate network in analogy to the homonymous data highways of the internet. This finding points to a major role of the oceanic surface circulation in coupling and stabilizing the global temperature field in the long term mean (140 years for the model run and 60 years for reanalysis data). Carefully comparing the backbone structures detected in climate networks constructed using linear Pearson correlation and nonlinear mutual information, we argue that the high sensitivity of betweenness with respect to small changes in network structure may allow to detect the footprints of strongly nonlinear physical interactions in the climate system. The results presented in this thesis are thoroughly founded and substantiated using a hierarchy of statistical significance tests on the level of time series and networks, i.e., by tests based on time series surrogates as well as network surrogates. This is particularly relevant when working with real world data. Specifically, we developed new types of network surrogates to include the additional constraints imposed by the spatial embedding of vertices in a climate network. Our methodology is of potential interest for a broad audience within the physics community and various applied fields, because it is universal in the sense of being valid for any spatially extended dynamical system. It can help to understand the localized flow of dynamical information in any such system by combining multivariate time series analysis, a complex network approach and the information flow measure betweenness centrality. Possible fields of application include fluid dynamics (turbulence), plasma physics and biological physics (population models, neural networks, cell models). Furthermore, the climate network approach is equally relevant for experimental data as well as model simulations and hence introduces a novel perspective on model evaluation and data driven model building. Our work is timely in the context of the current debate on climate change within the scientific community, since it allows to assess from a new perspective the regional vulnerability and stability of the climate system while relying on global and not only on regional knowledge. The methodology developed in this thesis hence has the potential to substantially contribute to the understanding of the local effect of extreme events and tipping points in the earth system within a holistic global framework.
We shall examine the Pedagogical Content Knowledge (PCK) of Computer Science (CS) teachers concerning students’ Computational Thinking (CT) problem solving skills within the context of a CS course in Dutch secondary education and thus obtain an operational definition of CT and ascertain appropriate teaching methodology. Next we shall develop an instrument to assess students’ CT and design a curriculum intervention geared toward teaching and improving students’ CT problem solving skills and competences. As a result, this research will yield an operational definition of CT, knowledge about CT PCK, a CT assessment instrument and teaching materials and accompanying teacher instructions. It shall contribute to CS teacher education, development of CT education and to education in other (STEM) subjects where CT plays a supporting role, both nationally and internationally.
Abstract interpretation-based model checking provides an approach to verifying properties of infinite-state systems. In practice, most previous work on abstract model checking is either restricted to verifying universal properties, or develops special techniques for temporal logics such as modal transition systems or other dual transition systems. By contrast we apply completely standard techniques for constructing abstract interpretations to the abstraction of a CTL semantic function, without restricting the kind of properties that can be verified. Furthermore we show that this leads directly to implementation of abstract model checking algorithms for abstract domains based on constraints, making use of an SMT solver.
We present the latest results on the observational dependence of the mass-loss rate in stellar winds of O and early-B stars on the metal content of their atmospheres, and compare these with predictions. Absolute empirical rates for the mass loss of stars brighter than 10$^{5.2} L_{\odot}$, based on H$\alpha$ and ultraviolet (UV) wind lines, are found to be about a factor of two higher than predictions. If this difference is attributed to inhomogeneities in the wind this would imply that luminous O and early-B stars have clumping factors in their H$\alpha$ and UV line forming regime of about a factor of 3--5. The investigated stars cover a metallicity range $Z$ from 0.2 to 1 $Z_{\odot}$. We find a hint towards smaller clumping factors for lower $Z$. The derived clumping factors, however, presuppose that clumping does not impact the predictions of the mass-loss rate. We discuss this assumption and explain how we intend to investigate its validity in more detail.
Localisation of deformation is a ubiquitous feature in continental rift dynamics and observed across drastically different time and length scales. This thesis comprises one experimental and two numerical modelling studies investigating strain localisation in (1) a ductile shear zone induced by a material heterogeneity and (2) in an active continental rift setting. The studies are related by the fact that the weakening mechanisms on the crystallographic and grain size scale enable bulk rock weakening, which fundamentally enables the formation of shear zones, continental rifts and hence plate tectonics. Aiming to investigate the controlling mechanisms on initiation and evolution of a shear zone, the torsion experiments of the experimental study were conducted in a Patterson type apparatus with strong Carrara marble cylinders with a weak, planar Solnhofen limestone inclusion. Using state-of-the-art numerical modelling software, the torsion experiments were simulated to answer questions regarding localisation procedure like stress distribution or the impact of rheological weakening. 2D numerical models were also employed to integrate geophysical and geological data to explain characteristic tectonic evolution of the Southern and Central Kenya Rift. Key elements of the numerical tools are a randomized initial strain distribution and the usage of strain softening. During the torsion experiments, deformation begins to localise at the limestone inclusion tips in a process zone, which propagates into the marble matrix with increasing deformation until a ductile shear zone is established. Minor indicators for coexisting brittle deformation are found close to the inclusion tip and presumed to slightly facilitate strain localisation besides the dominant ductile deformation processes. The 2D numerical model of the torsion experiment successfully predicts local stress concentration and strain rate amplification ahead of the inclusion in first order agreement with the experimental results. A simple linear parametrization of strain weaking enables high accuracy reproduction of phenomenological aspects of the observed weakening. The torsion experiments suggest that loading conditions do not affect strain localisation during high temperature deformation of multiphase material with high viscosity contrasts. A numerical simulation can provide a way of analysing the process zone evolution virtually and extend the examinable frame. Furthermore, the nested structure and anastomosing shape of an ultramylonite band was mimicked with an additional second softening step. Rheological weakening is necessary to establish a shear zone in a strong matrix around a weak inclusion and for ultramylonite formation.
Such strain weakening laws are also incorporated into the numerical models of the
Southern and Central Kenya Rift that capture the characteristic tectonic evolution. A three-stage early rift evolution is suggested that starts with (1) the accommodation of strain by a single border fault and flexure of the hanging-wall crust, after which (2) faulting in the hanging-wall and the basin centre increases before (3) the early-stage asymmetry is lost and basinward localisation of deformation occurs. Along-strike variability of rifts can be produced by modifying the initial random noise distribution. In summary, the three studies address selected aspects of the broad range of mechanisms and processes that fundamentally enable the deformation of rock and govern the localisation patterns across the scales. In addition to the aforementioned results, the first and second manuscripts combined, demonstrate a procedure to find new or improve on existing numerical formulations for specific rheologies and their dynamic weakening. These formulations are essential in addressing rock deformation from the grain to the global scale. As within the third study of this thesis, where geodynamic controls on the evolution of a rift were examined and acquired by the integration of geological and geophysical data into a numerical model.
An account is presented of the focus properties, common ground effect and dialogue behaviour of the accented German discourse marker "doch" and the accented sentence negation "nicht". It is argued that "doch" and "nicht" evoke as a focus alternative the logical complement of the proposition expressed by the sentence in which they occur, and that an analysis in terms of contrastive focus accounts for their effect on the common ground and their function in dialogue.
Data dependencies, or integrity constraints, are used to improve the quality of a database schema, to optimize queries, and to ensure consistency in a database. In the last years conditional dependencies have been introduced to analyze and improve data quality. In short, a conditional dependency is a dependency with a limited scope defined by conditions over one or more attributes. Only the matching part of the instance must adhere to the dependency. In this paper we focus on conditional inclusion dependencies (CINDs). We generalize the definition of CINDs, distinguishing covering and completeness conditions. We present a new use case for such CINDs showing their value for solving complex data quality tasks. Further, we define quality measures for conditions inspired by precision and recall. We propose efficient algorithms that identify covering and completeness conditions conforming to given quality thresholds. Our algorithms choose not only the condition values but also the condition attributes automatically. Finally, we show that our approach efficiently provides meaningful and helpful results for our use case.
We investigate how the economic consequences of the pandemic, and of the government-mandated measures to contain its spread, affect the self-employed – particularly women – in Germany. For our analysis, we use representative, real-time survey data in which respondents were asked about their situation during the COVID-19 pandemic. Our findings indicate that among the self-employed, who generally face a higher likelihood of income losses due to COVID-19 than employees, women are 35% more likely to experience income losses than their male counterparts. Conversely, we do not find a comparable gender gap among employees. Our results further suggest that the gender gap among the self-employed is largely explained by the fact that women disproportionately work in industries that are more severely affected by the COVID-19 pandemic. Our analysis of potential mechanisms reveals that women are significantly more likely to be impacted by government-imposed restrictions, i.e. the regulation of opening hours. We conclude that future policy measures intending to mitigate the consequences of such shocks should account for this considerable variation in economic hardship.
A new method is used in an eye-tracking pilot experiment which shows that it is possible to detect differences in common ground associated with the use of minimally different types of indefinite anaphora. Following Richardson and Dale (2005), cross recurrence quantification analysis (CRQA) was used to show that the tandem eye movements of two Swedish-speaking interlocutors are slightly more coupled when they are using fully anaphoric indefinite expressions than when they are using less anaphoric indefinites. This shows the potential of CRQA to detect even subtle processing differences in ongoing discourse.
Linguistic and psycholinguistic accounts based on the study of English may prove unreliable as guides to sentence processing in even closely related languages. The present study illustrates this claim in a test of sentence interpretation by German-, Italian-, and English-speaking adults. Subjects were presented with simple transitive sentences in which contrasts of (1) word order, (2) agreement, (3) animacy, and (4) stress were systematically varied. For each sentence, subjects were asked to state which of the two nouns was the actor. The results indicated that Americans relied overwhelming on word order, using a first-noun strategy in NVN and a second-noun strategy in VNN and NNV sentences. Germans relied on both agreement and animacy. Italians showed extreme reliance on agreement cues. In both German and Italian, stress played a role in terms of complex interactions with word order and agreement. The findings were interpreted in terms of the “competition model” of Bates and MacWhinney (in H. Winitz (Ed.), Annals of the New York Academy of Sciences Conference on Native and Foreign Language Acquisition. New York: New York Academy of Sciences, 1982) in which cue validity is considered to be the primary determinant of cue strength. According to this model, cues are said to be high in validity when they are also high in applicability and reliability.
The Arctic is the hot spot of the ongoing, global climate change. Over the last decades, near-surface temperatures in the Arctic have been rising almost four times faster than on global average. This amplified warming of the Arctic and the associated rapid changes of its environment are largely influenced by interactions between individual components of the Arctic climate system. On daily to weekly time scales, storms can have major impacts on the Arctic sea-ice cover and are thus an important part of these interactions within the Arctic climate. The sea-ice impacts of storms are related to high wind speeds, which enhance the drift and deformation of sea ice, as well as to changes in the surface energy budget in association with air mass advection, which impact the seasonal sea-ice growth and melt.
The occurrence of storms in the Arctic is typically associated with the passage of transient cyclones. Even though the above described mechanisms how storms/cyclones impact the Arctic sea ice are in principal known, there is a lack of statistical quantification of these effects. In accordance with that, the overarching objective of this thesis is to statistically quantify cyclone impacts on sea-ice concentration (SIC) in the Atlantic Arctic Ocean over the last four decades. In order to further advance the understanding of the related mechanisms, an additional objective is to separate dynamic and thermodynamic cyclone impacts on sea ice and assess their relative importance. Finally, this thesis aims to quantify recent changes in cyclone impacts on SIC. These research objectives are tackled utilizing various data sets, including atmospheric and oceanic reanalysis data as well as a coupled model simulation and a cyclone tracking algorithm.
Results from this thesis demonstrate that cyclones are significantly impacting SIC in the Atlantic Arctic Ocean from autumn to spring, while there are mostly no significant impacts in summer. The strength and the sign (SIC decreasing or SIC increasing) of the cyclone impacts strongly depends on the considered daily time scale and the region of the Atlantic Arctic Ocean. Specifically, an initial decrease in SIC (day -3 to day 0 relative to the cyclone) is found in the Greenland, Barents and Kara Seas, while SIC increases following cyclones (day 0 to day 5 relative to the cyclone) are mostly limited to the Barents and Kara Seas.
For the cold season, this results in a pronounced regional difference between overall (day -3 to day 5 relative to the cyclone) SIC-decreasing cyclone impacts in the Greenland Sea and overall SIC-increasing cyclone impacts in the Barents and Kara Seas. A cyclone case study based on a coupled model simulation indicates that both dynamic and thermodynamic mechanisms contribute to cyclone impacts on sea ice in winter. A typical pattern consisting of an initial dominance of dynamic sea-ice changes followed by enhanced thermodynamic ice growth after the cyclone passage was found. This enhanced ice growth after the cyclone passage most likely also explains the (statistical) overall SIC-increasing effects of cyclones in the Barents and Kara Seas in the cold season.
Significant changes in cyclone impacts on SIC over the last four decades have emerged throughout the year. These recent changes are strongly varying from region to region and month to month. The strongest trends in cyclone impacts on SIC are found in autumn in the Barents and Kara Seas. Here, the magnitude of destructive cyclone impacts on SIC has approximately doubled over the last four decades. The SIC-increasing effects following the cyclone passage have particularly weakened in the Barents Sea in autumn. As a consequence, previously existing overall SIC-increasing cyclone impacts in this region in autumn have recently disappeared. Generally, results from this thesis show that changes in the state of the sea-ice cover (decrease in mean sea-ice concentration and thickness) and near-surface air temperature are most important for changed cyclone impacts on SIC, while changes in cyclone properties (i.e. intensity) do not play a significant role.