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Stochastic information, to be understood as "information gained by the application of stochastic methods", is proposed as a tool in the assessment of changes in climate. This thesis aims at demonstrating that stochastic information can improve the consideration and reduction of uncertainty in the assessment of changes in climate. The thesis consists of three parts. In part one, an indicator is developed that allows the determination of the proximity to a critical threshold. In part two, the tolerable windows approach (TWA) is extended to a probabilistic TWA. In part three, an integrated assessment of changes in flooding probability due to climate change is conducted within the TWA. The thermohaline circulation (THC) is a circulation system in the North Atlantic, where the circulation may break down in a saddle-node bifurcation under the influence of climate change. Due to uncertainty in ocean models, it is currently very difficult to determine the distance of the THC to the bifurcation point. We propose a new indicator to determine the system's proximity to the bifurcation point by considering the THC as a stochastic system and using the information contained in the fluctuations of the circulation around the mean state. As the system is moved closer to the bifurcation point, the power spectrum of the overturning becomes "redder", i.e. more energy is contained in the low frequencies. Since the spectral changes are a generic property of the saddle-node bifurcation, the method is not limited to the THC, but it could also be applicable to other systems, e.g. transitions in ecosystems. In part two, a probabilistic extension to the tolerable windows approach (TWA) is developed. In the TWA, the aim is to determine the complete set of emission strategies that are compatible with so-called guardrails. Guardrails are limits to impacts of climate change or to climate change itself. Therefore, the TWA determines the "maneuvering space" humanity has, if certain impacts of climate change are to be avoided. Due to uncertainty it is not possible to definitely exclude the impacts of climate change considered, but there will always be a certain probability of violating a guardrail. Therefore the TWA is extended to a probabilistic TWA that is able to consider "probabilistic uncertainty", i.e. uncertainty that can be expressed as a probability distribution or uncertainty that arises through natural variability. As a first application, temperature guardrails are imposed, and the dependence of emission reduction strategies on probability distributions for climate sensitivities is investigated. The analysis suggests that it will be difficult to observe a temperature guardrail of 2°C with high probabilities of actually meeting the target. In part three, an integrated assessment of changes in flooding probability due to climate change is conducted. A simple hydrological model is presented, as well as a downscaling scheme that allows the reconstruction of the spatio-temporal natural variability of temperature and precipitation. These are used to determine a probabilistic climate impact response function (CIRF), a function that allows the assessment of changes in probability of certain flood events under conditions of a changed climate. The assessment of changes in flooding probability is conducted in 83 major river basins. Not all floods can be considered: Events that either happen very fast, or affect only a very small area can not be considered, but large-scale flooding due to strong longer-lasting precipitation events can be considered. Finally, the probabilistic CIRFs obtained are used to determine emission corridors, where the guardrail is a limit to the fraction of world population that is affected by a predefined shift in probability of the 50-year flood event. This latter analysis has two main results. The uncertainty about regional changes in climate is still very high, and even small amounts of further climate change may lead to large changes in flooding probability in some river systems.
Origin and symmetry of the observed global magnetic fields in galaxies are not fully understood. We intend to clarify the question of the magnetic field origin and investigate the global action of the magneto-rotational instability (MRI) in galactic disks with the help of 3D global magneto-hydrodynamical (MHD) simulations. The calculations were done with the time-stepping ZEUS 3D code using massive parallelization. The alpha-Omega dynamo is known to be one of the most efficient mechanisms to reproduce the observed global galactic fields. The presence of strong turbulence is a pre-requisite for the alpha-Omega dynamo generation of the regular magnetic fields. The observed magnitude and spatial distribution of turbulence in galaxies present unsolved problems to theoreticians. The MRI is known to be a fast and powerful mechanism to generate MHD turbulence and to amplify magnetic fields. We find that the critical wavelength increases with the increasing of magnetic fields during the simulation, transporting the energy from critical to larger scales. The final structure, if not disrupted by supernovae explosions, is the structure of `thin layers' of thickness of about 100 pcs. An important outcome of all simulations is the magnitude of the horizontal components of the Reynolds and Maxwell stresses. The result is that the MRI-driven turbulence is magnetic-dominated: its magnetic energy exceeds the kinetic energy by a factor of 4. The Reynolds stress is small and less than 1% of the Maxwell stress. The angular momentum transport is thus completely dominated by the magnetic field fluctuations. The volume-averaged pitch angle is always negative with a magnitude of about -30. The non-saturated MRI regime is lasting sufficiently long to fill the time between the galactic encounters, independently of strength and geometry of the initial field. Therefore, we may claim the observed pitch angles can be due to MRI action in the gaseous galactic disks. The MRI is also shown to be a very fast instability with e-folding time proportional to the time of one rotation. Steep rotation curves imply a stronger growth for the magnetic energy due to MRI. The global e-folding time is from 44 Myr to 100 Myr depending on the rotation profile. Therefore, MRI can explain the existence of rather large magnetic field in very young galaxies. We also have reproduced the observed rms values of velocities in the interstellar turbulence as it was observed in NGC 1058. We have shown with the simulations that the averaged velocity dispersion of about 5 km/s is a typical number for the MRI-driven turbulence in galaxies, which agrees with observations. The dispersion increases outside of the disk plane, whereas supernovae-driven turbulence is found to be concentrated within the disk. In our simulations the velocity dispersion increases a few times with the heights. An additional support to the dynamo alpha-effect in the galaxies is the ability of the MRI to produce a mix of quadrupole and dipole symmetries from the purely vertical seed fields, so it also solves the seed-fields problem of the galactic dynamo theory. The interaction of magneto-rotational instability and random supernovae explosions remains an open question. It would be desirable to run the simulation with the supernovae explosions included. They would disrupt the calm ring structure produced by global MRI, may be even to the level when we can no longer blame MRI to be responsible for the turbulence.
Wetting and phase transitions play a very important role our daily life. Molecularly thin films of long-chain alkanes at solid/vapour interfaces (e.g. C30H62 on silicon wafers) are very good model systems for studying the relation between wetting behaviour and (bulk) phase transitions. Immediately above the bulk melting temperature the alkanes wet partially the surface (drops). In this temperature range the substrate surface is covered with a molecularly thin ordered, solid-like alkane film ("surface freezing"). Thus, the alkane melt wets its own solid only partially which is a quite rare phenomenon in nature. The thesis treats about how the alkane melt wets its own solid surface above and below the bulk melting temperature and about the corresponding melting and solidification processes. Liquid alkane drops can be undercooled to few degrees below the bulk melting temperature without immediate solidification. This undercooling behaviour is quite frequent and theoretical quite well understood. In some cases, slightly undercooled drops start to build two-dimensional solid terraces without bulk solidification. The terraces grow radially from the liquid drops on the substrate surface. They consist of few molecular layers with the thickness multiple of all-trans length of the molecule. By analyzing the terrace growth process one can find that, both below and above the melting point, the entire substrate surface is covered with a thin film of mobile alkane molecules. The presence of this film explains how the solid terrace growth is feeded: the alkane molecules flow through it from the undercooled drops to the periphery of the terrace. The study shows for the first time the coexistence of a molecularly thin film ("precursor") with partially wetting bulk phase. The formation and growth of the terraces is observed only in a small temperature interval in which the 2D nucleation of terraces is more likely than the bulk solidification. The nucleation mechanisms for 2D solidification are also analyzed in this work. More surprising is the terrace behaviour above bulk the melting temperature. The terraces can be slightly overheated before they melt. The melting does not occur all over the surface as a single event; instead small drops form at the terrace edge. Subsequently these drops move on the surface "eating" the solid terraces on their way. By this they grow in size leaving behind paths from were the material was collected. Both overheating and droplet movement can be explained by the fact that the alkane melt wets only partially its own solid. For the first time, these results explicitly confirm the supposed connection between the absence of overheating in solid and "surface melting": the solids usually start to melt without an energetic barrier from the surface at temperatures below the bulk melting point. Accordingly, the surface freezing of alkanes give rise of an energetic barrier which leads to overheating.
Subject of this work is the study of applications of the Galactic Microlensing effect, where the light of a distant star (source) is bend according to Einstein's theory of gravity by the gravitational field of intervening compact mass objects (lenses), creating multiple (however not resolvable) images of the source. Relative motion of source, observer and lens leads to a variation of deflection/magnification and thus to a time dependant observable brightness change (lightcurve), a so-called microlensing event, lasting weeks to months. The focus lies on the modeling of binary-lens events, which provide a unique tool to fully characterize the lens-source system and to detect extra-solar planets around the lens star. Making use of the ability of genetic algorithms to efficiently explore large and intricate parameter spaces in the quest for the global best solution, a modeling software (Tango) for binary lenses is developed, presented and applied to data sets from the PLANET microlensing campaign. For the event OGLE-2002-BLG-069 the 2nd ever lens mass measurement has been achieved, leading to a scenario, where a G5III Bulge giant at 9.4 kpc is lensed by an M-dwarf binary with total mass of M=0.51 solar masses at distance 2.9 kpc. Furthermore a method is presented to use the absence of planetary lightcurve signatures to constrain the abundance of extra-solar planets.
Due to its relevance for global climate, the realistic representation of the Atlantic meridional overturning circulation (AMOC) in ocean models is a key task. In recent years, two paradigms have evolved around what are its driving mechanisms: diapycnal mixing and Southern Ocean winds. This work aims at clarifying what sets the strength of the Atlantic overturning components in an ocean general circulation model and discusses the role of spatially inhomogeneous mixing, numerical diffusion and winds. Furthermore, the relation of the AMOC with a key quantity, the meridional pressure difference is analyzed. Due to the application of a very low diffusive tracer advection scheme, a realistic Atlantic overturning circulation can be obtained that is purely wind driven. On top of the winddriven circulation, changes of density gradients are caused by increasing the parameterized eddy diffusion in the North Atlantic and Southern Ocean. The linear relation between the maximum of the Atlantic overturning and the meridional pressure difference found in previous studies is confirmed and it is shown to be due to one significant pressure gradient between the average pressure over high latitude deep water formation regions and a relatively uniform pressure between 30°N and 30°S, which can directly be related to a zonal flow through geostrophy. Under constant Southern Ocean windstress forcing, a South Atlantic outflow in the range of 6-16 Sv is obtained for a large variety of experiments. Overall, the circulation is winddriven but its strength not uniquely determined by the Southern Ocean windstress. The scaling of the Atlantic overturning components is linear with the background vertical diffusivity, not confirming the 2/3 power law for one-hemisphere models without wind forcing. The pycnocline depth is constant in the coarse resolution model with large vertical grid extends. It suggests the ocean model operates like the Stommel box model with a linear relation of the pressure difference and fixed vertical scale for the volume transport. However, this seems only valid for vertical diffusivities smaller 0.4 cm²/s, when the dominant upwelling within the Atlantic occurs along the boundaries. For larger vertical diffusivities, a significant amount of interior upwelling occurs. It is further shown that any localized vertical mixing in the deep to bottom ocean cannot drive an Atlantic overturning. However, enhanced boundary mixing at thermocline depths is potentially important. The numerical diffusion is shown to have a large impact on the representation of the Atlantic overturning in the model. While the horizontal numerical diffusion tends to destabilize the Atlantic overturning the verital numerical diffusion denotes an amplifying mechanism.
It is known that the efficiency of organic light-emitting devices (OLEDs) is strongly influenced by the ’quality′ of the thin films [1]. On the basis of this conviction, the work presented in this thesis aimed to obtain a better understanding of the structure of organic thin films of general interest in the field of organic light emitting devices by using scanning probe microscopies (SPMs). A not yet reported crystal structure of quaterthiophene film grown on potassium hydrogen (KHP) is determined by optical measurements, a simulation program, diffraction at both normal incidence and grazing angle and AFM. The crystal cell is triclinic with parameters a = 0.721 nm, b = 0.632 nm, c = 0.956 nm and a = 91°, b = 91.4°, g = 91° [2]. The morphologies of four organic thin films deposited on gold are characterized by ultra high vacuum scanning tunneling microscopy (UHV-STM). Terraces in an hexanethiol monolayer, lamellar structures in an azobenzenethiol monolayer, rods in a a poly(paraphenylenevinylene) oligomer film and a granular morphology in an oxadiazole film are shown. The topographies of a series of poly(3,4-ethylenedioxythiophene)/poly(styrenesulfonate) (PEDOT/PSS) films deposited on indium-tin oxide (ITO) and gold obtained from dispersions with PEDOT:PSS weight ratios of 1:20, 1:6 and 1:1 are investigated by AFM. It is demonstrated that the films show the same topography on gold and on ITO. It is shown that the PEDOT films eliminate the spike features of ITO. It is reported that PEDOT 1:20 and 1:6 appear indistinguishable between each other but different from PEDOT 1:1 (the most conductive). Coupling STM and I-d measurements, a not yet reported structural model of PEDOT 1:1 on gold is obtained [3]. In this model the surface presents grains and the bulk particles/domains rich in PEDOT embedded in a PEDOT-poor matrix. The equation of conductivity is derived. A STM investigation of four PEDOT films deposited on ITO obtained from dispersions with the same PEDOT:PSS weight ratio of 1:1 is carried out [4]. The films differ either for the presence of sorbitol or for a different synthetic route (and they present different conductivities). For the first time a quantitative and qualitative correlation between the nanometer-scale morphology of PEDOT films with and without sorbitol and their conductivity is established.
The topic of synchronization forms a link between nonlinear dynamics and neuroscience. On the one hand, neurobiological research has shown that the synchronization of neuronal activity is an essential aspect of the working principle of the brain. On the other hand, recent advances in the physical theory have led to the discovery of the phenomenon of phase synchronization. A method of data analysis that is motivated by this finding - phase synchronization analysis - has already been successfully applied to empirical data. The present doctoral thesis ties up to these converging lines of research. Its subject are methodical contributions to the further development of phase synchronization analysis, as well as its application to event-related potentials, a form of EEG data that is especially important in the cognitive sciences. The methodical contributions of this work consist firstly in a number of specialized statistical tests for a difference in the synchronization strength in two different states of a system of two oscillators. Secondly, in regard of the many-channel character of EEG data an approach to multivariate phase synchronization analysis is presented. For the empirical investigation of neuronal synchronization a classic experiment on language processing was replicated, comparing the effect of a semantic violation in a sentence context with that of the manipulation of physical stimulus properties (font color). Here phase synchronization analysis detects a decrease of global synchronization for the semantic violation as well as an increase for the physical manipulation. In the latter case, by means of the multivariate analysis the global synchronization effect can be traced back to an interaction of symmetrically located brain areas.<BR> The findings presented show that the method of phase synchronization analysis motivated by physics is able to provide a relevant contribution to the investigation of event-related potentials in the cognitive sciences.
In this thesis the magnetohydrodynamic jet formation and the effects of magnetic diffusion on the formation of axisymmetric protostellar jets have been investigated in three different simulation sets. The time-dependent numerical simulations have been performed, using the magnetohydrodynamic ZEUS-3D code.
Robotic telescopes & Doppler imaging : measuring differential rotation on long-period active stars
(2004)
The sun shows a wide variety of magnetic-activity related phenomena. The magnetic field responsible for this is generated by a dynamo process which is believed to operate in the tachocline, which is located at the bottom of the convection zone. This dynamo is driven in part by differential rotation and in part by magnetic turbulences in the convection zone. The surface differential rotation, one key ingredient of dynamo theory, can be measured by tracing sunspot positions.To extend the parameter space for dynamo theories, one can extend these measurements to other stars than the sun. The primary obstacle in this endeavor is the lack of resolved surface images on other stars. This can be overcome by the Doppler imaging technique, which uses the rotation-induced Doppler-broadening of spectral lines to compute the surface distribution of a physical parameter like temperature. To obtain the surface image of a star, high-resolution spectroscopic observations, evenly distributed over one stellar rotation period are needed. This turns out to be quite complicated for long period stars. The upcoming robotic observatory STELLA addresses this problem with a dedicated scheduling routine, which is tailored for Doppler imaging targets. This will make observations for Doppler imaging not only easier, but also more efficient.As a preview of what can be done with STELLA, we present results of a Doppler imaging study of seven stars, all of which show evidence for differential rotation, but unfortunately the errors are of the same order of magnitude as the measurements due to unsatisfactory data quality, something that will not happen on STELLA. Both, cross-correlation analysis and the sheared image technique where used to double check the results if possible. For four of these stars, weak anti-solar differential rotation was found in a sense that the pole rotates faster than the equator, for the other three stars weak differential rotation in the same direction as on the sun was found.Finally, these new measurements along with other published measurements of differential rotation using Doppler imaging, were analyzed for correlations with stellar evolution, binarity, and rotation period. The total sample of stars show a significant correlation with rotation period, but if separated into antisolar and solar type behavior, only the subsample showing anti-solar differential rotation shows this correlation. Additionally, there is evidence for binary stars showing less differential rotation as single stars, as is suggested by theory. All other parameter combinations fail to deliver any results due to the still small sample of stars available.
Adherent cells constantly collect information about the mechanical properties of their extracellular environment by actively pulling on it through cell-matrix contacts, which act as mechanosensors. In recent years, the sophisticated use of elastic substrates has shown that cells respond very sensitively to changes in effective stiffness in their environment, which results in a reorganization of the cytoskeleton in response to mechanical input. We develop a theoretical model to predict cellular self-organization in soft materials on a coarse grained level. Although cell organization in principle results from complex regulatory events inside the cell, the typical response to mechanical input seems to be a simple preference for large effective stiffness, possibly because force is more efficiently generated in a stiffer environment. The term effective stiffness comprises effects of both rigidity and prestrain in the environment. This observation can be turned into an optimization principle in elasticity theory. By specifying the cellular probing force pattern and by modeling the environment as a linear elastic medium, one can predict preferred cell orientation and position. Various examples for cell organization, which are of large practical interest, are considered theoretically: cells in external strain fields and cells close to boundaries or interfaces for different sample geometries and boundary conditions. For this purpose the elastic equations are solved exactly for an infinite space, an elastic half space and the elastic sphere. The predictions of the model are in excellent agreement with experiments for fibroblast cells, both on elastic substrates and in hydrogels. Mechanically active cells like fibroblasts could also interact elastically with each other. We calculate the optimal structures on elastic substrates as a function of material properties, cell density and the geometry of cell positioning, respectively, that allows each cell to maximize the effective stiffness in its environment due to the traction of all the other cells. Finally, we apply Monte Carlo simulations to study the effect of noise on cellular structure formation. The model not only contributes to a better understanding of many physiological situations. In the future it could also be used for biomedical applications to optimize protocols for artificial tissues with respect to sample geometry, boundary condition, material properties or cell density.
This work deals with the connection between two basic phenomena in Nonlinear Dynamics: synchronization of chaotic systems and recurrences in phase space. Synchronization takes place when two or more systems adapt (synchronize) some characteristic of their respective motions, due to an interaction between the systems or to a common external forcing. The appearence of synchronized dynamics in chaotic systems is rather universal but not trivial. In some sense, the possibility that two chaotic systems synchronize is counterintuitive: chaotic systems are characterized by the sensitivity ti different initial conditions. Hence, two identical chaotic systems starting at two slightly different initial conditions evolve in a different manner, and after a certain time, they become uncorrelated. Therefore, at a first glance, it does not seem to be plausible that two chaotic systems are able to synchronize. But as we will see later, synchronization of chaotic systems has been demonstrated. On one hand it is important to investigate the conditions under which synchronization of chaotic systems occurs, and on the other hand, to develop tests for the detection of synchronization. In this work, I have concentrated on the second task for the cases of phase synchronization (PS) and generalized synchronization (GS). Several measures have been proposed so far for the detection of PS and GS. However, difficulties arise with the detection of synchronization in systems subjected to rather large amounts of noise and/or instationarities, which are common when analyzing experimental data. The new measures proposed in the course of this thesis are rather robust with respect to these effects. They hence allow to be applied to data, which have evaded synchronization analysis so far. The proposed tests for synchronization in this work are based on the fundamental property of recurrences in phase space.
Understanding stars, their magnetic activity phenomena and the underlying dynamo action is the foundation for understanding 'life, the universe and everything' - as stellar magnetic fields play a fundamental role for star and planet formation and for the terrestrial atmosphere and climate. Starspots are the fingerprints of magnetic field lines and thereby the most important sign of activity in a star's photosphere. However, they cannot be observed directly, as it is not (yet) possible to spacially resolve the surfaces of even the nearest neighbouring stars. Therefore, an indirect approach called 'Doppler imaging' is applied, which allows to reconstruct the surface spot distribution on rapidly rotating, active stars. In this work, data from 11 years of continuous spectroscopic observations of the active binary star EI Eridani are reduced and analysed. 34 Doppler maps are obtained and the problem of how to parameterise the information content of Doppler maps is discussed. Three approaches for parameter extraction are introduced and applied to all maps: average temperature, separated for several latitude bands; fractional spottedness; and, for the analysis of structural temperature distribution, longitudinal and latitudinal spot-occurrence functions. The resulting values do not show a distinct correlation with the proposed activity cycle as seen from photometric long-term observations, thereby suggesting that the photometric activity cycle is not accompanied by a spot cycle as seen on the Sun. The general morphology of the spot pattern on EI Eri remains persistent for the whole period of 11 years. In addition, a detailed parameter study is performed. Improved orbital parameters suggest that EI Eri might be complemented by a third star in a wide orbit of about 19 years. Preliminary differential rotation measurements are carried out, indicating an anti-solar orientation.
In this thesis, dynamical structures and manifolds in closed chaotic flows will be investigated. The knowledge about the dynamical structures (and manifolds) of a system is of importance, since they provide us first information about the dynamics of the system - means, with their help we are able to characterize the flow and maybe even to forecast it`s dynamics. The visualization of such structures in closed chaotic flows is a difficult and often long-lasting process. Here, the so-called 'Leaking-method' will be introduced, in examples of simple mathematical maps as the baker- or sine-map, with which we are able to visualize subsets of the manifolds of the system`s chaotic saddle. Comparisons between the visualized manifolds and structures traced out by chemical or biological reactions superimposed on the same flow will be done in the example of a kinematic model of the Gulf Stream. It will be shown that with the help of the leaking method dynamical structures can be also visualized in environmental systems. In the example of a realistic model of the Mediterranean Sea, the leaking method will be extended to the 'exchange-method'. The exchange method allows us to characterize transport between two regions, to visualize transport routes and their exchange sets and to calculate the exchange times. Exchange times and sets will be shown and calculated for a northern and southern region in the western basin of the Mediterranean Sea. Furthermore, mixing properties in the Earth mantle will be characterized and geometrical properties of manifolds in a 3dimensional mathematical model (ABC map) will be investigated.
Recurrence plots, a rather promising tool of data analysis, have been introduced by Eckman et al. in 1987. They visualise recurrences in phase space and give an overview about the system's dynamics. Two features have made the method rather popular. Firstly they are rather simple to compute and secondly they are putatively easy to interpret. However, the straightforward interpretation of recurrence plots for some systems yields rather surprising results. For example indications of low dimensional chaos have been reported for stock marked data, based on recurrence plots. In this work we exploit recurrences or ``naturally occurring analogues'' as they were termed by E. Lorenz, to obtain three key results. One of which is that the most striking structures which are found in recurrence plots are hinged to the correlation entropy and the correlation dimension of the underlying system. Even though an eventual embedding changes the structures in recurrence plots considerably these dynamical invariants can be estimated independently of the special parameters used for the computation. The second key result is that the attractor can be reconstructed from the recurrence plot. This means that it contains all topological information of the system under question in the limit of long time series. The graphical representation of the recurrences can also help to develop new algorithms and exploit specific structures. This feature has helped to obtain the third key result of this study. Based on recurrences to points which have the same ``recurrence structure'', it is possible to generate surrogates of the system which capture all relevant dynamical characteristics, such as entropies, dimensions and characteristic frequencies of the system. These so generated surrogates are shadowed by a trajectory of the system which starts at different initial conditions than the time series in question. They can be used then to test for complex synchronisation.
One of the most striking features of ecological systems is their ability to undergo sudden outbreaks in the population numbers of one or a small number of species. The similarity of outbreak characteristics, which is exhibited in totally different and unrelated (ecological) systems naturally leads to the question whether there are universal mechanisms underlying outbreak dynamics in Ecology. It will be shown into two case studies (dynamics of phytoplankton blooms under variable nutrients supply and spread of epidemics in networks of cities) that one explanation for the regular recurrence of outbreaks stems from the interaction of the natural systems with periodical variations of their environment. Natural aquatic systems like lakes offer very good examples for the annual recurrence of outbreaks in Ecology. The idea whether chaos is responsible for the irregular heights of outbreaks is central in the domain of ecological modeling. This question is investigated in the context of phytoplankton blooms. The dynamics of epidemics in networks of cities is a problem which offers many ecological and theoretical aspects. The coupling between the cities is introduced through their sizes and gives rise to a weighted network which topology is generated from the distribution of the city sizes. We examine the dynamics in this network and classified the different possible regimes. It could be shown that a single epidemiological model can be reduced to a one-dimensional map. We analyze in this context the dynamics in networks of weighted maps. The coupling is a saturation function which possess a parameter which can be interpreted as an effective temperature for the network. This parameter allows to vary continously the network topology from global coupling to hierarchical network. We perform bifurcation analysis of the global dynamics and succeed to construct an effective theory explaining very well the behavior of the system.
This thesis analyses synchronization phenomena occurring in large ensembles of interacting oscillatory units. In particular, the effects of nonisochronicity (frequency dependence on the oscillator's amplitude) on the macroscopic transition to synchronization are studied in detail. The new phenomena found (Anomalous Synchronization) are investigated in populations of oscillators as well as between oscillator's ensembles.
We calculate the additional carbon emissions as a result of the conversion of natural land in a process of urbanisation; and the change of carbon flows by “urbanised” ecosystems, when the atmospheric carbon is exported to the neighboring territories, from 1980 till 2050 for the eight regions of the world. As a scenario we use combined UN and demographic model′s prognoses for regional total and urban population growth. The calculations of urban areas dynamics are based on two models: the regression model and the Gamma-model. The urbanised area is sub-divided on built-up, „green“ (parks, etc.) and informal settlements (favelas) areas. The next step is to calculate the regional and world dynamics of carbon emission and export, and the annual total carbon balance. Both models give similar results with some quantitative differences. In the first model, the world annual emissions attain a maximum of 205 MtC/year between 2020-2030. Emissions will then slowly decrease. The maximum contributions are given by China and the Asia and Pacific regions. In the second model, world annual emissions increase to 1.25 GtC in 2005, beginning to decrease afterwards. If we compare the emission maximum with the annual emission caused by deforestation, 1.36GtC per year, then we can say that the role of urbanised territories (UT) is of a comparable magnitude. Regarding the world annual export of carbon by UT, we observe its monotonous growth by three times, from 24 MtC to 66 MtC in the first model, and from 249 MtC to 505 MtC in the second one. The latter, is therefore comparable to the amount of carbon transported by rivers into the ocean (196-537 MtC). By estimating the total balance we find that urbanisation shifts the total balance towards a “sink” state. The urbanisation is inhibited in the interval 2020-2030, and by 2050 the growth of urbanised areas would almost stop. Hence, the total emission of natural carbon at that stage will stabilise at the level of the 1980s (80 MtC per year). As estimated by the second model, the total balance, being almost constant until 2000, then starts to decrease at an almost constant rate. We can say that by the end of the XXI century, the total carbon balance will be equal to zero, when the exchange flows are fully balanced, and may even be negative, when the system begins to take up carbon from the atmosphere, i.e., becomes a “sink”.
My thesis is concerned with several new noise-induced phenomena in excitable neural models, especially those with FitzHugh-Nagumo dynamics. In these effects the fluctuations intrinsically present in any complex neural network play a constructive role and improve functionality. I report the occurrence of Vibrational Resonance in excitable systems. Both in an excitable electronic circuit and in the FitzHugh-Nagumo model, I show that an optimal amplitude of high-frequency driving enhances the response of an excitable system to a low-frequency signal. Additionally, the influence of additive noise and the interplay between Stochastic and Vibrational Resonance is analyzed. Further, I study systems which combine both oscillatory and excitable properties, and hence intrinsically possess two internal frequencies. I show that in such a system the effect of Stochastic Resonance can be amplified by an additional high-frequency signal which is in resonance with the oscillatory frequency. This amplification needs much lower noise intensities than for conventional Stochastic Resonance in excitable systems. I study frequency selectivity in noise-induced subthreshold signal processing in a system with many noise-supported stochastic attractors. I show that the response of the coupled elements at different noise levels can be significantly enhanced or reduced by forcing some elements into resonance with these new frequencies which correspond to appropriate phase-relations. A noise-induced phase transition to excitability is reported in oscillatory media with FitzHugh-Nagumo dynamics. This transition takes place via noise-induced stabilization of a deterministically unstable fixed point of the local dynamics, while the overall phase-space structure of the system is maintained. The joint action of coupling and noise leads to a different type of phase transition and results in a stabilization of the system. The resulting noise-induced regime is shown to display properties characteristic of excitable media, such as Stochastic Resonance and wave propagation. This effect thus allows the transmission of signals through an otherwise globally oscillating medium. In particular, these theoretical findings suggest a possible mechanism for suppressing undesirable global oscillations in neural networks (which are usually characteristic of abnormal medical conditions such as Parkinson′s disease or epilepsy), using the action of noise to restore excitability, which is the normal state of neuronal ensembles.
Concerns have been raised that anthropogenic climate change could lead to large-scale singular climate events, i.e., abrupt nonlinear climate changes with repercussions on regional to global scales. One central goal of this thesis is the development of models of two representative components of the climate system that could exhibit singular behavior: the Atlantic thermohaline circulation (THC) and the Indian monsoon. These models are conceived so as to fulfill the main requirements of integrated assessment modeling, i.e., reliability, computational efficiency, transparency and flexibility. The model of the THC is an interhemispheric four-box model calibrated against data generated with a coupled climate model of intermediate complexity. It is designed to be driven by global mean temperature change which is translated into regional fluxes of heat and freshwater through a linear down-scaling procedure. Results of a large number of transient climate change simulations indicate that the reduced-form THC model is able to emulate key features of the behavior of comprehensive climate models such as the sensitivity of the THC to the amount, regional distribution and rate of change in the heat and freshwater fluxes. The Indian monsoon is described by a novel one-dimensional box model of the tropical atmosphere. It includes representations of the radiative and surface fluxes, the hydrological cycle and surface hydrology. Despite its high degree of idealization, the model satisfactorily captures relevant aspects of the observed monsoon dynamics, such as the annual course of precipitation and the onset and withdrawal of the summer monsoon. Also, the model exhibits the sensitivity to changes in greenhouse gas and sulfate aerosol concentrations that are known from comprehensive models. A simplified version of the monsoon model is employed for the identification of changes in the qualitative system behavior against changes in boundary conditions. The most notable result is that under summer conditions a saddle-node bifurcation occurs at critical values of the planetary albedo or insolation. Furthermore, the system exhibits two stable equilibria: besides the wet summer monsoon, a stable state exists which is characterized by a weak hydrological cycle. These results are remarkable insofar, as they indicate that anthropogenic perturbations of the planetary albedo such as sulfur emissions and/or land-use changes could destabilize the Indian summer monsoon. The reduced-form THC model is employed in an exemplary integrated assessment application. Drawing on the conceptual and methodological framework of the tolerable windows approach, emissions corridors (i.e., admissible ranges of CO2- emissions) are derived that limit the risk of a THC collapse while considering expectations about the socio-economically acceptable pace of emissions reductions. Results indicate, for example, a large dependency of the width of the emissions corridor on climate and hydrological sensitivity: for low values of climate and/or hydrological sensitivity, the corridor boundaries are far from being transgressed by any plausible emissions scenario for the 21st century. In contrast, for high values of both quantities low non-intervention scenarios leave the corridor already in the early decades of the 21st century. This implies that if the risk of a THC collapse is to be kept low, business-as-usual paths would need to be abandoned within the next two decades. All in all, this thesis highlights the value of reduced-form modeling by presenting a number of applications of this class of models, ranging from sensitivity and bifurcation analysis to integrated assessment. The results achieved and conclusions drawn provide a useful contribution to the scientific and policy debate about the consequences of anthropogenic climate change and the long-term goals of climate protection. --- Anmerkung: Die Autorin ist Trägerin des von der Mathematisch-Naturwissenschaftlichen Fakultät der Universität Potsdam vergebenen Michelson-Preises für die beste Promotion des Jahres 2003/2004.
A polymer is a large molecule made up of many elementary chemical units, joined together by covalent bonds (for example, polyethylene). Polyelectrolytes (PELs) are polymer chains containing a certain amount of ionizable monomers. With their specific properties PELs acquire big importance in molecular and cell biology as well as in technology. Compared to neutral polymers the theory of PELs is less understood. In particular, this is valid for PELs in poor solvents. A poor solvent environment causes an effective attraction between monomers. Hence, for PELs in a poor solvent, there occurs a competition between attraction and repulsion. Strong or quenched PELs are completely dissociated at any accessible pH. The position of charges along the chain is fixed by chemical synthesis. On the other hand, in weak or annealed PELs dissociation of charges depends on solution pH. For the first time the simulation results have given direct evidence that at rather poor solvents an annealed PEL indeed undergoes a first-order phase transition when the chemical potential (solution pH) reaches at a certain value. The discontinuous transition occurs between a weakly charged compact globular structure and a strongly charged stretched configuration. At not too poor solvents theory predicts that globule would become unstable with respect to the formation of pearl-necklaces. The results show that pearl-necklaces exist in annealed PELs indeed. Furthermore, as predicted by theory, the simulation results have shown that annealed PELs display a sharp transition from a highly charged stretched state to a weakly charged globule at a critical salt concentration.