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Over the past decades, rapid and constant advances have motivated GNSS technology to approach the ability to monitor transient ground motions with mm to cm accuracy in real-time. As a result, the potential of using real-time GNSS for natural hazards prediction and early warning has been exploited intensively in recent years, e.g., landslides and volcanic eruptions monitoring. Of particular note, compared with traditional seismic instruments, GNSS does not saturate or tilt in terms of co-seismic displacement retrieving, which makes it especially valuable for earthquake and earthquake induced tsunami early warning. In this thesis, we focus on the application of real-time GNSS to fast seismic source inversion and tsunami early warning.
Firstly, we present a new approach to get precise co-seismic displacements using cost effective single-frequency receivers. As is well known, with regard to high precision positioning, the main obstacle for single-frequency GPS receiver is ionospheric delay. Considering that over a few minutes, the change of ionospheric delay is almost linear, we constructed a linear model for each satellite to predict ionospheric delay. The effectiveness of this method has been validated by an out-door experiment and 2011 Tohoku event, which confirms feasibility of using dense GPS networks for geo-hazard early warning at an affordable cost.
Secondly, we extended temporal point positioning from GPS-only to GPS/GLONASS and assessed the potential benefits of multi-GNSS for co-seismic displacement determination. Out-door experiments reveal that when observations are conducted in an adversary environment, adding a couple of GLONASS satellites could provide more reliable results. The case study of 2015 Illapel Mw 8.3 earthquake shows that the biases between co-seismic displacements derived from GPS-only and GPS/GLONASS vary from station to station, and could be up to 2 cm in horizontal direction and almost 3 cm in vertical direction. Furthermore, slips inverted from GPS/GLONASS co-seismic displacements using a layered crust structure on a curved plane are shallower and larger for the Illapel event.
Thirdly, we tested different inversion tools and discussed the uncertainties of using real-time GNSS for tsunami early warning. To be exact, centroid moment tensor inversion, uniform slip inversion using a single Okada fault and distributed slip inversion in layered crust on a curved plane were conducted using co-seismic displacements recorded during 2014 Pisagua earthquake. While the inversion results give similar magnitude and the rupture center, there are significant differences in depth, strike, dip and rake angles, which lead to different tsunami propagation scenarios. Even though, resulting tsunami forecasting along the Chilean coast is close to each other for all three models.
Finally, based on the fact that the positioning performance of BDS is now equivalent to GPS in Asia-Pacific area and Manila subduction zone has been identified as a zone of potential tsunami hazard, we suggested a conceptual BDS/GPS network for tsunami early warning in South China Sea. Numerical simulations with two earthquakes (Mw 8.0 and Mw 7.5) and induced tsunamis demonstrate the viability of this network. In addition, the advantage of BDS/GPS over a single GNSS system by source inversion grows with decreasing earthquake magnitudes.
Extreme hydro-meteorological events, such as severe droughts or heavy rainstorms, constitute primary manifestations of climate variability and exert a critical impact on the natural environment and human society. This is particularly true for high-mountain areas, such as the eastern flank of the southern Central Andes of NW Argentina, a region impacted by deep convection processes that form the basis of extreme events, often resulting in floods, a variety of mass movements, and hillslope processes. This region is characterized by pronounced E-W gradients in topography, precipitation, and vegetation cover, spanning low to medium-elevation, humid and densely vegetated areas to high-elevation, arid and sparsely vegetated environments. This strong E-W gradient is mirrored by differences in the efficiency of surface processes, which mobilize and transport large amounts of sediment through the fluvial system, from the steep hillslopes to the intermontane basins and further to the foreland. In a highly sensitive high-mountain environment like this, even small changes in the spatiotemporal distribution, magnitude and rates of extreme events may strongly impact environmental conditions, anthropogenic activity, and the well-being of mountain communities and beyond. However, although the NW Argentine Andes comprise the catchments for the La Plata river that traverses one of the most populated and economically relevant areas of South America, there are only few detailed investigations of climate variability and extreme hydro-meteorological events.
In this thesis, I focus on deciphering the spatiotemporal variability of rainfall and river discharge, with particular emphasis on extreme hydro-meteorological events in the subtropical southern Central Andes of NW Argentina during the past seven decades. I employ various methods to assess and quantify statistically significant trend patterns of rainfall and river discharge, integrating high-quality daily time series from gauging stations (40 rainfall and 8 river discharge stations) with gridded datasets (CPC-uni and TRMM 3B42 V7), for the period between 1940 and 2015. Evidence for a general intensification of the hydrological cycle at intermediate elevations (~ 0.5 – 3 km asl) at the eastern flank of the southern Central Andes is found both from rainfall and river-discharge time-series analysis during the period from 1940 to 2015. This intensification is associated with the increase of the annual total amount of rainfall and the mean annual discharge. However, most pronounced trends are found at high percentiles, i.e. extreme hydro-meteorological events, particularly during the wet season from December to February.An important outcome of my studies is the recognition of a rapid increase in the amount of river discharge during the period between 1971 and 1977, most likely linked to the 1976-77 global climate shift, which is associated with the North Pacific Ocean sea surface temperature variability. Interestingly, after this rapid increase, both rainfall and river discharge decreased at low and intermediate elevations along the eastern flank of the Andes. In contrast, during the same time interval, at high elevations, extensive areas on the arid Puna de Atacama plateau have recorded increasing annual rainfall totals. This has been associated with more intense extreme hydro-meteorological events from 1979 to 2014. This part of the study reveals that low-, intermediate, and high-elevation sectors in the Andes of NW Argentina respond differently to changing climate conditions.
Possible forcing mechanisms of the pronounced hydro-meteorological variability observed in the study area are also investigated. For the period between 1940 and 2015, I analyzed modes of oscillation of river discharge from small to medium drainage basins (102 to 104 km2), located on the eastern flank of the orogen. First, I decomposed the relevant monthly time series using the Hilbert-Huang Transform, which is particularly appropriate for non-stationary time series that result from non-linear natural processes. I observed that in the study region discharge variability can be described by five quasi-periodic oscillatory modes on timescales varying from 1 to ~20 years. Secondly, I tested the link between river-discharge variations and large-scale climate modes of variability, using different climate indices, such as the BEST ENSO (Bivariate El Niño-Southern Oscillation Time-series) index. This analysis reveals that, although most of the variance on the annual timescale is associated with the South American Monsoon System, a relatively large part of river-discharge variability is linked to Pacific Ocean variability (PDO phases) at multi-decadal timescales (~20 years). To a lesser degree, river discharge variability is also linked to the Tropical South Atlantic (TSA) sea surface temperature anomaly at multi-annual timescales (~2-5 years).
Taken together, these findings exemplify the high degree of sensitivity of high-mountain environments with respect to climatic variability and change. This is particularly true for the topographic transitions between the humid, low-moderate elevations and the semi-arid to arid highlands of the southern Central Andes. Even subtle changes in the hydro-meteorological regime of these areas of the mountain belt react with major impacts on erosional hillslope processes and generate mass movements that fundamentally impact the transport capacity of mountain streams. Despite more severe storms in these areas, the fluvial system is characterized by pronounced variability of the stream power on different timescales, leading to cycles of sediment aggradation, the loss of agriculturally used land and severe impacts on infrastructure.
Eye movements serve as a window into ongoing visual-cognitive processes and can thus be used to investigate how people perceive real-world scenes. A key issue for understanding eye-movement control during scene viewing is the roles of central and peripheral vision, which process information differently and are therefore specialized for different tasks (object identification and peripheral target selection respectively). Yet, rather little is known about the contributions of central and peripheral processing to gaze control and how they are coordinated within a fixation during scene viewing. Additionally, the factors determining fixation durations have long been neglected, as scene perception research has mainly been focused on the factors determining fixation locations. The present thesis aimed at increasing the knowledge on how central and peripheral vision contribute to spatial and, in particular, to temporal aspects of eye-movement control during scene viewing. In a series of five experiments, we varied processing difficulty in the central or the peripheral visual field by attenuating selective parts of the spatial-frequency spectrum within these regions. Furthermore, we developed a computational model on how foveal and peripheral processing might be coordinated for the control of fixation duration. The thesis provides three main findings. First, the experiments indicate that increasing processing demands in central or peripheral vision do not necessarily prolong fixation durations; instead, stimulus-independent timing is adapted when processing becomes too difficult. Second, peripheral vision seems to play a prominent role in the control of fixation durations, a notion also implemented in the computational model. The model assumes that foveal and peripheral processing proceed largely in parallel and independently during fixation, but can interact to modulate fixation duration. Thus, we propose that the variation in fixation durations can in part be accounted for by the interaction between central and peripheral processing. Third, the experiments indicate that saccadic behavior largely adapts to processing demands, with a bias of avoiding spatial-frequency filtered scene regions as saccade targets. We demonstrate that the observed saccade amplitude patterns reflect corresponding modulations of visual attention. The present work highlights the individual contributions and the interplay of central and peripheral vision for gaze control during scene viewing, particularly for the control of fixation duration. Our results entail new implications for computational models and for experimental research on scene perception.
Das Ziel der Doktorarbeit war die Entwicklung und Evaluation eines skillsbasierten primären Präventionsprogramms (Mainzer Schultraining zur Essstörungsprävention (MaiStep)) für partielle und manifeste Essstörungen. Dabei wurde die Wirksamkeit durch einen primären (Reduktion vorhandener Essstörungssymptome) und sekundären (assoziierte Psychopathologie) Zielparameter 3 und 12 Monate nach Durchführung des Trainings überprüft. Innerhalb der randomisiert kontrollierten Studie gab es zwei Interventionsgruppe und eine aktive Kontrollgruppe. 1.654 Jugendliche (weiblich/männlich: 781/873; mittleres Alter: 13.1±0.7; BMI: 20.0±3.5) konnten für die Studie, an zufällig ausgewählten Schulen in Rheinland-Pfalz, rekrutiert werden. Die Entwicklung des Präventionsprogramms basiert auf einem systematischen Literaturreview von 63 wissenschaftlichen Studien über die Prävention von Essstörungen im Kindes- und Jugendalter. Eine Interventionsgruppe wurde durch Psychologinnen/Psychologen und eine zweite durch Lehrkräfte angeleitet. Das in der aktiven Kontrollgruppe durchgeführte Sucht- bzw. Stresspräventionsprogramm wurde durch Lehrkräfte geleitet. MaiStep zeigte zur 3-Monatskatamnese keine signifikanten Effekte im Vergleich zur aktiven Kontrollgruppe. Allerdings zeigten sich nach 12 Monaten multiple signifikante Effekte zwischen den Interventions- und der aktiven Kontrollgruppe. Im Rahmen der Analyse des primären Parameters wurden in den Interventionsgruppen signifikant weniger Jugendliche mit einer partiellen Anorexia nervosa (CHI²(2) = 8.74, p = .01**) und/oder partiellen Bulimia nervosa (CHI²(2) = 7.25, p = .02*) gefunden. Im Rahmen der sekundären Zielparameter zeigten sich signifikante Veränderungen in Subskalen des Eating Disorder Inventory (EDI-2) Schlankheitsstreben (F (2, 355) = 3.94, p = .02*) und Perfektionismus (F (2, 355) = 4.19, p = .01**) sowie dem Body Image Avoidance Questionnaire (BIAQ) (F (2, 525) = 18.79, p = .01**) zwischen den Interventions- und der aktiven Kontrollgruppe. MaiStep kann somit als erfolgreiches Programm zur Reduktion von partiellen Essstörungen für die Altersgruppe der 13- 15-jährigen bezeichnet werden. Trotz unterschiedlicher Wirkmechanismen zeigten sich die Lehrkräfte im Vergleich zu den Psychologinnen/Psychologen ebenso erfolgreich in der Durchführung.
Trial registration MaiStep is registered at the German Clinical Trials Register (DRKS00005050).
The cytoskeleton is an essential component of living cells. It is composed of different types of protein filaments that form complex, dynamically rearranging, and interconnected networks. The cytoskeleton serves a multitude of cellular functions which further depend on the cell context. In animal cells, the cytoskeleton prominently shapes the cell's mechanical properties and movement. In plant cells, in contrast, the presence of a rigid cell wall as well as their larger sizes highlight the role of the cytoskeleton in long-distance intracellular transport. As it provides the basis for cell growth and biomass production, cytoskeletal transport in plant cells is of direct environmental and economical relevance. However, while knowledge about the molecular details of the cytoskeletal transport is growing rapidly, the organizational principles that shape these processes on a whole-cell level remain elusive.
This thesis is devoted to the following question: How does the complex architecture of the plant cytoskeleton relate to its transport functionality? The answer requires a systems level perspective of plant cytoskeletal structure and transport. To this end, I combined state-of-the-art confocal microscopy, quantitative digital image analysis, and mathematically powerful, intuitively accessible graph-theoretical approaches.
This thesis summarizes five of my publications that shed light on the plant cytoskeleton as a transportation network: (1) I developed network-based frameworks for accurate, automated quantification of cytoskeletal structures, applicable in, e.g., genetic or chemical screens; (2) I showed that the actin cytoskeleton displays properties of efficient transport networks, hinting at its biological design principles; (3) Using multi-objective optimization, I demonstrated that different plant cell types sustain cytoskeletal networks with cell-type specific and near-optimal organization; (4) By investigating actual transport of organelles through the cell, I showed that properties of the actin cytoskeleton are predictive of organelle flow and provided quantitative evidence for a coordination of transport at a cellular level; (5) I devised a robust, optimization-based method to identify individual cytoskeletal filaments from a given network representation, allowing the investigation of single filament properties in the network context. The developed methods were made publicly available as open-source software tools.
Altogether, my findings and proposed frameworks provide quantitative, system-level insights into intracellular transport in living cells. Despite my focus on the plant cytoskeleton, the established combination of experimental and theoretical approaches is readily applicable to different organisms. Despite the necessity of detailed molecular studies, only a complementary, systemic perspective, as presented here, enables both understanding of cytoskeletal function in its evolutionary context as well as its future technological control and utilization.
This work reports about new high-resolution imaging and spectroscopic observations of solar type III radio bursts at low radio frequencies in the range from 30 to 80 MHz. Solar type III radio bursts are understood as result of the beam-plasma interaction of electron beams in the corona. The Sun provides a unique opportunity to study these plasma processes of an active star. Its activity appears in eruptive events like flares, coronal mass ejections and radio bursts which are all accompanied by enhanced radio emission. Therefore solar radio emission carries important information about plasma processes associated with the Sun’s activity. Moreover, the Sun’s atmosphere is a unique plasma laboratory with plasma processes under conditions not found in terrestrial laboratories. Because of the Sun’s proximity to Earth, it can be studied in greater detail than any other star but new knowledge about the Sun can be transfer to them. This “solar stellar connection” is important for the understanding of processes on other stars.
The novel radio interferometer LOFAR provides imaging and spectroscopic capabilities to study these processes at low frequencies. Here it was used for solar observations.
LOFAR, the characteristics of its solar data and the processing and analysis of the latter with the Solar Imaging Pipeline and Solar Data Center are described. The Solar Imaging Pipeline is the central software that allows using LOFAR for solar observations. So its development was necessary for the analysis of solar LOFAR data and realized here. Moreover a new density model with heat conduction and Alfvén waves was developed that provides the distance of radio bursts to the Sun from dynamic radio spectra.
Its application to the dynamic spectrum of a type III burst observed on March 16, 2016 by LOFAR shows a nonuniform radial propagation velocity of the radio emission. The analysis of an imaging observation of type III bursts on June 23, 2012 resolves a burst as bright, compact region localized in the corona propagating in radial direction along magnetic field lines with an average velocity of 0.23c. A nonuniform propagation velocity is revealed. A new beam model is presented that explains the nonuniform motion of the radio source as a propagation effect of an electron ensemble with a spread velocity distribution and rules out a monoenergetic electron distribution. The coronal electron number density is derived in the region from 1.5 to 2.5 R☉ and fitted with the newly developed density model. It determines the plasma density for the interplanetary space between Sun and Earth. The values correspond to a 1.25- and 5-fold Newkirk model for harmonic and fundamental emission, respectively. In comparison to data from other radio instruments the LOFAR data shows a high sensitivity and resolution in space, time and frequency.
The new results from LOFAR’s high resolution imaging spectroscopy are consistent with current theories of solar type III radio bursts and demonstrate its capability to track fast moving radio sources in the corona. LOFAR solar data is found to be a valuable source for solar radio physics and opens a new window for studying plasma processes associated with highly energetic electrons in the solar corona.
In this thesis sentence processing was investigated using a psychophysiological measure known as pupillometry as well as Event-Related Potentials (ERP). The scope of the the- sis was broad, investigating the processing of several different movement constructions with native speakers of English and second language learners of English, as well as word order and case marking in German speaking adults and children. Pupillometry and ERP allowed us to test competing linguistic theories and use novel methodologies to investigate the processing of word order. In doing so we also aimed to establish pupillometry as an effective way to investigate the processing of word order thus broadening the methodological spectrum.
The Milky Way is only one out of billions of galaxies in the universe. However, it is a special galaxy because it allows to explore the main mechanisms involved in its evolution and formation history by unpicking the system star-by-star. Especially, the chemical fingerprints of its stars provide clues and evidence of past events in the Galaxy’s lifetime. These information help not only to decipher the current structure and building blocks of the Milky Way, but to learn more about the general formation process of galaxies.
In the past decade a multitude of stellar spectroscopic Galactic surveys have scanned millions of stars far beyond the rim of the solar neighbourhood. The obtained spectroscopic information provide unprecedented insights to the chemo-dynamics of the Milky Way. In addition analytic models and numerical simulations of the Milky Way provide necessary descriptions and predictions suited for comparison with observations in order to decode the physical properties that underlie the complex system of the Galaxy.
In the thesis various approaches are taken to connect modern theoretical modelling of galaxy formation and evolution with observations from Galactic stellar surveys. With its focus on the chemo-kinematics of the Galactic disk this work aims to determine new observational constraints on the formation of the Milky Way providing also proper comparisons with two different models. These are the population synthesis model TRILEGAL based on analytical distribution functions, which aims to simulate the number and distribution of stars in the Milky Way and its different components, and a hybrid model (MCM) that combines an N-body simulation of a Milky Way like galaxy in the cosmological framework with a semi-analytic chemical evolution model for the Milky Way. The major observational data sets in use come from two surveys, namely the “Radial Velocity Experiment” (RAVE) and the “Sloan Extension for Galactic Understanding and Exploration” (SEGUE).
In the first approach the chemo-kinematic properties of the thin and thick disk of the Galaxy as traced by a selection of about 20000 SEGUE G-dwarf stars are directly compared to the predictions by the MCM model. As a necessary condition for this, SEGUE's selection function and its survey volume are evaluated in detail to correct the spectroscopic observations for their survey specific selection biases. Also, based on a Bayesian method spectro-photometric distances with uncertainties below 15% are computed for the selection of SEGUE G-dwarfs that are studied up to a distance of 3 kpc from the Sun.
For the second approach two synthetic versions of the SEGUE survey are generated based on the above models. The obtained synthetic stellar catalogues are then used to create mock samples best resembling the compiled sample of observed SEGUE G-dwarfs. Generally, mock samples are not only ideal to compare predictions from various models. They also allow validation of the models' quality and improvement as with this work could be especially achieved for TRILEGAL. While TRILEGAL reproduces the statistical properties of the thin and thick disk as seen in the observations, the MCM model has shown to be more suitable in reproducing many chemo-kinematic correlations as revealed by the SEGUE stars. However, evidence has been found that the MCM model may be missing a stellar component with the properties of the thick disk that the observations clearly show. While the SEGUE stars do indicate a thin-thick dichotomy of the stellar Galactic disk in agreement with other spectroscopic stellar studies, no sign for a distinct metal-poor disk is seen in the MCM model.
Usually stellar spectroscopic surveys are limited to a certain volume around the Sun covering different regions of the Galaxy’s disk. This often prevents to obtain a global view on the chemo-dynamics of the Galactic disk. Hence, a suitable combination of stellar samples from independent surveys is not only useful for the verification of results but it also helps to complete the picture of the Milky Way. Therefore, the thesis closes with a comparison of the SEGUE G-dwarfs and a sample of RAVE giants. The comparison reveals that the chemo-kinematic relations agree in disk regions where the samples of both surveys show a similar number of stars. For those parts of the survey volumes where one of the surveys lacks statistics they beautifully complement each other. This demonstrates that the comparison of theoretical models on the one side, and the combined observational data gathered by multiple surveys on the other side, are key ingredients to understand and disentangle the structure and formation history of the Milky Way.
This publications-based thesis summarizes my contribution to the scientific field of ultrafast structural dynamics. It consists of 16 publications, about the generation, detection and coupling of coherent gigahertz longitudinal acoustic phonons, also called hypersonic waves. To generate such high frequency phonons, femtosecond near infrared laser pulses were used to heat nanostructures composed of perovskite oxides on an ultrashort timescale. As a consequence the heated regions of such a nanostructure expand and a high frequency acoustic phonon pulse is generated. To detect such coherent acoustic sound pulses I use ultrafast variants of optical Brillouin and x-ray scattering. Here an incident optical or x-ray photon is scattered by the excited sound wave in the sample. The scattered light intensity measures the occupation of the phonon modes.
The central part of this work is the investigation of coherent high amplitude phonon wave packets which can behave nonlinearly, quite similar to shallow water waves which show a steepening of wave fronts or solitons well known as tsunamis. Due to the high amplitude of the acoustic wave packets in the solid, the acoustic properties can change significantly in the vicinity of the sound pulse. This may lead to a shape change of the pulse. I have observed by time-resolved Brillouin scattering, that a single cycle hypersound pulse shows a wavefront steepening. I excited hypersound pulses with strain amplitudes until 1% which I have calibrated by ultrafast x-ray diffraction (UXRD).
On the basis of this first experiment we developed the idea of the nonlinear mixing of narrowband phonon wave packets which we call "nonlinear phononics" in analogy with the nonlinear optics, which summarizes a kaleidoscope of surprising optical phenomena showing up at very high electric fields. Such phenomena are for instance Second Harmonic Generation, four-wave-mixing or solitons. But in case of excited coherent phonons the wave packets have usually very broad spectra which make it nearly impossible to look at elementary scattering processes between phonons with certain momentum and energy.
For that purpose I tested different techniques to excite narrowband phonon wave packets which mainly consist of phonons with a certain momentum and frequency. To this end epitaxially grown metal films on a dielectric substrate were excited with a train of laser pulses. These excitation pulses drive the metal film to oscillate with the frequency given by their inverse temporal displacement and send a hypersonic wave of this frequency into the substrate. The monochromaticity of these wave packets was proven by ultrafast optical Brillouin and x-ray scattering.
Using the excitation of such narrowband phonon wave packets I was able to observe the Second Harmonic Generation (SHG) of coherent phonons as a first example of nonlinear wave mixing of nanometric phonon wave packets.
Change points in time series are perceived as heterogeneities in the statistical or dynamical characteristics of the observations. Unraveling such transitions yields essential information for the understanding of the observed system’s intrinsic evolution and potential external influences. A precise detection of multiple changes is therefore of great importance for various research disciplines, such as environmental sciences, bioinformatics and economics. The primary purpose of the detection approach introduced in this thesis is the investigation of transitions underlying direct or indirect climate observations. In order to develop a diagnostic approach capable to capture such a variety of natural processes, the generic statistical features in terms of central tendency and dispersion are employed in the light of Bayesian inversion. In contrast to established Bayesian approaches to multiple changes, the generic approach proposed in this thesis is not formulated in the framework of specialized partition models of high dimensionality requiring prior specification, but as a robust kernel-based approach of low dimensionality employing least informative prior distributions.
First of all, a local Bayesian inversion approach is developed to robustly infer on the location and the generic patterns of a single transition. The analysis of synthetic time series comprising changes of different observational evidence, data loss and outliers validates the performance, consistency and sensitivity of the inference algorithm. To systematically investigate time series for multiple changes, the Bayesian inversion is extended to a kernel-based inference approach. By introducing basic kernel measures, the weighted kernel inference results are composed into a proxy probability to a posterior distribution of multiple transitions. The detection approach is applied to environmental time series from the Nile river in Aswan and the weather station Tuscaloosa, Alabama comprising documented changes. The method’s performance confirms the approach as a powerful diagnostic tool to decipher multiple changes underlying direct climate observations.
Finally, the kernel-based Bayesian inference approach is used to investigate a set of complex terrigenous dust records interpreted as climate indicators of the African region of the Plio-Pleistocene period. A detailed inference unravels multiple transitions underlying the indirect climate observations, that are interpreted as conjoint changes. The identified conjoint changes coincide with established global climate events. In particular, the two-step transition associated to the establishment of the modern Walker-Circulation contributes to the current discussion about the influence of paleoclimate changes on the environmental conditions in tropical and subtropical Africa at around two million years ago.