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Semi-empirical sea-level models (SEMs) exploit physically motivated empirical relationships between global sea level and certain drivers, in the following global mean temperature. This model class evolved as a supplement to process-based models (Rahmstorf (2007)) which were unable to fully represent all relevant processes. They thus failed to capture past sea-level change (Rahmstorf et al. (2012)) and were thought likely to underestimate future sea-level rise. Semi-empirical models were found to be a fast and useful tool for exploring the uncertainties in future sea-level rise, consistently giving significantly higher projections than process-based models.
In the following different aspects of semi-empirical sea-level modelling have been studied. Models were first validated using various data sets of global sea level and temperature. SEMs were then used on the glacier contribution to sea level, and to infer past global temperature from sea-level data via inverse modelling. Periods studied encompass the instrumental period, covered by tide gauges (starting 1700 CE (Common Era) in Amsterdam) and satellites (first launched in 1992 CE), the era from 1000 BCE (before CE) to present, and the full length of the Holocene (using proxy data). Accordingly different data, model formulations and implementations have been used. It could be shown in Bittermann et al. (2013) that SEMs correctly predict 20th century sea-level when calibrated with data until 1900 CE. SEMs also turned out to give better predictions than the Intergovernmental Panel on Climate Change (IPCC) 4th assessment report (AR4, IPCC (2007)) models, for the period from 1961–2003 CE.
With the first multi-proxy reconstruction of global sea-level as input, estimate of the human-induced component of modern sea-level change and projections of future sea-level rise were calculated (Kopp et al. (2016)). It turned out with 90% confidence that more than 40 % of the observed 20th century sea-level rise is indeed anthropogenic. With the new semi-empirical and IPCC (2013) 5th assessment report (AR5) projections the gap between SEM and process-based model projections closes, giving higher credibility to both. Combining all scenarios, from strong mitigation to business as usual, a global sea-level rise of 28–131 cm relative to 2000 CE, is projected with 90% confidence. The decision for a low carbon pathway could halve the expected global sea-level rise by 2100 CE.
Present day temperature and thus sea level are driven by the globally acting greenhouse-gas forcing. Unlike that, the Milankovich forcing, acting on Holocene timescales, results mainly in a northern-hemisphere temperature change. Therefore a semi-empirical model can be driven with northernhemisphere temperatures, which makes it possible to model the main subcomponent of sea-level change over this period. It showed that an additional positive constant rate of the order of the estimated Antarctic sea-level contribution is then required to explain the sea-level evolution over the Holocene. Thus the global sea level, following the climatic optimum, can be interpreted as the sum of a temperature induced sea-level drop and a positive long-term contribution, likely an ongoing response to deglaciation coming from Antarctica.
The relationship between nutrition and the development of chronic diseases including metabolic syndrome, diabetes mellitus, cancer and cardiovascular disease has been well studied. On the other hand, changes in the GH-IGF-1 axis in association with nutrition-related diseases have been reported. The interplay between GH, total IGF-1 and different inhibitory and stimulatory kinds of IGF-1 binding proteins (IGFBPs) results in IGF-1 bioactivity, the ability of IGF-1 to induce phosphorylation of its receptor and consequently its signaling. Moreover, IGF-1 bioactivity is sufficient to reflect any change in the GH-IGF-1 system. Accumulating evidence suggests that both of high protein diet, characterized by increased glucagon secretion, and insulin-induced hypoglycemia increase mortality rate and the mechanisms are unclear. However both of glucagon and insulin-induced hypoglycemia are potent stimuli of GH secretion. The aim of the current study was to identify the impact of glucagon and insulin-induced hypoglycemia on IGF-1 bioactivity as possible mechanisms. In a double-blind placebo-controlled study, glucagon was intramuscularly administrated in 13 type 1 diabetic patients (6 males /7 females; [BMI]: 24.8 ± 0.95 kg/m2), 11 obese subjects (OP; 5/ 6; 34.4 ± 1.7 kg/m2), and 13 healthy lean participants (LP; 6/ 7; 21.7 ± 0.6 kg/m2), whereas 12 obese subjects (OP; 6/ 6; 34.4 ± 1.7 kg/m2), and 13 healthy lean participants (LP; 6/ 7; 21.7 ± 0.6 kg/m2) performed insulin tolerance test in another double-blind placebo-controlled study and changes in GH, total IGF-1, IGF binding proteins (IGFBPs) and IGF-1 bioactivity, measured by the cell-based KIRA method, were investigated. In addition, the interaction between the metabolic hormones (glucagon and insulin) and the GH-IGF-1 system on the transcriptional level was studied using mouse primary hepatocytes. In this thesis, glucagon decreased IGF-1 bioactivity in humans independently of endogenous insulin levels, most likely through modulation of IGFBP-1 and-2 levels. The glucagon-induced reduction in IGF-1 bioactivity may represent a novel mechanism underlying the impact of glucagon on GH secretion and may explain the negative effect of high protein diet related to increased cardiovascular risk and mortality rate. In addition, insulin-induced hypoglycemia was correlated with a decrease in IGF-1 bioactivity through up-regulation of IGFBP-2. These results may refer to a possible and poorly explored mechanism explaining the strong association between hypoglycemia and increased cardiovascular mortality among diabetic patients.
Adjustment of empirically derived ground motion prediction equations (GMPEs), from a data- rich region/site where they have been derived to a data-poor region/site, is one of the major challenges associated with the current practice of seismic hazard analysis. Due to the fre- quent use in engineering design practices the GMPEs are often derived for response spectral ordinates (e.g., spectral acceleration) of a single degree of freedom (SDOF) oscillator. The functional forms of such GMPEs are based upon the concepts borrowed from the Fourier spectral representation of ground motion. This assumption regarding the validity of Fourier spectral concepts in the response spectral domain can lead to consequences which cannot be explained physically.
In this thesis, firstly results from an investigation that explores the relationship between Fourier and response spectra, and implications of this relationship on the adjustment issues of GMPEs, are presented. The relationship between the Fourier and response spectra is explored by using random vibration theory (RVT), a framework that has been extensively used in earthquake engineering, for instance within the stochastic simulation framework and in the site response analysis. For a 5% damped SDOF oscillator the RVT perspective of response spectra reveals that no one-to-one correspondence exists between Fourier and response spectral ordinates except in a limited range (i.e., below the peak of the response spectra) of oscillator frequencies. The high oscillator frequency response spectral ordinates are dominated by the contributions from the Fourier spectral ordinates that correspond to the frequencies well below a selected oscillator frequency. The peak ground acceleration (PGA) is found to be related with the integral over the entire Fourier spectrum of ground motion which is in contrast to the popularly held perception that PGA is a high-frequency phenomenon of ground motion.
This thesis presents a new perspective for developing a response spectral GMPE that takes the relationship between Fourier and response spectra into account. Essentially, this frame- work involves a two-step method for deriving a response spectral GMPE: in the first step two empirical models for the FAS and for a predetermined estimate of duration of ground motion are derived, in the next step, predictions from the two models are combined within the same RVT framework to obtain the response spectral ordinates. In addition to that, a stochastic model based scheme for extrapolating the individual acceleration spectra beyond the useable frequency limits is also presented. To that end, recorded acceleration traces were inverted to obtain the stochastic model parameters that allow making consistent extrapola- tion in individual (acceleration) Fourier spectra. Moreover an empirical model, for a dura- tion measure that is consistent within the RVT framework, is derived. As a next step, an oscillator-frequency-dependent empirical duration model is derived that allows obtaining the most reliable estimates of response spectral ordinates. The framework of deriving the response spectral GMPE presented herein becomes a self-adjusting model with the inclusion of stress parameter (∆σ) and kappa (κ0) as the predictor variables in the two empirical models. The entire analysis of developing the response spectral GMPE is performed on recently compiled RESORCE-2012 database that contains recordings made from Europe, the Mediterranean and the Middle East. The presented GMPE for response spectral ordinates should be considered valid in the magnitude range of 4 ≤ MW ≤ 7.6 at distances ≤ 200 km.
Reconstructing climate from the Dead Sea sediment record using high-resolution micro-facies analyses
(2015)
The sedimentary record of the Dead Sea is a key archive for reconstructing climate in the eastern Mediterranean region, as it stores the environmental and tectonic history of the Levant for the entire Quaternary. Moreover, the lake is located at the boundary between Mediterranean sub-humid to semi-arid and Saharo-Arabian hyper-arid climates, so that even small shifts in atmospheric circulation are sensitively recorded in the sediments. This DFG-funded doctoral project was carried out within the ICDP Dead Sea Deep Drilling Project (DSDDP) that intended to gain the first long, continuous and high-resolution sediment core from the deep Dead Sea basin. The drilling campaign was performed in winter 2010-11 and more than 700 m of sediments were recovered. The main aim of this thesis was (1) to establish the lithostratigraphic framework for the ~455 m long sediment core from the deep Dead Sea basin and (2) to apply high-resolution micro-facies analyses for reconstructing and better understanding climate variability from the Dead Sea sediments.
Addressing the first aim, the sedimentary facies of the ~455 m long deep-basin core 5017-1 were described in great detail and characterised through continuous overview-XRF element scanning and magnetic susceptibility measurements. Three facies groups were classified: (1) the marl facies group, (2) the halite facies group and (3) a group involving different expressions of massive, graded and slumped deposits including coarse clastic detritus. Core 5017-1 encompasses a succession of four main lithological units. Based on first radiocarbon and U-Th ages and correlation of these units to on-shore stratigraphic sections, the record comprises the last ca 220 ka, i.e. the upper part of the Amora Formation (parts of or entire penultimate interglacial and glacial), the last interglacial Samra Fm. (~135-75 ka), the last glacial Lisan Fm. (~75-14 ka) and the Holocene Ze’elim Formation. A major advancement of this record is that, for the first time, also transitional intervals were recovered that are missing in the exposed formations and that can now be studied in great detail.
Micro-facies analyses involve a combination of high-resolution microscopic thin section analysis and µXRF element scanning supported by magnetic susceptibility measurements. This approach allows identifying and characterising micro-facies types, detecting event layers and reconstructing past climate variability with up to seasonal resolution, given that the analysed sediments are annually laminated. Within this thesis, micro-facies analyses, supported by further sedimentological and geochemical analyses (grain size, X-ray diffraction, total organic carbon and calcium carbonate contents) and palynology, were applied for two time intervals:
(1) The early last glacial period ~117-75 ka was investigated focusing on millennial-scale hydroclimatic variations and lake level changes recorded in the sediments. Thereby, distinguishing six different micro-facies types with distinct geochemical and sedimentological characteristics allowed estimating relative lake level and water balance changes of the lake. Comparison of the results to other records in the Mediterranean region suggests a close link of the hydroclimate in the Levant to North Atlantic and Mediterranean climates during the time of the build-up of Northern hemisphere ice sheets during the early last glacial period.
(2) A mostly annually laminated late Holocene section (~3700-1700 cal yr BP) was analysed in unprecedented detail through a multi-proxy, inter-site correlation approach of a shallow-water core (DSEn) and its deep-basin counterpart (5017-1). Within this study, a ca 1500 years comprising time series of erosion and dust deposition events was established and anchored to the absolute time-scale through 14C dating and age modelling. A particular focus of this study was the characterisation of two dry periods, from ~3500 to 3300 and from ~3000 to 2400 cal yr BP, respectively. Thereby, a major outcome was the coincidence of the latter dry period with a period of moist and cold climate in Europe related to a Grand Solar Minimum around 2800 cal yr BP and an increase in flood events despite overall dry conditions in the Dead Sea region during that time. These contrasting climate signatures in Europe and at the Dead Sea were likely linked through complex teleconnections of atmospheric circulation, causing a change in synoptic weather patterns in the eastern Mediterranean.
In summary, within this doctorate the lithostratigraphic framework of a unique long sediment core from the deep Dead Sea basin is established, which serves as a base for any further high-resolution investigations on this core. It is demonstrated in two case studies that micro-facies analyses are an invaluable tool to understand the depositional processes in the Dead Sea and to decipher past climate variability in the Levant on millennial to seasonal time-scales. Hence, this work adds important knowledge helping to establish the deep Dead Sea record as a key climate archive of supra-regional significance.
In this thesis we study reciprocal classes of Markov chains. Given a continuous time Markov chain on a countable state space, acting as reference dynamics, the associated reciprocal class is the set of all probability measures on path space that can be written as a mixture of its bridges. These processes possess a conditional independence property that generalizes the Markov property, and evolved from an idea of Schrödinger, who wanted to obtain a probabilistic interpretation of quantum mechanics.
Associated to a reciprocal class is a set of reciprocal characteristics, which are space-time functions that determine the reciprocal class. We compute explicitly these characteristics, and divide them into two main families: arc characteristics and cycle characteristics. As a byproduct, we obtain an explicit criterion to check when two different Markov chains share their bridges.
Starting from the characteristics we offer two different descriptions of the reciprocal class, including its non-Markov probabilities.
The first one is based on a pathwise approach and the second one on short time asymptotic. With the first approach one produces a family of functional equations whose only solutions are precisely the elements of the reciprocal class. These equations are integration by parts on path space associated with derivative operators which perturb the paths by mean of the addition of random loops. Several geometrical tools are employed to construct such formulas. The problem of obtaining sharp characterizations is also considered, showing some interesting connections with discrete geometry. Examples of such formulas are given in the framework of counting processes and random walks on Abelian groups, where the set of loops has a group structure.
In addition to this global description, we propose a second approach by looking at the short time behavior of a reciprocal process. In the same way as the Markov property and short time expansions of transition probabilities characterize Markov chains, we show that a reciprocal class is characterized by imposing the reciprocal property and two families of short time expansions for the bridges. Such local approach is suitable to study reciprocal processes on general countable graphs. As application of our characterization, we considered several interesting graphs, such as lattices, planar
graphs, the complete graph, and the hypercube.
Finally, we obtain some first results about concentration of measure implied by lower bounds on the reciprocal characteristics.