Perspectives of regional paleoclimate modeling

Regional climate modeling bridges the gap between the coarse resolution of current global climate models and the regional‐to‐local scales, where the impacts of climate change are of primary interest. Here, we present a review of the added value of the regional climate modeling approach within the scope of paleoclimate research and discuss the current major challenges and perspectives. Two time periods serve as an example: the Holocene, including the Last Millennium, and the Last Glacial Maximum. Reviewing the existing literature reveals the benefits of regional paleo climate modeling, particularly over areas with complex terrain. However, this depends largely on the variable of interest, as the added value of regional modeling arises from a more realistic representation of physical processes and climate feedbacks compared to global climate models, and this affects different climate variables in various ways. In particular, hydrological processes have been shown to be better represented in regional models, and they can deliver more realistic meteorological data to drive ice sheet and glacier modeling. Thus, regional climate models provide a clear benefit to answer fundamental paleoclimate research questions and may be key to advance a meaningful joint interpretation of climate model and proxy data

Hidden multiple bond effects in dynamic force spectroscopy

In dynamic force spectroscopy, a (bio-)molecular complex is subjected to a steadily increasing force until the chemical bond breaks. Repeating the same experiment many times results in a broad distribution of rupture forces, whose quantitative interpretation represents a formidable theoretical challenge. In this study we address the situation that more than a single molecular bond is involved in one experimental run, giving rise to multiple rupture events which are even more difficult to analyze and thus are usually eliminated as far as possible from the further evaluation of the experimental data. We develop and numerically solve a detailed model of a complete dynamic force spectroscopy experiment including a possible clustering of molecules on the substrate surface, the formation of bonds, their dissociation under load, and the post processing of the force extension curves. We show that the data, remaining after elimination of obvious multiple rupture events, may still contain a considerable number of "hidden" multiple bonds, which are experimentally indistinguishable from "true" single bonds, but which have considerable effects on the resulting rupture force statistics and its consistent theoretical interpretation.Comment: 31 pages, 7 figure

Perspectives of regional paleoclimate modeling

Regional climate modeling bridges the gap between the coarse resolution of current global climate models and the regional-to-local scales, where the impacts of climate change are of primary interest. Here, we present a review of the added value of the regional climate modeling approach within the scope of paleoclimate research and discuss the current major challenges and perspectives. Two time periods serve as an example: the Holocene, including the Last Millennium, and the Last Glacial Maximum. Reviewing the existing literature reveals the benefits of regional paleo climate modeling, particularly over areas with complex terrain. However, this depends largely on the variable of interest, as the added value of regional modeling arises from a more realistic representation of physical processes and climate feedbacks compared to global climate models, and this affects different climate variables in various ways. In particular, hydrological processes have been shown to be better represented in regional models, and they can deliver more realistic meteorological data to drive ice sheet and glacier modeling. Thus, regional climate models provide a clear benefit to answer fundamental paleoclimate research questions and may be key to advance a meaningful joint interpretation of climate model and proxy data

Massively Parallel RNA Sequencing Identifies a Complex Immune Gene Repertoire in the lophotrochozoan Mytilus edulis

The marine mussel Mytilus edulis and its closely related sister species are distributed world-wide and play an important role in coastal ecology and economy. The diversification in different species and their hybrids, broad ecological distribution, as well as the filter feeding mode of life has made this genus an attractive model to investigate physiological and molecular adaptations and responses to various biotic and abiotic environmental factors. In the present study we investigated the immune system of Mytilus, which may contribute to the ecological plasticity of this species. We generated a large Mytilus transcriptome database from different tissues of immune challenged and stress treated individuals from the Baltic Sea using 454 pyrosequencing. Phylogenetic comparison of orthologous groups of 23 species demonstrated the basal position of lophotrochozoans within protostomes. The investigation of immune related transcripts revealed a complex repertoire of innate recognition receptors and downstream pathway members including transcripts for 27 toll-like receptors and 524 C1q domain containing transcripts. NOD-like receptors on the other hand were absent. We also found evidence for sophisticated TNF, autophagy and apoptosis systems as well as for cytokines. Gill tissue and hemocytes showed highest expression of putative immune related contigs and are promising tissues for further functional studies. Our results partly contrast with findings of a less complex immune repertoire in ecdysozoan and other lophotrochozoan protostomes. We show that bivalves are interesting candidates to investigate the evolution of the immune system from basal metazoans to deuterostomes and protostomes and provide a basis for future molecular work directed to immune system functioning in Mytilus

Term Structure Models Driven by General Lévy Processes

As a generalization of the Gaussian Heath-Jarrow-Morton term structure model, we present a new class of bond price models that can be driven by a wide range of Lévy processes. We deduce the forward and short rate processes implied by this model and prove that, under certain assumptions, the short rate is Markovian if and only if the volatility structure has either the Vasicek or the Ho-Lee form. Finally, we compare numerically forward rates and European call option prices in a model driven by a hyperbolic Lévy motion with those in the Gaussian model. Copyright Blackwell Publishers Inc 1999.

Term Structure Models Driven by General Lévy Processes

As a generalization of the Gaussian Heath-Jarrow-Morton term structure model, we present a new class of bond price models that can be driven by a wide range of L'evy processes. We deduce the forward and short rate processes implied by this model and prove that, under certain assumptions, the short rate is Markovian if and only if the volatility structure has either the Vasicek or the Ho-Lee form. Finally, we compare numerically forward rates and European call option prices in a model driven by a hyperbolic L'evy motion with those in the Gaussian model. Keywords: term structure models, martingale modelling, L'evy process, hyperbolic L'evy motion, Markov property, Vasicek model 1 Introduction Models of the term structure of interest rates are important for many problems in economics, in particular for the valuation of contingent claims depending on interest rate sensitive assets. In the Heath-Jarrow-Morton (1992) setting, one assumes that there is a complete set of zero coupon bonds w..

Evaluating the dependence structure of compound precipitation and wind speed extremes

Estimating the likelihood of compound climate extremes such as concurrent drought and heatwaves or compound precipitation and wind speed extremes is important for assessing climate risks. Typically, simulations from climate models are used to assess future risks, but it is largely unknown how well the current generation of models represents compound extremes. Here, we introduce a new metric that measures whether the tails of bivariate distributions show a similar dependence structure across different datasets. We analyse com-pound precipitation and wind extremes in reanalysis data and different high-resolution simulations for central Europe. A state-of-the-art reanalysis dataset (ERA5) is compared to simulations with a weather model (Weather Research and Forecasting – WRF) either driven by observation-based boundary conditions or a global circulation model (Community Earth System Model – CESM) under present-day and future conditions with strong greenhouse gas forcing (Representative Concentration Pathway 8.5 – RCP8.5). Over the historical period, the high-resolution WRF simulations capture precipitation and wind extremes as well as their response to orographic effects more realistically than ERA5. Thus, WRF simulations driven by observation-based boundary conditions are used as a benchmark for evaluating the dependence structure of wind and precipitation extremes. Overall, boundary conditions in WRF appear to be the key factor in explaining differences in the dependence behaviour between strong wind and heavy precipitation between simulations. In comparison, external forcings (RCP8.5) are of second order. Our approach offers new methodological tools to evaluate climate model simulations with respect to compound extremes

Lévy term structure models: No-arbitrage and completeness

The Lévy term structure model due to Eberlein and Raible is extended to non-homogeneous driving processes. The classes of equivalent martingale and local martingale measures for various filtrations are characterized. It turns out that in a number of standard situations the martingale measure is unique. Copyright Springer-Verlag Berlin/Heidelberg 2005Term structures, Lévy processes, no-arbitrage, completeness,