@article{AikenAikenCotton2018, author = {Aiken, John M. and Aiken, Chastity and Cotton, Fabrice}, title = {A python library for teaching computation to seismology students}, series = {Seismological research letters}, volume = {89}, journal = {Seismological research letters}, number = {3}, publisher = {Seismological Society of America}, address = {Albany}, issn = {0895-0695}, doi = {10.1785/0220170246}, pages = {1165 -- 1171}, year = {2018}, abstract = {Python is at the forefront of scientific computation for seismologists and therefore should be introduced to students interested in becoming seismologists. On its own, Python is open source and well designed with extensive libraries. However, Python code can also be executed, visualized, and communicated to others with "Jupyter Notebooks". Thus, Jupyter Notebooks are ideal for teaching students Python and scientific computation. In this article, we designed an openly available Python library and collection of Jupyter Notebooks based on defined scientific computation learning goals for seismology students. The Notebooks cover topics from an introduction to Python to organizing data, earthquake catalog statistics, linear regression, and making maps. Our Python library and collection of Jupyter Notebooks are meant to be used as course materials for an upper-division data analysis course in an Earth Science Department, and the materials were tested in a Probabilistic Seismic Hazard course. However, seismologists or anyone else who is interested in Python for data analysis and map making can use these materials.}, language = {en} } @article{HeimannVasyuraBathkeSudhausetal.2019, author = {Heimann, Sebastian and Vasyura-Bathke, Hannes and Sudhaus, Henriette and Isken, Marius Paul and Kriegerowski, Marius and Steinberg, Andreas and Dahm, Torsten}, title = {A Python framework for efficient use of pre-computed Green's functions in seismological and other physical forward and inverse source problems}, series = {Solid earth}, volume = {10}, journal = {Solid earth}, number = {6}, publisher = {Copernicus}, address = {G{\"o}ttingen}, issn = {1869-9510}, doi = {10.5194/se-10-1921-2019}, pages = {1921 -- 1935}, year = {2019}, abstract = {The computation of such synthetic GFs is computationally and operationally demanding. As a consequence, the onthe-fly recalculation of synthetic GFs in each iteration of an optimisation is time-consuming and impractical. Therefore, the pre-calculation and efficient storage of synthetic GFs on a dense grid of source to receiver combinations enables the efficient lookup and utilisation of GFs in time-critical scenarios. We present a Python-based framework and toolkit - Pyrocko-GF - that enables the pre-calculation of synthetic GF stores, which are independent of their numerical calculation method and GF transfer function. The framework aids in the creation of such GF stores by interfacing a suite of established numerical forward modelling codes in seismology (computational back ends). So far, interfaces to back ends for layered Earth model cases have been provided; however, the architecture of Pyrocko-GF is designed to cover back ends for other geometries (e.g. full 3-D heterogeneous media) and other physical quantities (e.g. gravity, pressure, tilt). Therefore, Pyrocko-GF defines an extensible GF storage format suitable for a wide range of GF types, especially handling elasticity and wave propagation problems. The framework assists with visualisations, quality control, and the exchange of GF stores, which is supported through an online platform that provides many pre-calculated GF stores for local, regional, and global studies. The Pyrocko-GF toolkit comes with a well-documented application programming interface (API) for the Python programming language to efficiently facilitate forward modelling of geophysical processes, e.g. synthetic waveforms or static displacements for a wide range of source models.}, language = {en} } @article{AlawiSchneiderKallmeyer2014, author = {Alawi, Mashal and Schneider, Beate and Kallmeyer, Jens}, title = {A procedure for separate recovery of extra- and intracellular DNA from a single marine sediment sample}, series = {Journal of microbiological methods}, volume = {104}, journal = {Journal of microbiological methods}, publisher = {Elsevier}, address = {Amsterdam}, issn = {0167-7012}, doi = {10.1016/j.mimet.2014.06.009}, pages = {36 -- 42}, year = {2014}, abstract = {Extracellular DNA (eDNA) is a ubiquitous biological compound in aquatic sediment and soil. Previous studies suggested that eDNA plays an important role in biogeochemical element cycling, horizontal gene transfer and stabilization of biofilm structures. Previous methods for eDNA extraction were either not suitable for oligotrophic sediments or only allowed quantification but no genetic analyses. Our procedure is based on cell detachment and eDNA liberation from sediment particles by sequential washing with an alkaline sodium phosphate buffer followed by a separation of cells and eDNA. The separated eDNA is then bound onto silica particles and purified, whereas the intracellular DNA from the separated cells is extracted using a commercial kit. The method provides extra- and intracellular DNA of high purity that is suitable for downstream applications like PCR. Extracellular DNA was extracted from organic-rich shallow sediment of the Baltic Sea, glacially influenced sediment of the Barents Sea and from the oligotrophic South Pacific Gyre. The eDNA concentration in these samples varied from 23 to 626 ng g(-1) wet weight sediment. A number of experiments were performed to verify each processing step. Although extraction efficiency is higher than other published methods, it is not fully quantitative. (C) 2014 Elsevier B.V. All rights reserved.}, language = {en} } @article{RolinskiRammigWalzetal.2015, author = {Rolinski, Susanne and Rammig, A. and Walz, Ariane and von Bloh, Werner and van Oijen, M. and Thonicke, Kirsten}, title = {A probabilistic risk assessment for the vulnerability of the European carbon cycle to weather extremes: the ecosystem perspective}, series = {Biogeosciences}, volume = {12}, journal = {Biogeosciences}, number = {6}, publisher = {Copernicus}, address = {G{\"o}ttingen}, issn = {1726-4170}, doi = {10.5194/bg-12-1813-2015}, pages = {1813 -- 1831}, year = {2015}, abstract = {Extreme weather events are likely to occur more often under climate change and the resulting effects on ecosystems could lead to a further acceleration of climate change. But not all extreme weather events lead to extreme ecosystem response. Here, we focus on hazardous ecosystem behaviour and identify coinciding weather conditions. We use a simple probabilistic risk assessment based on time series of ecosystem behaviour and climate conditions. Given the risk assessment terminology, vulnerability and risk for the previously defined hazard are estimated on the basis of observed hazardous ecosystem behaviour. We apply this approach to extreme responses of terrestrial ecosystems to drought, defining the hazard as a negative net biome productivity over a 12-month period. We show an application for two selected sites using data for 1981-2010 and then apply the method to the pan-European scale for the same period, based on numerical modelling results (LPJmL for ecosystem behaviour; ERA-Interim data for climate). Our site-specific results demonstrate the applicability of the proposed method, using the SPEI to describe the climate condition. The site in Spain provides an example of vulnerability to drought because the expected value of the SPEI is 0.4 lower for hazardous than for non-hazardous ecosystem behaviour. In northern Germany, on the contrary, the site is not vulnerable to drought because the SPEI expectation values imply wetter conditions in the hazard case than in the non-hazard case. At the pan-European scale, ecosystem vulnerability to drought is calculated in the Mediterranean and temperate region, whereas Scandinavian ecosystems are vulnerable under conditions without water shortages. These first model- based applications indicate the conceptual advantages of the proposed method by focusing on the identification of critical weather conditions for which we observe hazardous ecosystem behaviour in the analysed data set. Application of the method to empirical time series and to future climate would be important next steps to test the approach.}, language = {en} } @misc{RolinskiRammigWalzetal.2014, author = {Rolinski, Susanne and Rammig, Anja and Walz, Ariane and von Bloh, Werner and van Oijen, M. and Thonicke, Kirsten}, title = {A probabilistic risk assessment for the vulnerability of the European carbon cycle to weather extremes}, series = {Postprints der Universit{\"a}t Potsdam : Mathematisch naturwissenschaftliche Reihe (487)}, journal = {Postprints der Universit{\"a}t Potsdam : Mathematisch naturwissenschaftliche Reihe (487)}, number = {487}, issn = {1866-8372}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-407999}, pages = {1813 -- 1831}, year = {2014}, abstract = {Extreme weather events are likely to occur more often under climate change and the resulting effects on ecosystems could lead to a further acceleration of climate change. But not all extreme weather events lead to extreme ecosystem response. Here, we focus on hazardous ecosystem behaviour and identify coinciding weather conditions. We use a simple probabilistic risk assessment based on time series of ecosystem behaviour and climate conditions. Given the risk assessment terminology, vulnerability and risk for the previously defined hazard are estimated on the basis of observed hazardous ecosystem behaviour. We apply this approach to extreme responses of terrestrial ecosystems to drought, defining the hazard as a negative net biome productivity over a 12-month period. We show an application for two selected sites using data for 1981-2010 and then apply the method to the pan-European scale for the same period, based on numerical modelling results (LPJmL for ecosystem behaviour; ERA-Interim data for climate). Our site-specific results demonstrate the applicability of the proposed method, using the SPEI to describe the climate condition. The site in Spain provides an example of vulnerability to drought because the expected value of the SPEI is 0.4 lower for hazardous than for non-hazardous ecosystem behaviour. In northern Germany, on the contrary, the site is not vulnerable to drought because the SPEI expectation values imply wetter conditions in the hazard case than in the non-hazard case. At the pan-European scale, ecosystem vulnerability to drought is calculated in the Mediterranean and temperate region, whereas Scandinavian ecosystems are vulnerable under conditions without water shortages. These first model- based applications indicate the conceptual advantages of the proposed method by focusing on the identification of critical weather conditions for which we observe hazardous ecosystem behaviour in the analysed data set. Application of the method to empirical time series and to future climate would be important next steps to test the approach.}, language = {en} } @article{PaprotnyKreibichMoralesNapolesetal.2020, author = {Paprotny, Dominik and Kreibich, Heidi and Morales-Napoles, Oswaldo and Wagenaar, Dennis and Castellarin, Attilio and Carisi, Francesca and Bertin, Xavier and Merz, Bruno and Schr{\"o}ter, Kai}, title = {A probabilistic approach to estimating residential losses from different flood types}, series = {Natural hazards : journal of the International Society for the Prevention and Mitigation of Natural Hazards}, volume = {105}, journal = {Natural hazards : journal of the International Society for the Prevention and Mitigation of Natural Hazards}, number = {3}, publisher = {Springer}, address = {New York}, issn = {0921-030X}, doi = {10.1007/s11069-020-04413-x}, pages = {2569 -- 2601}, year = {2020}, abstract = {Residential assets, comprising buildings and household contents, are a major source of direct flood losses. Existing damage models are mostly deterministic and limited to particular countries or flood types. Here, we compile building-level losses from Germany, Italy and the Netherlands covering a wide range of fluvial and pluvial flood events. Utilizing a Bayesian network (BN) for continuous variables, we find that relative losses (i.e. loss relative to exposure) to building structure and its contents could be estimated with five variables: water depth, flow velocity, event return period, building usable floor space area and regional disposable income per capita. The model's ability to predict flood losses is validated for the 11 flood events contained in the sample. Predictions for the German and Italian fluvial floods were better than for pluvial floods or the 1993 Meuse river flood. Further, a case study of a 2010 coastal flood in France is used to test the BN model's performance for a type of flood not included in the survey dataset. Overall, the BN model achieved better results than any of 10 alternative damage models for reproducing average losses for the 2010 flood. An additional case study of a 2013 fluvial flood has also shown good performance of the model. The study shows that data from many flood events can be combined to derive most important factors driving flood losses across regions and time, and that resulting damage models could be applied in an open data framework.}, language = {en} } @article{SobelArnaud1999, author = {Sobel, Edward and Arnaud, Nikolas}, title = {A possible middle paleozoic suture in the altyn tagh, NorthWest China}, year = {1999}, language = {en} } @article{KlemmHerzschuhPisaricetal.2013, author = {Klemm, Juliane and Herzschuh, Ulrike and Pisaric, Michael F. J. and Telford, Richard J. and Heim, Birgit and Pestryakova, Luidmila Agafyevna}, title = {A pollen-climate transfer function from the tundra and taiga vegetation in Arctic Siberia and its applicability to a Holocene record}, series = {Palaeogeography, palaeoclimatology, palaeoecology : an international journal for the geo-sciences}, volume = {386}, journal = {Palaeogeography, palaeoclimatology, palaeoecology : an international journal for the geo-sciences}, publisher = {Elsevier}, address = {Amsterdam}, issn = {0031-0182}, doi = {10.1016/j.palaeo.2013.06.033}, pages = {702 -- 713}, year = {2013}, abstract = {This study aims to establish, evaluate, and apply a modern pollen-climate transfer function from the transition zone between arctic tundra and light-needled taiga in Arctic Siberia. Lacustrine samples (n = 96) from the northern Siberian lowlands of Yakutia were collected along four north-to-south transects crossing the arctic forest line. Samples span a broad temperature and precipitation gradient (mean July temperature, T-July: 7.5-18.7 degrees C; mean annual precipitation, P-ann: 114-315 mm/yr). Redundancy analyses are used to examine the relationship between the modern pollen signal and corresponding vegetation types and climate. Performance of transfer functions for T-July and P-ann were cross-validated and tested for spatial autocorrelation effects. The root mean square errors of prediction are 1.67 degrees C for T-July and 40 mm/yr for P-ann. A climate reconstruction based on fossil pollen spectra from a Siberian Arctic lake sediment core spanning the Holocene yielded cold conditions for the Late Glacial (1-2 degrees C below present T-July). Warm and moist conditions were reconstructed for the early to mid Holocene (2 degrees C higher T-July than present), and climate conditions similar to modern ones were reconstructed for the last 4000 years. In conclusion, our modern pollen data set fills the gap of existing regional calibration sets with regard to the underrepresented Siberian tundra-taiga transition zone. The Holocene climate reconstruction indicates that the temperature deviation from modern values was only moderate despite the assumed Arctic sensitivity to present climate change.}, language = {en} } @article{RamischLockotHaberzettletal.2016, author = {Ramisch, Arne and Lockot, Gregori and Haberzettl, Torsten and Hartmann, Kai and Kuhn, Gerhard and Lehmkuhl, Frank and Schimpf, Stefan and Schulte, Philipp and Stauch, Georg and Wang, Rong and Wunnemann, Bernd and Yan, Dada and Zhang, Yongzhan and Diekmann, Bernhard}, title = {A persistent northern boundary of Indian Summer Monsoon precipitation over Central Asia during the Holocene}, series = {Scientific reports}, volume = {6}, journal = {Scientific reports}, publisher = {Nature Publ. Group}, address = {London}, issn = {2045-2322}, doi = {10.1038/srep25791}, pages = {596 -- 633}, year = {2016}, abstract = {Extra-tropical circulation systems impede poleward moisture advection by the Indian Summer Monsoon. In this context, the Himalayan range is believed to insulate the south Asian circulation from extra-tropical influences and to delineate the northern extent of the Indian Summer Monsoon in central Asia. Paleoclimatic evidence, however, suggests increased moisture availability in the Early Holocene north of the Himalayan range which is attributed to an intensification of the Indian Summer Monsoon. Nevertheless, mechanisms leading to a surpassing of the Himalayan range and the northern maximum extent of summer monsoonal influence remain unknown. Here we show that the Kunlun barrier on the northern Tibetan Plateau [similar to 36 degrees N] delimits Indian Summer Monsoon precipitation during the Holocene. The presence of the barrier relocates the insulation effect 1,000 km further north, allowing a continental low intensity branch of the Indian Summer Monsoon which is persistent throughout the Holocene. Precipitation intensities at its northern extent seem to be driven by differentiated solar heating of the Northern Hemisphere indicating dependency on energy-gradients rather than absolute radiation intensities. The identified spatial constraints of monsoonal precipitation will facilitate the prediction of future monsoonal precipitation patterns in Central Asia under varying climatic conditions.}, language = {en} } @article{KuehnScherbaum2016, author = {Kuehn, Nicolas M. and Scherbaum, Frank}, title = {A partially non-ergodic ground-motion prediction equation for Europe and the Middle East}, series = {Bulletin of earthquake engineering : official publication of the European Association for Earthquake Engineering}, volume = {14}, journal = {Bulletin of earthquake engineering : official publication of the European Association for Earthquake Engineering}, publisher = {Springer}, address = {Dordrecht}, issn = {1570-761X}, doi = {10.1007/s10518-016-9911-x}, pages = {2629 -- 2642}, year = {2016}, abstract = {A partially non-ergodic ground-motion prediction equation is estimated for Europe and the Middle East. Therefore, a hierarchical model is presented that accounts for regional differences. For this purpose, the scaling of ground-motion intensity measures is assumed to be similar, but not identical in different regions. This is achieved by assuming a hierarchical model, where some coefficients are treated as random variables which are sampled from an underlying global distribution. The coefficients are estimated by Bayesian inference. This allows one to estimate the epistemic uncertainty in the coefficients, and consequently in model predictions, in a rigorous way. The model is estimated based on peak ground acceleration data from nine different European/Middle Eastern regions. There are large differences in the amount of earthquakes and records in the different regions. However, due to the hierarchical nature of the model, regions with only few data points borrow strength from other regions with more data. This makes it possible to estimate a separate set of coefficients for all regions. Different regionalized models are compared, for which different coefficients are assumed to be regionally dependent. Results show that regionalizing the coefficients for magnitude and distance scaling leads to better performance of the models. The models for all regions are physically sound, even if only very few earthquakes comprise one region.}, language = {en} }