TY - JOUR A1 - Molkenthin, Christian A1 - Donner, Christian A1 - Reich, Sebastian A1 - Zöller, Gert A1 - Hainzl, Sebastian A1 - Holschneider, Matthias A1 - Opper, Manfred T1 - GP-ETAS: semiparametric Bayesian inference for the spatio-temporal epidemic type aftershock sequence model JF - Statistics and Computing N2 - The spatio-temporal epidemic type aftershock sequence (ETAS) model is widely used to describe the self-exciting nature of earthquake occurrences. While traditional inference methods provide only point estimates of the model parameters, we aim at a fully Bayesian treatment of model inference, allowing naturally to incorporate prior knowledge and uncertainty quantification of the resulting estimates. Therefore, we introduce a highly flexible, non-parametric representation for the spatially varying ETAS background intensity through a Gaussian process (GP) prior. Combined with classical triggering functions this results in a new model formulation, namely the GP-ETAS model. We enable tractable and efficient Gibbs sampling by deriving an augmented form of the GP-ETAS inference problem. This novel sampling approach allows us to assess the posterior model variables conditioned on observed earthquake catalogues, i.e., the spatial background intensity and the parameters of the triggering function. Empirical results on two synthetic data sets indicate that GP-ETAS outperforms standard models and thus demonstrate the predictive power for observed earthquake catalogues including uncertainty quantification for the estimated parameters. Finally, a case study for the l'Aquila region, Italy, with the devastating event on 6 April 2009, is presented. KW - Self-exciting point process KW - Hawkes process KW - Spatio-temporal ETAS model KW - Bayesian inference KW - Sampling KW - Earthquake modeling KW - Gaussian process KW - Data augmentation Y1 - 2022 U6 - https://doi.org/10.1007/s11222-022-10085-3 SN - 0960-3174 SN - 1573-1375 VL - 32 IS - 2 PB - Springer CY - Dordrecht ER - TY - JOUR A1 - Schanner, Maximilian A1 - Korte, Monika A1 - Holschneider, Matthias T1 - ArchKalmag14k: A kalman-filter based global geomagnetic model for the holocene JF - Journal of geophysical research : Solid earth N2 - We propose a global geomagnetic field model for the last 14 thousand years, based on thermoremanent records. We call the model ArchKalmag14k. ArchKalmag14k is constructed by modifying recently proposed algorithms, based on space-time correlations. Due to the amount of data and complexity of the model, the full Bayesian posterior is numerically intractable. To tackle this, we sequentialize the inversion by implementing a Kalman-filter with a fixed time step. Every step consists of a prediction, based on a degree dependent temporal covariance, and a correction via Gaussian process regression. Dating errors are treated via a noisy input formulation. Cross correlations are reintroduced by a smoothing algorithm and model parameters are inferred from the data. Due to the specific statistical nature of the proposed algorithms, the model comes with space and time-dependent uncertainty estimates. The new model ArchKalmag14k shows less variation in the large-scale degrees than comparable models. Local predictions represent the underlying data and agree with comparable models, if the location is sampled well. Uncertainties are bigger for earlier times and in regions of sparse data coverage. We also use ArchKalmag14k to analyze the appearance and evolution of the South Atlantic anomaly together with reverse flux patches at the core-mantle boundary, considering the model uncertainties. While we find good agreement with earlier models for recent times, our model suggests a different evolution of intensity minima prior to 1650 CE. In general, our results suggest that prior to 6000 BCE the data is not sufficient to support global models. Y1 - 2022 U6 - https://doi.org/10.1029/2021JB023166 SN - 2169-9313 SN - 2169-9356 VL - 127 IS - 2 PB - American Geophysical Union CY - Washington ER - TY - JOUR A1 - Ropp, Guillaume A1 - Lesur, Vincent A1 - Bärenzung, Julien A1 - Holschneider, Matthias T1 - Sequential modelling of the Earth’s core magnetic field JF - Earth, Planets and Space N2 - We describe a new, original approach to the modelling of the Earth's magnetic field. The overall objective of this study is to reliably render fast variations of the core field and its secular variation. This method combines a sequential modelling approach, a Kalman filter, and a correlation-based modelling step. Sources that most significantly contribute to the field measured at the surface of the Earth are modelled. Their separation is based on strong prior information on their spatial and temporal behaviours. We obtain a time series of model distributions which display behaviours similar to those of recent models based on more classic approaches, particularly at large temporal and spatial scales. Interesting new features and periodicities are visible in our models at smaller time and spatial scales. An important aspect of our method is to yield reliable error bars for all model parameters. These errors, however, are only as reliable as the description of the different sources and the prior information used are realistic. Finally, we used a slightly different version of our method to produce candidate models for the thirteenth edition of the International Geomagnetic Reference Field. KW - geomagnetic field KW - secular variation KW - Kalman filter KW - IGRF Y1 - 2020 U6 - https://doi.org/10.1186/s40623-020-01230-1 SN - 1880-5981 VL - 72 IS - 1 PB - Springer CY - New York ER - TY - JOUR A1 - Schanner, Maximilian Arthus A1 - Mauerberger, Stefan A1 - Korte, Monika A1 - Holschneider, Matthias T1 - Correlation based time evolution of the archeomagnetic field JF - Journal of geophysical research : JGR ; an international quarterly. B, Solid earth N2 - In a previous study, a new snapshot modeling concept for the archeomagnetic field was introduced (Mauerberger et al., 2020, ). By assuming a Gaussian process for the geomagnetic potential, a correlation-based algorithm was presented, which incorporates a closed-form spatial correlation function. This work extends the suggested modeling strategy to the temporal domain. A space-time correlation kernel is constructed from the tensor product of the closed-form spatial correlation kernel with a squared exponential kernel in time. Dating uncertainties are incorporated into the modeling concept using a noisy input Gaussian process. All but one modeling hyperparameters are marginalized, to reduce their influence on the outcome and to translate their variability to the posterior variance. The resulting distribution incorporates uncertainties related to dating, measurement and modeling process. Results from application to archeomagnetic data show less variation in the dipole than comparable models, but are in general agreement with previous findings. Y1 - 2021 U6 - https://doi.org/10.1029/2020JB021548 SN - 2169-9313 SN - 2169-9356 VL - 126 IS - 7 PB - American Geophysical Union CY - Washington ER - TY - JOUR A1 - Baerenzung, Julien A1 - Holschneider, Matthias A1 - Wicht, Johannes A1 - Lesur, Vincent A1 - Sanchez, Sabrina T1 - The Kalmag model as a candidate for IGRF-13 JF - Earth, planets and space N2 - We present a new model of the geomagnetic field spanning the last 20 years and called Kalmag. Deriving from the assimilation of CHAMP and Swarm vector field measurements, it separates the different contributions to the observable field through parameterized prior covariance matrices. To make the inverse problem numerically feasible, it has been sequentialized in time through the combination of a Kalman filter and a smoothing algorithm. The model provides reliable estimates of past, present and future mean fields and associated uncertainties. The version presented here is an update of our IGRF candidates; the amount of assimilated data has been doubled and the considered time window has been extended from [2000.5, 2019.74] to [2000.5, 2020.33]. KW - Geomagnetic field KW - Secular variation KW - Assimilation KW - Kalman filter KW - Machine learning Y1 - 2020 U6 - https://doi.org/10.1186/s40623-020-01295-y SN - 1880-5981 VL - 72 IS - 1 PB - Springer CY - New York ER - TY - JOUR A1 - Moldenhawer, Ted A1 - Moreno, Eduardo A1 - Schindler, Daniel A1 - Flemming, Sven A1 - Holschneider, Matthias A1 - Huisinga, Wilhelm A1 - Alonso, Sergio A1 - Beta, Carsten T1 - Spontaneous transitions between amoeboid and keratocyte-like modes of migration JF - Frontiers in Cell and Developmental Biology N2 - The motility of adherent eukaryotic cells is driven by the dynamics of the actin cytoskeleton. Despite the common force-generating actin machinery, different cell types often show diverse modes of locomotion that differ in their shape dynamics, speed, and persistence of motion. Recently, experiments in Dictyostelium discoideum have revealed that different motility modes can be induced in this model organism, depending on genetic modifications, developmental conditions, and synthetic changes of intracellular signaling. Here, we report experimental evidence that in a mutated D. discoideum cell line with increased Ras activity, switches between two distinct migratory modes, the amoeboid and fan-shaped type of locomotion, can even spontaneously occur within the same cell. We observed and characterized repeated and reversible switchings between the two modes of locomotion, suggesting that they are distinct behavioral traits that coexist within the same cell. We adapted an established phenomenological motility model that combines a reaction-diffusion system for the intracellular dynamics with a dynamic phase field to account for our experimental findings. KW - cell migration KW - amoeboid motility KW - keratocytle-like motility KW - modes of KW - migration KW - D. discoideum KW - actin dynamics Y1 - 2022 U6 - https://doi.org/10.3389/fcell.2022.898351 SN - 2296-634X VL - 10 PB - Frontiers Media CY - Lausanne ER - TY - JOUR A1 - Mauerberger, Stefan A1 - Schanner, Maximilian Arthus A1 - Korte, Monika A1 - Holschneider, Matthias T1 - Correlation based snapshot models of the archeomagnetic field JF - Geophysical journal international N2 - For the time stationary global geomagnetic field, a new modelling concept is presented. A Bayesian non-parametric approach provides realistic location dependent uncertainty estimates. Modelling related variabilities are dealt with systematically by making little subjective apriori assumptions. Rather than parametrizing the model by Gauss coefficients, a functional analytic approach is applied. The geomagnetic potential is assumed a Gaussian process to describe a distribution over functions. Apriori correlations are given by an explicit kernel function with non-informative dipole contribution. A refined modelling strategy is proposed that accommodates non-linearities of archeomagnetic observables: First, a rough field estimate is obtained considering only sites that provide full field vector records. Subsequently, this estimate supports the linearization that incorporates the remaining incomplete records. The comparison of results for the archeomagnetic field over the past 1000 yr is in general agreement with previous models while improved model uncertainty estimates are provided. KW - geopotential theory KW - archaeomagnetism KW - magnetic field variations through KW - time KW - palaeomagnetism KW - inverse theory KW - statistical methods Y1 - 2020 U6 - https://doi.org/10.1093/gji/ggaa336 SN - 0956-540X SN - 1365-246X VL - 223 IS - 1 SP - 648 EP - 665 PB - Oxford Univ. Press CY - Oxford ER - TY - JOUR A1 - Schindler, Daniel A1 - Moldenhawer, Ted A1 - Stange, Maike A1 - Lepro, Valentino A1 - Beta, Carsten A1 - Holschneider, Matthias A1 - Huisinga, Wilhelm T1 - Analysis of protrusion dynamics in amoeboid cell motility by means of regularized contour flows JF - PLoS Computational Biology : a new community journal N2 - Amoeboid cell motility is essential for a wide range of biological processes including wound healing, embryonic morphogenesis, and cancer metastasis. It relies on complex dynamical patterns of cell shape changes that pose long-standing challenges to mathematical modeling and raise a need for automated and reproducible approaches to extract quantitative morphological features from image sequences. Here, we introduce a theoretical framework and a computational method for obtaining smooth representations of the spatiotemporal contour dynamics from stacks of segmented microscopy images. Based on a Gaussian process regression we propose a one-parameter family of regularized contour flows that allows us to continuously track reference points (virtual markers) between successive cell contours. We use this approach to define a coordinate system on the moving cell boundary and to represent different local geometric quantities in this frame of reference. In particular, we introduce the local marker dispersion as a measure to identify localized membrane expansions and provide a fully automated way to extract the properties of such expansions, including their area and growth time. The methods are available as an open-source software package called AmoePy, a Python-based toolbox for analyzing amoeboid cell motility (based on time-lapse microscopy data), including a graphical user interface and detailed documentation. Due to the mathematical rigor of our framework, we envision it to be of use for the development of novel cell motility models. We mainly use experimental data of the social amoeba Dictyostelium discoideum to illustrate and validate our approach.
Author summary Amoeboid motion is a crawling-like cell migration that plays an important key role in multiple biological processes such as wound healing and cancer metastasis. This type of cell motility results from expanding and simultaneously contracting parts of the cell membrane. From fluorescence images, we obtain a sequence of points, representing the cell membrane, for each time step. By using regression analysis on these sequences, we derive smooth representations, so-called contours, of the membrane. Since the number of measurements is discrete and often limited, the question is raised of how to link consecutive contours with each other. In this work, we present a novel mathematical framework in which these links are described by regularized flows allowing a certain degree of concentration or stretching of neighboring reference points on the same contour. This stretching rate, the so-called local dispersion, is used to identify expansions and contractions of the cell membrane providing a fully automated way of extracting properties of these cell shape changes. We applied our methods to time-lapse microscopy data of the social amoeba Dictyostelium discoideum. Y1 - 2021 U6 - https://doi.org/10.1371/journal.pcbi.1009268 SN - 1553-734X SN - 1553-7358 VL - 17 IS - 8 PB - PLoS CY - San Fransisco ER - TY - JOUR A1 - Berner, Nadine A1 - Trauth, Martin H. A1 - Holschneider, Matthias T1 - Bayesian inference about Plio-Pleistocene climate transitions in Africa JF - Quaternary science reviews : the international multidisciplinary research and review journal N2 - During the last 5 Ma the Earth's ocean-atmosphere system passed through several major transitions, many of which are discussed as possible triggers for human evolution. A classic in this context is the possible influence of the closure of the Panama Strait, the intensification of Northern Hemisphere Glaciation, a stepwise increase in aridity in Africa, and the first appearance of the genus Homo about 2.5 - 2.7 Ma ago. Apart from the fact that the correlation between these events does not necessarily imply causality, many attempts to establish a relationship between climate and evolution fail due to the challenge of precisely localizing an a priori unknown number of changes potentially underlying complex climate records. The kernel-based Bayesian inference approach applied here allows inferring the location, generic shape, and temporal scale of multiple transitions in established records of Plio-Pleistocene African climate. By defining a transparent probabilistic analysis strategy, we are able to identify conjoint changes occurring across the investigated terrigenous dust records from Ocean Drilling Programme (ODP) sites in the Atlantic Ocean (ODP 659), Arabian (ODP 721/722) and Mediterranean Sea (ODP 967). The study indicates a two-step transition in the African climate proxy records at (2.35-2.10) Ma and (1.70 - 1.50) Ma, that may be associated with the reorganization of the Hadley-Walker Circulation. . KW - Plio-Pleistocene KW - Hadley-Walker Circulation KW - climate transition KW - Bayesian inference KW - time series analysis KW - ODP 659 KW - ODP 721/722 KW - ODP 967 Y1 - 2022 U6 - https://doi.org/10.1016/j.quascirev.2021.107287 SN - 0277-3791 SN - 1873-457X VL - 277 PB - Elsevier CY - Oxford ER - TY - JOUR A1 - Sharma, Shubham A1 - Hainzl, Sebastian A1 - Zöller, Gert A1 - Holschneider, Matthias T1 - Is Coulomb stress the best choice for aftershock forecasting? JF - Journal of geophysical research : Solid earth N2 - The Coulomb failure stress (CFS) criterion is the most commonly used method for predicting spatial distributions of aftershocks following large earthquakes. However, large uncertainties are always associated with the calculation of Coulomb stress change. The uncertainties mainly arise due to nonunique slip inversions and unknown receiver faults; especially for the latter, results are highly dependent on the choice of the assumed receiver mechanism. Based on binary tests (aftershocks yes/no), recent studies suggest that alternative stress quantities, a distance-slip probabilistic model as well as deep neural network (DNN) approaches, all are superior to CFS with predefined receiver mechanism. To challenge this conclusion, which might have large implications, we use 289 slip inversions from SRCMOD database to calculate more realistic CFS values for a layered half-space and variable receiver mechanisms. We also analyze the effect of the magnitude cutoff, grid size variation, and aftershock duration to verify the use of receiver operating characteristic (ROC) analysis for the ranking of stress metrics. The observations suggest that introducing a layered half-space does not improve the stress maps and ROC curves. However, results significantly improve for larger aftershocks and shorter time periods but without changing the ranking. We also go beyond binary testing and apply alternative statistics to test the ability to estimate aftershock numbers, which confirm that simple stress metrics perform better than the classic Coulomb failure stress calculations and are also better than the distance-slip probabilistic model. Y1 - 2020 U6 - https://doi.org/10.1029/2020JB019553 SN - 2169-9313 SN - 2169-9356 VL - 125 IS - 9 PB - American Geophysical Union CY - Washington ER - TY - JOUR A1 - Cotronei, Mariantonia A1 - Di Salvo, Rosa A1 - Holschneider, Matthias A1 - Puccio, Luigia T1 - Interpolation in reproducing kernel Hilbert spaces based on random subdivision schemes JF - Journal of computational and applied mathematics N2 - In this paper we present a Bayesian framework for interpolating data in a reproducing kernel Hilbert space associated with a random subdivision scheme, where not only approximations of the values of a function at some missing points can be obtained, but also uncertainty estimates for such predicted values. This random scheme generalizes the usual subdivision by taking into account, at each level, some uncertainty given in terms of suitably scaled noise sequences of i.i.d. Gaussian random variables with zero mean and given variance, and generating, in the limit, a Gaussian process whose correlation structure is characterized and used for computing realizations of the conditional posterior distribution. The hierarchical nature of the procedure may be exploited to reduce the computational cost compared to standard techniques in the case where many prediction points need to be considered. KW - Subdivision schemes KW - Interpolation KW - Simulation of Gaussian processes KW - Bayesian inversion Y1 - 2016 U6 - https://doi.org/10.1016/j.cam.2016.08.002 SN - 0377-0427 SN - 1879-1778 VL - 311 SP - 342 EP - 353 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Salamat, Mona A1 - Zare, Mehdi A1 - Holschneider, Matthias A1 - Zöller, Gert T1 - Calculation of Confidence Intervals for the Maximum Magnitude of Earthquakes in Different Seismotectonic Zones of Iran JF - Pure and applied geophysics N2 - The problem of estimating the maximum possible earthquake magnitude m(max) has attracted growing attention in recent years. Due to sparse data, the role of uncertainties becomes crucial. In this work, we determine the uncertainties related to the maximum magnitude in terms of confidence intervals. Using an earthquake catalog of Iran, m(max) is estimated for different predefined levels of confidence in six seismotectonic zones. Assuming the doubly truncated Gutenberg-Richter distribution as a statistical model for earthquake magnitudes, confidence intervals for the maximum possible magnitude of earthquakes are calculated in each zone. While the lower limit of the confidence interval is the magnitude of the maximum observed event, the upper limit is calculated from the catalog and the statistical model. For this aim, we use the original catalog which no declustering methods applied on as well as a declustered version of the catalog. Based on the study by Holschneider et al. (Bull Seismol Soc Am 101(4): 1649-1659, 2011), the confidence interval for m(max) is frequently unbounded, especially if high levels of confidence are required. In this case, no information is gained from the data. Therefore, we elaborate for which settings finite confidence levels are obtained. In this work, Iran is divided into six seismotectonic zones, namely Alborz, Azerbaijan, Zagros, Makran, Kopet Dagh, Central Iran. Although calculations of the confidence interval in Central Iran and Zagros seismotectonic zones are relatively acceptable for meaningful levels of confidence, results in Kopet Dagh, Alborz, Azerbaijan and Makran are not that much promising. The results indicate that estimating mmax from an earthquake catalog for reasonable levels of confidence alone is almost impossible. KW - Maximum magnitude of earthquake KW - Level of confidence KW - Confidence interval Y1 - 2016 U6 - https://doi.org/10.1007/s00024-016-1418-5 SN - 0033-4553 SN - 1420-9136 VL - 174 SP - 763 EP - 777 PB - Springer CY - Basel ER - TY - GEN A1 - Lühr, Hermann A1 - Wicht, Johannes A1 - Gilder, Stuart A. A1 - Holschneider, Matthias T1 - Preface T2 - Magnetic Fields in the Solar System: Planets, Moons and Solar Wind Interactions Y1 - 2018 SN - 978-3-319-64292-5 SN - 978-3-319-64291-8 SN - 0067-0057 VL - 448 SP - V EP - VI PB - Springer CY - Dordrecht ER - TY - GEN A1 - Lühr, Hermann A1 - Wicht, Johannes A1 - Gilder, Stuart A. A1 - Holschneider, Matthias T1 - General Introduction and Scientific Summary of the German Priority Program "PlanetMag" T2 - Magnetic Fields in the Solar System N2 - This book aims at understanding the diversity of planetary and lunar magnetic fields and their interaction with the solar wind. A synergistic interdisciplinary approach combines newly developed tools for data acquisition and analysis, computer simulations of planetary interiors and dynamos, models of solar wind interaction, measurement of terrestrial rocks and meteorites, and laboratory investigations. The following chapters represent a selection of some of the scientific findings derived by the 22 projects within the DFG Priority Program Planetary Magnetism" (PlanetMag). This introductory chapter gives an overview of the individual following chapters, highlighting their role in the overall goals of the PlanetMag framework. The diversity of the different contributions reflects the wide range of magnetic phenomena in our solar system. From the program we have excluded magnetism of the sun, which is an independent broad research discipline, but include the interaction of the solar wind with planets and moons. Within the subsequent 13 chapters of this book, the authors review the field centered on their research topic within PlanetMag. Here we shortly introduce the content of all the subsequent chapters and outline the context in which they should be seen. Y1 - 2018 SN - 978-3-319-64292-5 SN - 978-3-319-64291-8 U6 - https://doi.org/10.1007/978-3-319-64292-5_1 SN - 0067-0057 VL - 448 SP - 1 EP - 6 PB - Springer CY - Dordrecht ER - TY - JOUR A1 - Prokhorov, Boris E. A1 - Förster, Matthias A1 - Lesur, Vincent A1 - Namgaladze, Alexander A. A1 - Holschneider, Matthias A1 - Stolle, Claudia T1 - Modeling of the ionospheric current system and calculating its JF - Magnetic Fields in the Solar System: Planets, Moons and Solar Wind Interactions N2 - The additional magnetic field produced by the ionospheric current system is a part of the Earth’s magnetic field. This current system is a highly variable part of a global electric circuit. The solar wind and interplanetary magnetic field (IMF) interaction with the Earth’s magnetosphere is the external driver for the global electric circuit in the ionosphere. The energy is transferred via the field-aligned currents (FACs) to the Earth’s ionosphere. The interactions between the neutral and charged particles in the ionosphere lead to the so-called thermospheric neutral wind dynamo which represents the second important driver for the global current system. Both processes are components of the magnetosphere–ionosphere–thermosphere (MIT) system, which depends on solar and geomagnetic conditions, and have significant seasonal and UT variations. The modeling of the global dynamic Earth’s ionospheric current system is the first aim of this investigation. For our study, we use the Potsdam version of the Upper Atmosphere Model (UAM-P). The UAM is a first-principle, time-dependent, and fully self-consistent numerical global model. The model includes the thermosphere, ionosphere, plasmasphere, and inner magnetosphere as well as the electrodynamics of the coupled MIT system for the altitudinal range from 80 (60) km up to the 15 Earth radii. The UAM-P differs from the UAM by a new electric field block. For this study, the lower latitudinal and equatorial electrodynamics of the UAM-P model was improved. The calculation of the ionospheric current system’s contribution to the Earth’s magnetic field is the second aim of this study. We present the method, which allows computing the additional magnetic field inside and outside the current layer as generated by the space current density distribution using the Biot-Savart law. Additionally, we perform a comparison of the additional magnetic field calculation using 2D (equivalent currents) and 3D current distribution. Y1 - 2018 SN - 978-3-319-64292-5 SN - 978-3-319-64291-8 U6 - https://doi.org/10.1007/978-3-319-64292-5_10 SN - 0067-0057 SN - 2214-7985 VL - 448 SP - 263 EP - 292 PB - Springer CY - Dordrecht ER - TY - JOUR A1 - Lesur, Vincent A1 - Wardinski, Ingo A1 - Bärenzung, Julien A1 - Holschneider, Matthias T1 - On the frequency spectra of the core magnetic field Gauss coefficients JF - Physics of the earth and planetary interiors N2 - From monthly mean observatory data spanning 1957-2014, geomagnetic field secular variation values were calculated by annual differences. Estimates of the spherical harmonic Gauss coefficients of the core field secular variation were then derived by applying a correlation based modelling. Finally, a Fourier transform was applied to the time series of the Gauss coefficients. This process led to reliable temporal spectra of the Gauss coefficients up to spherical harmonic degree 5 or 6, and down to periods as short as 1 or 2 years depending on the coefficient. We observed that a k(-2) slope, where k is the frequency, is an acceptable approximation for these spectra, with possibly an exception for the dipole field. The monthly estimates of the core field secular variation at the observatory sites also show that large and rapid variations of the latter happen. This is an indication that geomagnetic jerks are frequent phenomena and that significant secular variation signals at short time scales - i.e. less than 2 years, could still be extracted from data to reveal an unexplored part of the core dynamics. KW - Geomagnetism KW - Core field KW - Secular variation rate of change KW - Geomagnetic jerks KW - Correlation based modelling Y1 - 2017 U6 - https://doi.org/10.1016/j.pepi.2017.05.017 SN - 0031-9201 SN - 1872-7395 VL - 276 SP - 145 EP - 158 PB - Elsevier CY - Amsterdam ER - TY - GEN A1 - Zöller, Gert A1 - Holschneider, Matthias T1 - Reply to “Comment on ‘The Maximum Possible and the Maximum Expected Earthquake Magnitude for Production‐Induced Earthquakes at the Gas Field in Groningen, The Netherlands’ by Gert Zöller and Matthias Holschneider” by Mathias Raschke T2 - Bulletin of the Seismological Society of America Y1 - 2018 U6 - https://doi.org/10.1785/0120170131 SN - 0037-1106 SN - 1943-3573 VL - 108 IS - 2 SP - 1029 EP - 1030 PB - Seismological Society of America CY - Albany ER - TY - JOUR A1 - Fiedler, Bernhard A1 - Zöller, Gert A1 - Holschneider, Matthias A1 - Hainzl, Sebastian T1 - Multiple Change-Point Detection in Spatiotemporal Seismicity Data JF - Bulletin of the Seismological Society of America N2 - Earthquake rates are driven by tectonic stress buildup, earthquake-induced stress changes, and transient aseismic processes. Although the origin of the first two sources is known, transient aseismic processes are more difficult to detect. However, the knowledge of the associated changes of the earthquake activity is of great interest, because it might help identify natural aseismic deformation patterns such as slow-slip events, as well as the occurrence of induced seismicity related to human activities. For this goal, we develop a Bayesian approach to identify change-points in seismicity data automatically. Using the Bayes factor, we select a suitable model, estimate possible change-points, and we additionally use a likelihood ratio test to calculate the significance of the change of the intensity. The approach is extended to spatiotemporal data to detect the area in which the changes occur. The method is first applied to synthetic data showing its capability to detect real change-points. Finally, we apply this approach to observational data from Oklahoma and observe statistical significant changes of seismicity in space and time. Y1 - 2018 U6 - https://doi.org/10.1785/0120170236 SN - 0037-1106 SN - 1943-3573 VL - 108 IS - 3A SP - 1147 EP - 1159 PB - Seismological Society of America CY - Albany ER - TY - JOUR A1 - Bärenzung, Julien A1 - Holschneider, Matthias A1 - Wicht, Johannes A1 - Sanchez, Sabrina A1 - Lesur, Vincent T1 - Modeling and predicting the short-term evolution of the geomagnetic field JF - Journal of geophysical research : Solid earth N2 - We propose a reduced dynamical system describing the coupled evolution of fluid flow and magnetic field at the top of the Earth's core between the years 1900 and 2014. The flow evolution is modeled with a first-order autoregressive process, while the magnetic field obeys the classical frozen flux equation. An ensemble Kalman filter algorithm serves to constrain the dynamics with the geomagnetic field and its secular variation given by the COV-OBS.x1 model. Using a large ensemble with 40,000 members provides meaningful statistics including reliable error estimates. The model highlights two distinct flow scales. Slowly varying large-scale elements include the already documented eccentric gyre. Localized short-lived structures include distinctly ageostophic features like the high-latitude polar jet on the Northern Hemisphere. Comparisons with independent observations of the length-of-day variations not only validate the flow estimates but also suggest an acceleration of the geostrophic flows over the last century. Hindcasting tests show that our model outperforms simpler predictions bases (linear extrapolation and stationary flow). The predictability limit, of about 2,000 years for the magnetic dipole component, is mostly determined by the random fast varying dynamics of the flow and much less by the geomagnetic data quality or lack of small-scale information. KW - core flow KW - assimilation KW - prediction KW - length of day Y1 - 2018 U6 - https://doi.org/10.1029/2017JB015115 SN - 2169-9313 SN - 2169-9356 VL - 123 IS - 6 SP - 4539 EP - 4560 PB - American Geophysical Union CY - Washington ER - TY - JOUR A1 - Fiedler, Bernhard A1 - Hainzl, Sebastian A1 - Zöller, Gert A1 - Holschneider, Matthias T1 - Detection of Gutenberg-Richter b-Value Changes in Earthquake Time Series JF - Bulletin of the Seismological Society of America N2 - The Gutenberg-Richter relation for earthquake magnitudes is the most famous empirical law in seismology. It states that the frequency of earthquake magnitudes follows an exponential distribution; this has been found to be a robust feature of seismicity above the completeness magnitude, and it is independent of whether global, regional, or local seismicity is analyzed. However, the exponent b of the distribution varies significantly in space and time, which is important for process understanding and seismic hazard assessment; this is particularly true because of the fact that the Gutenberg-Richter b-value acts as a proxy for the stress state and quantifies the ratio of large-to-small earthquakes. In our work, we focus on the automatic detection of statistically significant temporal changes of the b-value in seismicity data. In our approach, we use Bayes factors for model selection and estimate multiple change-points of the frequency-magnitude distribution in time. The method is first applied to synthetic data, showing its capability to detect change-points as function of the size of the sample and the b-value contrast. Finally, we apply this approach to examples of observational data sets for which b-value changes have previously been stated. Our analysis of foreshock and after-shock sequences related to mainshocks, as well as earthquake swarms, shows that only a portion of the b-value changes is statistically significant. Y1 - 2018 U6 - https://doi.org/10.1785/0120180091 SN - 0037-1106 SN - 1943-3573 VL - 108 IS - 5A SP - 2778 EP - 2787 PB - Seismological Society of America CY - Albany ER -