@article{ZoellerHolschneider2014,
  author    = {Z{\"o}ller, Gert and Holschneider, Matthias},
  title     = {Induced seismicity: What is the size of the largest expected earthquake?},
  series = {The bulletin of the Seismological Society of America},
  volume    = {104},
  journal   = {The bulletin of the Seismological Society of America},
  number    = {6},
  publisher = {Seismological Society of America},
  address   = {Albany},
  issn      = {0037-1106},
  doi       = {10.1785/0120140195},
  pages     = {3153 -- 3158},
  year      = {2014},
  abstract  = {The injection of fluids is a well-known origin for the triggering of earthquake sequences. The growing number of projects related to enhanced geothermal systems, fracking, and others has led to the question, which maximum earthquake magnitude can be expected as a consequence of fluid injection? This question is addressed from the perspective of statistical analysis. Using basic empirical laws of earthquake statistics, we estimate the magnitude M-T of the maximum expected earthquake in a predefined future time window T-f. A case study of the fluid injection site at Paradox Valley, Colorado, demonstrates that the magnitude m 4.3 of the largest observed earthquake on 27 May 2000 lies very well within the expectation from past seismicity without adjusting any parameters. Vice versa, for a given maximum tolerable earthquake at an injection site, we can constrain the corresponding amount of injected fluids that must not be exceeded within predefined confidence bounds.},
  language  = {en}
}
@article{ShebalinNarteauZecharetal.2014,
  author    = {Shebalin, Peter N. and Narteau, Clement and Zechar, Jeremy Douglas and Holschneider, Matthias},
  title     = {Combining earthquake forecasts using differential probability gains},
  series = {Earth, planets and space},
  volume    = {66},
  journal   = {Earth, planets and space},
  publisher = {Springer},
  address   = {Heidelberg},
  issn      = {1880-5981},
  doi       = {10.1186/1880-5981-66-37},
  pages     = {14},
  year      = {2014},
  abstract  = {We describe an iterative method to combine seismicity forecasts. With this method, we produce the next generation of a starting forecast by incorporating predictive skill from one or more input forecasts. For a single iteration, we use the differential probability gain of an input forecast relative to the starting forecast. At each point in space and time, the rate in the next-generation forecast is the product of the starting rate and the local differential probability gain. The main advantage of this method is that it can produce high forecast rates using all types of numerical forecast models, even those that are not rate-based. Naturally, a limitation of this method is that the input forecast must have some information not already contained in the starting forecast. We illustrate this method using the Every Earthquake a Precursor According to Scale (EEPAS) and Early Aftershocks Statistics (EAST) models, which are currently being evaluated at the US testing center of the Collaboratory for the Study of Earthquake Predictability. During a testing period from July 2009 to December 2011 (with 19 target earthquakes), the combined model we produce has better predictive performance - in terms of Molchan diagrams and likelihood - than the starting model (EEPAS) and the input model (EAST). Many of the target earthquakes occur in regions where the combined model has high forecast rates. Most importantly, the rates in these regions are substantially higher than if we had simply averaged the models.},
  language  = {en}
}
@article{HolschneiderZoellerClementsetal.2014,
  author    = {Holschneider, Matthias and Z{\"o}ller, Gert and Clements, R. and Schorlemmer, Danijel},
  title     = {Can we test for the maximum possible earthquake magnitude?},
  series = {Journal of geophysical research : Solid earth},
  volume    = {119},
  journal   = {Journal of geophysical research : Solid earth},
  number    = {3},
  publisher = {American Geophysical Union},
  address   = {Washington},
  issn      = {2169-9313},
  doi       = {10.1002/2013JB010319},
  pages     = {2019 -- 2028},
  year      = {2014},
  language  = {en}
}
@article{BaerenzungHolschneiderLesur2014,
  author    = {Baerenzung, Julien and Holschneider, Matthias and Lesur, Vincent},
  title     = {Bayesian inversion for the filtered flow at the Earth's core-mantle boundary},
  series = {Journal of geophysical research : Solid earth},
  volume    = {119},
  journal   = {Journal of geophysical research : Solid earth},
  number    = {4},
  publisher = {American Geophysical Union},
  address   = {Washington},
  issn      = {2169-9313},
  doi       = {10.1002/2013JB010358},
  pages     = {2695 -- 2720},
  year      = {2014},
  abstract  = {The inverse problem of determining the flow at the Earth's core-mantle boundary according to an outer core magnetic field and secular variation model has been investigated through a Bayesian formalism. To circumvent the issue arising from the truncated nature of the available fields, we combined two modeling methods. In the first step, we applied a filter on the magnetic field to isolate its large scales by reducing the energy contained in its small scales, we then derived the dynamical equation, referred as filtered frozen flux equation, describing the spatiotemporal evolution of the filtered part of the field. In the second step, we proposed a statistical parametrization of the filtered magnetic field in order to account for both its remaining unresolved scales and its large-scale uncertainties. These two modeling techniques were then included in the Bayesian formulation of the inverse problem. To explore the complex posterior distribution of the velocity field resulting from this development, we numerically implemented an algorithm based on Markov chain Monte Carlo methods. After evaluating our approach on synthetic data and comparing it to previously introduced methods, we applied it to a magnetic field model derived from satellite data for the single epoch 2005.0. We could confirm the existence of specific features already observed in previous studies. In particular, we retrieved the planetary scale eccentric gyre characteristic of flow evaluated under the compressible quasi-geostrophy assumption although this hypothesis was not considered in our study. In addition, through the sampling of the velocity field posterior distribution, we could evaluate the reliability, at any spatial location and at any scale, of the flow we calculated. The flow uncertainties we determined are nevertheless conditioned by the choice of the prior constraints we applied to the velocity field.},
  language  = {en}
}