In the frame of the European Commission project "Seismic Hazard Harmonization in Europe" (SHARE), aiming at harmonizing seismic hazard at a European scale, the compilation of a homogeneous, European parametric earthquake catalogue was planned. The goal was to be achieved by considering the most updated historical dataset and assessing homogenous magnitudes, with support from several institutions. This paper describes the SHARE European Earthquake Catalogue (SHEEC), which covers the time window 1000-1899. It strongly relies on the experience of the European Commission project "Network of Research Infrastructures for European Seismology" (NERIES), a module of which was dedicated to create the European "Archive of Historical Earthquake Data" (AHEAD) and to establish methodologies to homogenously derive earthquake parameters from macroseismic data. AHEAD has supplied the final earthquake list, obtained after sorting J Seismol (2013) duplications out and eliminating many fake events; in addition, it supplied the most updated historical dataset. Macroseismic data points (MDPs) provided by AHEAD have been processed with updated, repeatable procedures, regionally calibrated against a set of recent, instrumental earthquakes, to obtain earthquake parameters. From the same data, a set of epicentral intensity-to-magnitude relations has been derived, with the aim of providing another set of homogeneous Mw estimates. Then, a strategy focussed on maximizing the homogeneity of the final epicentral location and Mw, has been adopted. Special care has been devoted also to supply location and Mw uncertainty. The paper focuses on the procedure adopted for the compilation of SHEEC and briefly comments on the achieved results.

International audienceA vital component of any seismic hazard analysis is a model for predicting the expected distribution of ground motions at a site due to possible earthquake scenarios. The limited nature of the datasets from which such models are derived gives rise to epistemic uncertainty in both the median estimates and the associated aleatory variability of these predictive equations. In order to capture this epistemic uncertainty in a seismic hazard analysis, more than one ground-motion prediction equation must be used, and the tool that is currently employed to combine multiple models is the logic tree. Candidate ground-motion models for a logic tree should be selected in order to obtain the smallest possible suite of equations that can capture the expected range of possible ground motions in the target region. This is achieved by starting from a comprehensive list of available equations and then applying criteria for rejecting those considered inappropriate in terms of quality, derivation or applicability. Once the final list of candidate models is established, adjustments must be applied to achieve parameter compatibility. Additional adjustments can also be applied to remove the effect of systematic differences between host and target regions. These procedures are applied to select and adjust ground-motion models for the analysis of seismic hazard at rock sites in West Central Europe. This region is chosen for illustrative purposes particularly because it highlights the issue of using ground-motion models derived from small magnitude earthquakes in the analysis of hazard due to much larger events. Some of the pitfalls of extrapolating ground-motion models from small to large magnitude earthquakes in low seismicity regions are discussed for the selected target region

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International audienceA key element in any seismic hazard analysis is the selection of appropriate ground-motion prediction equations (GMPEs). In an earlier paper, focused on the selection and adjustment of ground-motion models for probabilistic seismic hazard analysis (PSHA) in moderately active regions--with limited data and few, if any, indigenous models--Cotton et al. (2006) proposed seven criteria as the basis for selecting GMPEs. Recent experience in applying these criteria, faced with several new GMPEs developed since the Cotton et al. (2006) paper was published and a significantly larger strong-motion database, has led to consideration of how the criteria could be refined and of other conditions that could be included to meet the original objectives of Cotton et al. (2006). In fact, about a dozen new GMPEs are published each year, and this number appears to be increasing. Additionally, Cotton et al. (2006) concluded that the criteria should not be excessively specific, tied to the state-of-the-art in ground-motion modeling at the time of writing and thus remaining static, but rather should be sufficiently flexible to be adaptable to the continuing growth of the global strong-motion database and the continued evolution of GMPE

S U M M A R YBARENTS50, a new 3-D geophysical model of the crust in the Barents Sea Region has been developed by the University of Oslo, NORSAR and the U.S. Geological Survey. The target region comprises northern Norway and Finland, parts of the Kola Peninsula and the East European lowlands. Novaya Zemlya, the Kara Sea and Franz-Josef Land terminate the region to the east, while the Norwegian-Greenland Sea marks the western boundary. In total, 680 1-D seismic velocity profiles were compiled, mostly by sampling 2-D seismic velocity transects, from seismic refraction profiles. Seismic reflection data in the western Barents Sea were further used for density modelling and subsequent density-to-velocity conversion. Velocities from these profiles were binned into two sedimentary and three crystalline crustal layers. The first step of the compilation comprised the layer-wise interpolation of the velocities and thicknesses. Within the different geological provinces of the study region, linear relationships between the thickness of the sedimentary rocks and the thickness of the remaining crystalline crust are observed. We therefore, used the separately compiled (area-wide) sediment thickness data to adjust the total crystalline crustal thickness according to the total sedimentary thickness where no constraints from 1-D velocity profiles existed. The BARENTS50 model is based on an equidistant hexagonal grid with a node spacing of 50 km. The P-wave velocity model was used for gravity modelling to obtain 3-D density structure. A better fit to the observed gravity was achieved using a grid search algorithm which focussed on the density contrast of the sediment-basement interface. An improvement compared to older geophysical models is the high resolution of 50 km. Velocity transects through the 3-D model illustrate geological features of the European Arctic. The possible petrology of the crystalline basement in western and eastern Barents Sea is discussed on the basis of the observed seismic velocity structure. The BARENTS50 model is available at http://www.norsar.no/seismology/barents3d/.