ALBERT

Beschreibung: 〈span〉〈div〉ABSTRACT〈/div〉The task of downloading comprehensive datasets of event‐based seismic waveforms has been made easier through the development of standardized webservices but is still highly nontrivial because the likelihood of temporary network failures or subtle data errors naturally increases when the amount of requested data is in the order of millions of relatively short segments. This is even more challenging because the typical workflow is not restricted to a single massive download but consists of fetching all possible available input data (e.g., with several repeated download executions) for a processing stage producing any desired user‐defined output. Here, we present stream2segment, a highly customizable Python 2+3 package helping the user in the entire workflow of downloading, inspecting, and processing event‐based seismic data by means of a relational database management system as archiving storage, which has clear performance and usability advantages, and an integrated processing subroutine requiring a configuration file and a single Python function to produce user‐defined output. Stream2segment can also produce diagnostic maps or user‐defined plots, which, unlike existing tools, do not require external software dependencies and are not static images but instead are interactive browser‐based applications ideally suited for data inspection or annotation tasks and subsequent training of classifiers in foreseen supervised machine‐learning applications.Stream2segment has already been used as a data quality tool for datasets within the European Integrated Data Archive and to create a weak‐motion database (in the form of a so‐called flat file) for the stable continental region of Europe in the context of the European Ground Shaking Intensity Model service, in turn an important building block for seismic hazard studies.〈/span〉

Beschreibung: 〈span〉〈div〉SUMMARY〈/div〉We derive a harmonized local magnitude scale across Europe using data disseminated by network operators through the European Integrated Data Archive (EIDA). We first calibrate simultaneously a set of non-parametric attenuation functions regionalized by considering six different regions covering central and southern Europe, anchoring the models to the Richter’s scale at 17 km. Uncertainties on the attenuation coefficients, station corrections and magnitude values are evaluated through bootstrap analysis. The obtained attenuation functions show significant differences among the regions, up to 0.4 m.u. at 400 km, being the attenuation of the Wood–Anderson amplitude stronger for regions in the Mediterranean area. The non-parametric attenuation functions capture the changes in the rate of attenuation with distance due to the effects of later arrivals generated by crustal heterogeneity. A second calibration is performed to derive a parametric attenuation model. We consider a piece-wise linear function to describe the attenuation with the logarithm of distance, introducing two breakpoint distances at 10 and 60 km. For distances above 10 km, we also consider the anelastic attenuation term. We apply a mixed effect regression with network-dependent random effects on the anelastic coefficients. The parametric analysis confirms the stronger attenuation for networks operating in the Mediterranean area, such as the Italian and Greek networks, with respect to networks located in continental Europe. The network-dependent random effects allow us to quantify the between-network variability for different networks operating in the same region or country. The observed between-network variability is within ±0.2 m.u., smaller than the variability among the six regions.〈/span〉

Beschreibung: 〈span〉〈div〉Summary〈/div〉We derive a harmonized local magnitude scale across Europe using data disseminated by network operators through the European Integrated Data Archive (EIDA). We first calibrate simultaneously a set of non-parametric attenuation functions regionalized by considering six different regions covering central and southern Europe, anchoring the models to the Richter’s scale at 17 km. Uncertainties on the attenuation coefficients, station corrections and magnitude values are evaluated through bootstrap analysis. The obtained attenuation functions show significant differences among the regions, up to 0.4 m.u. at 400 km, being the attenuation of the Wood-Anderson amplitude stronger for regions in the Mediterranean area. The non-parametric attenuation functions capture the changes in the rate of attenuation with distance due to the effects of later arrivals generated by crustal heterogeneity. A second calibration is performed to derive a parametric attenuation model. We consider a piece-wise linear function to describe the attenuation with the logarithm of distance, introducing two breakpoint distances at 10 and 60 km. For distances above 10km, we also consider the anelastic attenuation term. We apply a mixed effect regression with network-dependent random effects on the anelastic coefficients. The parametric analysis confirms the stronger attenuation for networks operating in the Mediterranean area, such as the Italian and Greek networks, with respect to networks located in continental Europe. The network-dependent random effects allow us to quantify the between-network variability for different networks operating in the same region or country. The observed between-network variability is within ±0.2 m.u., smaller than the variability among the six regions.〈/span〉

Beschreibung: 〈span〉〈div〉ABSTRACT〈/div〉The task of downloading comprehensive datasets of event‐based seismic waveforms has been made easier through the development of standardized webservices but is still highly nontrivial because the likelihood of temporary network failures or subtle data errors naturally increases when the amount of requested data is in the order of millions of relatively short segments. This is even more challenging because the typical workflow is not restricted to a single massive download but consists of fetching all possible available input data (e.g., with several repeated download executions) for a processing stage producing any desired user‐defined output. Here, we present stream2segment, a highly customizable Python 2+3 package helping the user in the entire workflow of downloading, inspecting, and processing event‐based seismic data by means of a relational database management system as archiving storage, which has clear performance and usability advantages, and an integrated processing subroutine requiring a configuration file and a single Python function to produce user‐defined output. Stream2segment can also produce diagnostic maps or user‐defined plots, which, unlike existing tools, do not require external software dependencies and are not static images but instead are interactive browser‐based applications ideally suited for data inspection or annotation tasks and subsequent training of classifiers in foreseen supervised machine‐learning applications.Stream2segment has already been used as a data quality tool for datasets within the European Integrated Data Archive and to create a weak‐motion database (in the form of a so‐called flat file) for the stable continental region of Europe in the context of the European Ground Shaking Intensity Model service, in turn an important building block for seismic hazard studies.〈/span〉