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SN-CAST: seismic network capability assessment software tool for regional networks-examples from Ireland

  • Martin MöllhoffEmail author
  • Christopher J. Bean
  • Brian J. Baptie
Original Article

Abstract

Event detection capability plays an important role in the operation of seismic observatories and temporary networks. The magnitude threshold for the detection of seismic events with a given network geometry is frequently derived from the observed magnitude of completeness. However, the latter might be unknown for regions that have not been monitored previously or where the observed seismicity rate is low. We present the open-source Python program SN-CAST with which the geographical distribution of event detection capability can be calculated as a function of station coordinates and station ambient noise amplitudes. The method employs the local magnitude scale, and hence is mainly applicable to regional networks with an aperture of less than about 1000 km. The attenuation characteristics of the study region need to be derived independently or be known a priori. SN-CAST can easily be employed to determine network performance in quasi real-time if station data streams are available. It can also be used for designing the geometry of new networks or assessing the effect of adding or removing stations from an existing network. We present examples from the Irish National Seismic Network (https://www.insn.ie), which operates in a region of low seismicity and large variations in ocean and wind-generated seismic noise. The seismicity in Ireland is too low to allow the calculation of a magnitude of completeness for comparison with the derived capability maps. However, the maps are in good agreement with the location and magnitude of detected local and regional earthquakes demonstrating that SN-CAST is a reliable tool for assessing the detection capability of seismic networks.

Keywords

Seismic network Event Detection Magnitude Performance Noise 

Notes

Acknowledgements

We thank the INSN analysts for their contribution to the generation of the INSN seismic event catalog. We acknowledge the provision of real-time data access to seismic stations from the British Geological Survey (BGS) and the Atomic Weapons Establishment (AWE) Blacknest in the UK. The operation of the INSN was supported by iCRAG in the years 2015–2016 and is supported since November 2017 by the Geological Survey Ireland. The authors are grateful for the constructive review from an anonymous reviewer.

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Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  1. 1.Geophysics Section, Dublin Institute for Advanced StudiesSchool of Cosmic PhysicsDublin 2Ireland
  2. 2.British Geological Survey, The Lyell CentreResearch Avenue SouthEdinburghScotland

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