Jökull


Jökull - 01.01.2010, Side 51

Jökull - 01.01.2010, Side 51
Upptyppingar seismic swarms brittle-ductile boundary of 15–18 km, along a pre- sumed dyke that dipped at 50◦. Deep seismic activity attributed to melt movement is also observed beneath active volcanic centres in Ice- land, as well as elsewhere in the world such as Mt. Ki- lauea (Wright and Klein, 2006) and Japan (Hasegawa et al., 1991), but the hypocentres typically assume conduit-like as opposed to planar distributions. Near Mt. Upptyppingar, hundreds of lower crustal earthquakes have been observed beneath Askja vol- cano since the ASN began monitoring the area in 2005 (Soosalu et al., 2010). The seismicity outlines three separate vertical conduit structures that extend from c. 10 km down to the crust-mantle boundary. The most recent eruption at Askja volcano occurred in 1961. Mt. Eyjafjallajökull in southwest Iceland also ex- hibited deep seismicity in the mid-1990s that ex- tended from the crust-mantle boundary through to the surface (Hjaltadóttir et al., 2009). Seismic activ- ity persisted at shallower depths with sporadic deep events for over a decade, eventually leading to an eruption in 2010 that halted European air traffic for several days (Sigmundsson et al., 2010; Hjaltadóttir et al., 2009; Pedersen and Sigmundsson, 2004, 2006). GPS and InSAR modelling of surface deformation at Mt. Upptyppingar in 2007–2008 constrain the vol- ume of injected melt to be ∼0.040–0.047 km3, corre- sponding to the inflation of a ∼0.1–1 m thick, south- ward dipping dyke at depths of 10–18 km (Hooper et al., 2009). For comparison, the inferred volume of the pre-eruptive melt intrusion beneath Eyjafjalla- jökull was of the same magnitude (Sigmundsson et al., 2010). Seismicity that clearly defines a planar structure, as observed beneath Mt. Upptyppingar, presents an ideal opportunity to evaluate the effects of different processing techniques, network size and geometries, and phase picking accuracy by comparing hypocen- tral location precision. This form of analysis has been applied successfully in previous studies that, for ex- ample, demonstrate the benefits of relative relocation techniques (Waldhauser and Ellsworth, 2000; Slunga et al., 1995). The precision of seismic hypocentre locations af- fects how the seismicity is interpreted. Outstanding questions in crustal formation, such as the extent of host rock deformation caused by an active dyke in- trusion in visco-elastic crust, require extremely high hypocentral precision. ASN PROCESSING TECHNIQUES Data selection is primarily limited by the deploy- ment dates of the ASN (i.e., 6 July–22 August 2007). Within this date range, we further restrict our study period to 6–24 July, during which the most inten- sive and dynamic bursts of seismic activity occurred, including several earthquakes that exceeded Ml 2.0 and seismic propagation rates that reached as high as 0.05 m s−1. Moreover, signal to noise ratios were higher on average during this period than in late July and August. The study period comprises 547 events that are drawn from a SIL catalogue of over 9000 earthquakes observed beneath Mt. Upptypping- ar during 2007–2008. We then manually filtered the 547 events based on signal-to-noise ratio by inspect- ing waveforms for clarity of phase onsets. The final dataset consists of 288 high-quality events. Processing of seismic data from the ASN is per- formed in multiple steps. Firstly, events are lo- cated using the Coalescence Microseismic Mapping (CMM) software developed by Drew (2010). The SIL event catalogue is provided as input to CMM, which searches the continuously recorded data for phase on- sets near each catalogue event time through a Short Term Average to Long Term Average ratio (STA/LTA) (Drew et al., 2005). For a given search volume of dis- crete grid spacing and a specified velocity model, a look-up table is produced by forward-modelling travel times from each grid node to each receiver. The look-up table is then used to migrate seismic energy from both P-wave (vertical component) and S-wave (horizontal components) onsets at each station into the subsurface. Finally, a coalescence function is used to determine the subsurface location at which the seismic energy is focussed, yielding spatial and temporal information about the imaged seismic event. Any mis-identified onsets (e.g., from noise bursts) are smeared out over the migrated volume and thus do not contribute to the final CMM locations. Here we have used a grid spacing of 300 m; however, by virtue of JÖKULL No. 60 51
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