Torfajökull is the largest silicic volcanic centre in Iceland lying at the intersection of the rift zone (MidAtlantic Ridge) and the transform zone that connects to Reykjanes peninsula. It erupts infrequently,with only two eruptions in the last 1200 years, the latest of which was over 5 centuries ago. Yet, itsactive tectonic setting, persistent high and low frequency seismicity, deformation and geothermalactivity within its large caldera (18x12 km diameter) indicate the continued presence of a long-lasting magma chamber. Here we speculate on possible geometry, size and depth of the Torfajökullmagma chamber by using radar interferometry (InSAR) and seismic interferometry (SI).Using InSAR time series analysis we detect a surface subsidence pattern at rates of up to ~13 mm yr-1in the SW region of Torfajökull ́s caldera, on-going since at least 1993. The subsidence rate isconstant in time, and perhaps due to a cooling magma chamber. The data can be fit reasonably wellusing a model of a NE-SW oriented spheroidal body at ~5 km depth. As the deflating area correlatesspatially with the area of geothermal activity, deflation may also be the surface response due to anactive hydrothermal circulation.To gain more insight into the geometry of Torfajökull’s magmatic system and rock properties of thesubsurface, we apply ambient noise seismic interferometry (SI) by cross-correlation of ambient noise.With this technique we can detect velocity variations, which can correspond to the edges of dikes ormolten magma bodies. Our tomographic results give reliable results of velocity variations within adepth range of 2 km to 7.5 km. We find high velocity zones that we interpret as old dike intrusions.Low velocity anomalies (>5%), which usually indicate the presence of warmer material, are locatedon the southeast and southwest part of the volcano, outside the volcano caldera.Finally we compare both InSAR and SI results. The hypothesis of a magma chamber under thesubsidence area detected by InSAR does not seem to fit the tomographic results, as the expectededges of a magma body modelled by InSAR are not clearly identified by the SI results. If there is anestablished magma chamber within Torfajökull caldera this is likely to be bellow 7km depth.@en

Tomographic studies based on passive seismic measurements have proven to be a powerful tool to image the subsurface. This especially holds in areas like Iceland, where the microseism coverage arriving from the ocean is excellent. In this study, we apply Ambient Noise Seismic Interferometry (ANSI) to generate a tomographic image of Rayleigh-waves velocity anomalies to further invert for S-wave anomalies at two Icelandic locations. We derive a tomographic image over Reykjanes Peninsula geothermal system using 30 Broad-Band (BB) stations deployed under the IMAGE (Integrated Methods for Advanced Geothermal Exploration) project framework and operated for approximately one year and a half. In the other case study, we derive a tomographic image of Torfajökull volcano using 23 BB seismometers that recorded ambient noise for 100 days. The later data were acquired in 2005 by Cambridge University. We retrieve the surface-wave part of the Green’s functions by cross-correlation between station pairs and consecutive stacking of the cross-correlations to obtain coherent ballistic surface waves (BSW). We pick the arrival times of the BSW, which are the input for the tomographic analysis. Both datasets show remarkably high signal-to-noise ratio of surface-wave arrivals between 0.1 and 0.5 Hz, even with only 100 days of recorded ambient noise. A beamforming analysis indicates a broad azimuthal coverage with persistent ambient noise arrivals within three azimuthal quadrants - between 90 and 360 degrees. The highly coherent surface-wave retrieval and the wide azimuthal coverage of the microseisms explain the success of ANSI techniques in Iceland. For the tomographic inversion, we use a Tikhonov and a statistical regularisation to invert the ballistic surface-wave time-arrival to 3D frequency-dependent velocity variations. After further inversion to S-wave velocity variations, we detect low- and high-velocity anomalies with changes between -15% and 15% from an estimated average velocity, we interpret these anomalies as possible old dyke intrusions and heat sources.@en

Tomographic studies based on passive seismic measurements have proven to be a powerful tool to image the subsurface. This especially holds in areas like Iceland, where the microseism coverage arriving from the ocean is excellent. In this study, we apply Ambient Noise Seismic Interferometry (ANSI) to generate a tomographic image of Rayleigh-waves velocity anomalies to further invert for S-wave anomalies at two Icelandic locations. We derive a tomographic image over Reykjanes Peninsula geothermal system using 30 Broad-Band (BB) stations deployed under the IMAGE (Integrated Methods for Advanced Geothermal Exploration) project framework and operated for approximately one year and a half. In the other case study, we derive a tomographic image of Torfajökull volcano using 23 BB seismometers that recorded ambient noise for 100 days. The later data were acquired in 2005 by Cambridge University. We retrieve the surface-wave part of the Green’s functions by cross-correlation between station pairs and consecutive stacking of the cross-correlations to obtain coherent ballistic surface waves (BSW). We pick the arrival times of the BSW, which are the input for the tomographic analysis. Both datasets show remarkably high signal-to-noise ratio of surface-wave arrivals between 0.1 and 0.5 Hz, even with only 100 days of recorded ambient noise. A beamforming analysis indicates a broad azimuthal coverage with persistent ambient noise arrivals within three azimuthal quadrants - between 90 and 360 degrees. The highly coherent surface-wave retrieval and the wide azimuthal coverage of the microseisms explain the success of ANSI techniques in Iceland. For the tomographic inversion, we use a Tikhonov and a statistical regularisation to invert the ballistic surface-wave time-arrival to 3D frequency-dependent velocity variations. After further inversion to S-wave velocity variations, we detect low- and high-velocity anomalies with changes between -15% and 15% from an estimated average velocity, we interpret these anomalies as possible old dyke intrusions and heat sources.@en

Tomographic studies based on passive seismic measurements have proven to be a powerful tool to image the subsurface. This especially holds in areas like Iceland, where the microseism coverage arriving from the ocean is excellent. In this study, we apply Ambient Noise Seismic Interferometry (ANSI) to generate a tomographic image of Rayleigh-waves velocity anomalies to further invert for S-wave anomalies at two Icelandic locations. We derive a tomographic image over Reykjanes Peninsula geothermal system using 30 Broad-Band (BB) stations deployed under the IMAGE (Integrated Methods for Advanced Geothermal Exploration) project framework and operated for approximately one year and a half. In the other case study, we derive a tomographic image of Torfajökull volcano using 23 BB seismometers that recorded ambient noise for 100 days. The later data were acquired in 2005 by Cambridge University. We retrieve the surface-wave part of the Green’s functions by cross-correlation between station pairs and consecutive stacking of the cross-correlations to obtain coherent ballistic surface waves (BSW). We pick the arrival times of the BSW, which are the input for the tomographic analysis. Both datasets show remarkably high signal-to-noise ratio of surface-wave arrivals between 0.1 and 0.5 Hz, even with only 100 days of recorded ambient noise. A beamforming analysis indicates a broad azimuthal coverage with persistent ambient noise arrivals within three azimuthal quadrants - between 90 and 360 degrees. The highly coherent surface-wave retrieval and the wide azimuthal coverage of the microseisms explain the success of ANSI techniques in Iceland. For the tomographic inversion, we use a Tikhonov and a statistical regularisation to invert the ballistic surface-wave time-arrival to 3D frequency-dependent velocity variations. After further inversion to S-wave velocity variations, we detect low- and high-velocity anomalies with changes between -15% and 15% from an estimated average velocity, we interpret these anomalies as possible old dyke intrusions and heat sources.@en

Tomographic studies based on passive seismic measurements have proven to be a powerful tool to image the subsurface. This especially holds in areas like Iceland, where the microseism coverage arriving from the ocean is excellent. In this study, we apply Ambient Noise Seismic Interferometry (ANSI) to generate a tomographic image of Rayleigh-waves velocity anomalies to further invert for S-wave anomalies at two Icelandic locations. We derive a tomographic image over Reykjanes Peninsula geothermal system using 30 Broad-Band (BB) stations deployed under the IMAGE (Integrated Methods for Advanced Geothermal Exploration) project framework and operated for approximately one year and a half. In the other case study, we derive a tomographic image of Torfajökull volcano using 23 BB seismometers that recorded ambient noise for 100 days. The later data were acquired in 2005 by Cambridge University. We retrieve the surface-wave part of the Green’s functions by cross-correlation between station pairs and consecutive stacking of the cross-correlations to obtain coherent ballistic surface waves (BSW). We pick the arrival times of the BSW, which are the input for the tomographic analysis. Both datasets show remarkably high signal-to-noise ratio of surface-wave arrivals between 0.1 and 0.5 Hz, even with only 100 days of recorded ambient noise. A beamforming analysis indicates a broad azimuthal coverage with persistent ambient noise arrivals within three azimuthal quadrants - between 90 and 360 degrees. The highly coherent surface-wave retrieval and the wide azimuthal coverage of the microseisms explain the success of ANSI techniques in Iceland. For the tomographic inversion, we use a Tikhonov and a statistical regularisation to invert the ballistic surface-wave time-arrival to 3D frequency-dependent velocity variations. After further inversion to S-wave velocity variations, we detect low- and high-velocity anomalies with changes between -15% and 15% from an estimated average velocity, we interpret these anomalies as possible old dyke intrusions and heat sources.@en