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Calving event detection by observation of seiche effects on the
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Greenland fjords
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Fabian Walter1,2
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Marco Olivieri3
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John F. Clinton1
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1Swiss
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2Laboratory
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Seismological Service, ETH Zürich, Switzerland
3Istituto
of Hydraulics, Hydrology and Glaciology, ETH Zürich, Switzerland
Nazionale di Geofisica e Vulcanologia, Bologna, Italy
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ABSTRACT
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With mass loss from the Greenland ice sheet accelerating and spreading to higher latitudes,
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the quantification of mass discharge in the form of icebergs has recently received much
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scientific attention. Here, we make use of very low frequency (0.001-0.01 Hz) seismic data
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from three permanent broadband stations installed in the summers of 2009/2010 in
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northwest Greenland in order to monitor local calving activity. At these frequencies, calving
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seismograms are dominated by a tilt signal produced by local ground flexure in response to
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fjord seiching generated by major iceberg calving events. A simple triggering algorithm is
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proposed to detect calving events from large calving fronts with potentially no user
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interaction. The calving catalogue we derive identifies spatial and temporal differences in
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calving activity between Jakobshavn Isbræ and glaciers in the Uummannaq district some 200
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km further north. The Uummannaq glaciers show clear seasonal fluctuations in seiche-based
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calving detections as well as seiche amplitudes. In contrast, the detections at Jakobshavn
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Isbræ show little seasonal variation, which may be evidence for an ongoing transition into
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winter calving activity. The results offer further evidence that seismometers can provide
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efficient and inexpensive monitoring of calving fronts.
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INTRODUCTION
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In recent years, the accelerating mass loss of the Greenland ice sheet has raised global sea
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level by 0.67 mm/a (Spada and others, 2012). It is equally divided between negative surface
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mass balance and dynamic discharge to the ocean also known as ‘dynamic mass loss’ (e. g.
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Rignot and others, 2008; van den Broeke and others, 2009; Rignot and others, 2011; Khan and
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others, 2010). Discharge occurs mainly through outlet glaciers, whose flow velocities often
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exceed 3 km/a (e. g. Joughin and others, 2010). The dynamic mass loss component has
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recently received much attention as major outlet glaciers throughout Greenland started
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accelerating in the early 2000’s. Although this phenomenon initiated at the more southerly
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outlet glaciers, it now affects outlet glaciers at all latitudes (e. g. Rignot and Kanagaratnam,
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2006; Pritchard and others, 2009).
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At the termini of Greenland’s outlet glaciers, mass discharge occurs mainly through iceberg
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calving, although at least in some regions submarine melting may be responsible for similar
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amounts of mass loss (Rignot and others, 2010). In an effort to understand and quantify
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Greenland’s recent mass loss, iceberg calving has become the focus of vigorous glaciological
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investigation. GPS measurements (Amundson and others, 2008; Nettles and others, 2008)
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and theoretical studies (Thomas and others, 2004; Lüthi and others, 2009; Nick and others,
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2009) show that outlet glaciers can accelerate in response to large calving events,
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consequently calving processes may also have a direct effect on ice sheet stability. Indeed,
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there exists strong evidence that despite significant regional variability (Moon and others,
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2012), much of the recent episodic discharge increase in Greenland was triggered at calving
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fronts when fjord waters underwent transient warming (Holland and others, 2008; Murray
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and others, 2010, Rignot et al., 2012).
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Despite its important role in glacier and ice sheet mass balance, iceberg calving is still poorly
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understood. It remains a considerable challenge to incorporate the relevant boundary
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conditions, such as water and air temperatures, proglacial water depth, strain rates near the
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calving front, and fracture state of the terminus, into a ‘universal calving law’ (Alley and
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others, 2004; Benn and others, 2007; Amundson and Truffer, 2010; Bassis and others, 2010).
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One obstacle facing iceberg calving studies is the lack of supporting data. Satellite images
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detect and quantify calving events at limited temporal and spatial resolution (e. g. Joughin et.
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al, 2008). Direct visual observations using time-lapse cameras can provide impressively
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complete catalogues of calving events (e. g. Köhler and others, 2011; O’Neel and others,
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2007). However, these observations often come at high costs, are prone to subjective
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judgement of the observer, are limited to the seasons with daylight, and provide only rough
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estimates of calving volumes.
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Seismic monitoring of iceberg calving activity is an attractive alternative to direct
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observations, as large calving events in Greenland can generate energy across a broad
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frequency range (e. g. Amundson et al, 2008; Amundson et al., 2012a). Using seismic signals
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to monitor calving activity at various scales has been previously documented. Initial studies
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using sensors with limited frequency bands focused on high-frequency components (> 1 Hz)
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of regional calving seismograms (e. g. Qamar, 1988). More recently, several workers
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associated such high-frequency signals with narrow-band character (1-5 Hz) with various
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englacial fracture mechanisms that are active during calving events (e. g. O’Neel and Pfeffer,
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2007; Amundson and others, 2008; Richardson and others, 2010).
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The deployment of broadband seismometers has facilitated the observation of the broadband
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nature of signals produced by calving events. ‘Glacial earthquakes’ (Ekström and others,
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2003; Tsai and Ekström, 2007; Joughin and others, 2008; Larmat and others, 2008; Nettles
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and others, 2008; Nettles and Ekström, 2010) are generated by major calving events. They
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are identifiable on global seismic networks via detection of low-frequency (35-150 s) surface
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waves generated during iceberg detachment. Recent work on records at both teleseimic and
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local distances indicates the source mechanism of these events are most likely collision forces
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between detaching icebergs and the glacier terminus or fjord bottom (Amundson and others,
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2008; Tsai and others, 2008; Nettles and Ekström, 2010; Walter and others, 2012). The
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glacial earthquakes detected at teleseimic distances have a surface wave amplitudes
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equivalent to ~M5 tectonic earthquakes. Most glacial earthquakes are generated during
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calving events in Greenland, however Antarctic events have also been confirmed (Nettles and
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Ekström, 2010; Chen and others, 2011). Seasonal and secular changes in glacial earthquake
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detections have been associated with changes in dynamics of Greenland outlet glaciers
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(Ekström and others, 2006; Joughin and others, 2006).
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Despite these promising results, there remain open questions about the completeness of
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calving catalogues generated by glacial earthquake detection, particularly since only some
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classes of calving events appear to generate significant low-frequency surface wave energy.
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Specifically, Nettles and Ekström (2010) suggested that only capsizing icebergs appear to
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generate observable low-frequency surface wave energy, whereas tabular, non-capsizing
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icebergs can calve ‘quietly’. Similarly, they note that relatively few glacial earthquakes can be
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attributed to floating ice tongues, which suggests that coupling of the terminus to the solid
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earth is essential for surface wave generation. Consequently, the glacial earthquake catalogue
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may not reflect the full extent of seasonal variations in calving activity, because large, tabular
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and smaller capsizing icebergs typically can calve at different times of the year (Amundson
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and others, 2010). Furthermore, the single-force source conventionally used to model glacial
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earthquakes (e. g. Ekström et al., 2003; Tsai and Ekström, 2007) provides an amplitude,
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whose relationship with iceberg volume is not fully understood (Amundson et al., 2012b;
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Walter and others, 2012). Correspondingly, the upper limit for glacial earthquake size
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indicated by surface wave magnitudes (Nettles and Ekström, 2010) may not only be the result
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of a limit of glacier calving volume.
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Normal modes of proglacial fjord waters, which are excited as icebergs detach from glacier
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termini, are another type of calving-generated signal. The low-frequency (<0.01 Hz) signals
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from such ‘seiches’ can be recorded by seismometers in response to major calving events at
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Jakobshavn Isbræ, one of Greenland’s largest ice streams (Amundson and others, 2012a). In
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other closed and semi-closed water bodies, such as lakes (e. g. Forel, 1904) and harbours (e. g.
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Miles, 1974) seiches are commonly induced by winds. Seiche triggering through earthquakes
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(Kvale, 1955; Ichinose and others, 2000), landslides (Bondevik, 2005) and ship traffic
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(McNamara and others, 2011) has also been reported.
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In the present paper we show that, using data from three broadband stations in Greenland,
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long-period seismograms in the vicinity of resonating fjords can effectively be used to detect
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seiches and hence act as an automatic calving detector. We corroborate our detections using
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local tide gauge records, time-lapse photographs, satellite images, and the teleseismic glacial
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earthquake catalogue (Veitch and Nettles, in press). We further analyze our derived catalogue
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to discuss calving activity of remote Greenlandic glaciers, whose dynamics are difficult to
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study with in-situ field techniques.
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SEISMIC AND FJORD PRESSURE DATA
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The Greenland Ice Sheet Monitoring Network (GLISN; http://glisn.info/; Dahl-Jensen and others,
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2010, Husen and others, 2010) is a recent broadband seismic infrastructure in and around
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Greenland (Figure 1). GLISN is a joint collaboration with USA, Denmark, Switzerland,
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Germany, Canada, Italy, Japan, Norway, Poland and France. The purpose of this network is to
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enhance the capability of the pre-existing Greenland seismic infrastructure for detecting,
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locating, and characterizing both tectonic and glacial earthquakes, together with other cryo-
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seismic phenomena. As glacial earthquake activity has been shown to exhibit seasonal and
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secular fluctuations likely caused by changes in full-thickness iceberg calving rate (Ekström
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and others, 2006), by improving the detection of these events, the GLISN data can provide
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powerful monitoring of glaciological processes. All data from GLISN are freely and openly
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available through various institutes, including the ORFEUS Data Center (ODC) and the
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Incorporated Research Institutions for Seismology (IRIS). GLISN stations are almost uniformly
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equipped with Streckeisen STS-2 seismometers (flat response between 0.00833 and 50 Hz)
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and Quanterra Q330 digitizers. Except for on-ice and extremely remote stations, data are
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acquired and distributed in real-time.
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The present study uses regional seismic broadband recordings of calving events in
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northwestern Greenland. We use data from three stations (KULLO, NUUG and ILULI, Figure
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1), which were installed near the shoreline in the vicinity of major calving glaciers. Since their
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installation the instruments have been operating continuously with only minor interruptions.
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For each of the three stations, this has resulted in a data return above 99 % with only around
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20 data gaps per year.
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Associated with this project, off-line pressure sensors were temporarily installed in the fjords
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close to the stations ILULI and NUUG. The sensor specifications and operational periods are
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shown in Table 1. The pressure data effectively measures water level above the sensor. The
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fjord water pressure sensors directly measure the fjord seiches at the site, whereas
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seismometers respond to ground tilt induced by the changing fjord water heights in the
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vicinity of the station. Seismometer response to tilt induced by water waves has been
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documented in a variety of previous cases, including seiche signals induced by ship traffic in
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the Panama Canal (McNamara and others, 2011) and tsunamis (Okal, 2007). A tilt signal on a
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seismometer is characterized by significantly larger signals on the horizontal components
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compared to the vertical (Wielandt and Forbriger, 1999).
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STUDY SITES ON GREENLAND’S NORTHWEST COAST
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Installed in the town of Ilulissat in July 2009, the broadband station ILULI is located
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approximately 60 km from the calving front of Jakobshavn Isbræ (Figure 1), one of
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Greenland’s largest and fastest flowing outlet glaciers draining about 7 % of the entire ice
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sheet (Bindschadler, 1984). Following about 50 years of stability (Sohn and others, 1998), the
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glacier began a rapid retreat in 1998, losing its 15 km floating tongue (Luckman and Murray,
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2005). The retreat was accompanied by thinning rates as high as 15 m/a (Thomas and
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others, 2003; Krabill and others, 2004) and the flow rate near the terminus accelerated from
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about 6,000 m/a in 1997 to 12,000 m/a in 2003 (Joughin and others, 2004). The glacier has
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maintained its high velocities with calving front positions fluctuating seasonally on the order
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of 6 km (Joughin and others, 2008b). Until recently, the glacier formed a small floating tongue
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in winter as calving typically ceases. This temporary tongue disintegrates in early summer via
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calving of large tabular icebergs (Amundson and others, 2010), the typical calving style for the
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previously floating terminus. During the subsequent summer, iceberg discharge occurs
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mainly via calving of smaller, full-thickness icebergs, which capsize upon detachment
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(Amundson and others, 2010). Jakobshavn Isbræ is the only major calving front in the vicinity
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of ILULI and thus the only candidate front for the events we observe at this station. The ice
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debris cover in the fjord may be atypical: in recent years it has been present year-round,
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although its thickness and integrity change seasonally (Joughin and others, 2008b; Amundson
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and others, 2010). In contrast, Howat and others (2010) document the clearing of fjord
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debris cover for glaciers within 300 km north of Jakobshavn Isbræ. Amundson and others
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(2012a) demonstrate that calving events at Jakobshavn Isbræ produce seiche signals that are
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visible on station ILULI (Figure 1). Up to 6 glacial earthquakes in a single year have been
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located at this calving front (Veitch and Nettles, in press).
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The broadband station NUUG is located just outside the small fishing community of
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Nuugaatsiaq in Greenland’s Uummannaq district. It was installed in July 2010 near glacier
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termini located within a system of fjords likely suitable for sustained seiches (Figure 1). The
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calving fronts of Ingia and Umiamako Isbræ underwent rapid retreats in 2003, increasing
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their flow speeds by 20 and 300 %, respectively (Howat and others, 2010). Umiamako Isbræ
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retreated by close to 4 km, constituting the largest retreat in this area (McFadden and others,
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2011; Howat and others, 2010). Between 2004 and 2008 it thinned by some 66 m.
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Concurrently, it underwent acceleration, which may continue into the future (McFadden and
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others, 2011). Kangerdlugssup semerssua has exhibited a stable calving front position
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although it doubled its speed between 2000 and 2005 and thinned by nearly 60 m in recent
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years (McFadden and others, 2011; Howat and others, 2010). During the same period, Rink
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Isbræ, showed little changes in terminus position and flow speed (Howat and others, 2010;
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Joughin and others, 2010). Around the turn of the century, the discharge of Rink Isbræ was 5
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times as large as Kangerdlugssup semerssua and about half as large as Jakobshavn Isbræ
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(Rignot and Kanagaratnam, 2006). It is therefore likely the dominant producer of icebergs in
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the Uummannaq district. This is also in agreement with glacial earthquake studies, which
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ascribe all detected events in this region (0-2 per year) to Rink Isbræ (Tsai and Ekström,
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2007; Nettles and Ekström, 2010; Veitch and Nettles, in press).
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Near the broadband station KULLO, located at the village of Kullorsuaq since July 2009, the
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Greenland ice sheet drains through large ice streams and wide calving margins (Figure 1).
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The ice streams calve directly into the open ocean with buttressing rock outcrops forming
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only few water-filled fjords. Compared to the region near NUUG this suggests fewer water
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basins suited for seiches. Ice sheet changes have been moderate over the past decade (Rignot
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and Kanagaratnam, 2006), except for Alison Gletscher (ca. 30 km from KULLO), which from
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around 2002 began an 8.7 km retreat and doubled the peak speeds (Moon and Joughin, 2008;
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Joughin and others, 2010; Howat and Eddy, 2011; McFadden and others, 2011). The glacier’s
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terminus and speed stabilized relatively quickly around 2007, arguably because of steep
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slopes reaching far inland (McFadden and others, 2011). As expected for a rapid retreat,
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Alison Gletscher has produced up to 4 glacial earthquakes a year between 2003 and 2008
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(Veitch and Nettles, in press). In contrast, Hayes Glacier (ca. 40 km from KULLO) experienced
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a minor slow down between the early and mid 2000’s with approximately constant mass
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balance (Rignot and Kanagaratnam, 2006). Since 2006, it has only produced one glacial
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earthquake (Veitch and Nettles, in press).
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EVENT CHARACTERIZATION
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Broadband calving seismograms recorded near-shore within 100 km of the source are
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characterized by a rich and distinctive wave train. Figure 2 demonstrates the different
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characters of typically observed signals at station NUUG. The shown records include a calving
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event from 23 August 2010, as recorded on the North-South component. For the shown
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calving event, as well as for many others in the data set, the North-South component most
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clearly exhibits the typical features of a calving seismogram. Satellite images from the nearby
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glaciers taken before and after this date confirm the occurrence of iceberg calving and are
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discussed later. The general character of calving seismogram in Figure 2 is representative of
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other calving events at the three seismic broadband stations ILULI, NUUG and KULLO. Figure
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2 also includes signals from a large teleseism (M7.6 Kermadec Islands, 6 July 2011), a regional
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earthquake (M=3.2, epicentre approximately 120 km North-West of station ILULI, about 200
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km away from NUUG ), and a sample of seismic noise.
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In panel A, all the records are shown without any processing or filtering. The calving event is
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characterized by a high-frequency onset followed by a nearly monochromatic long-period
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energy that resonates for many hours, and is absent from all other signal types. Panel B
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shows the same data, after integration and bandpass-filtering between 0.001 and 0.01 Hz.
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Additionally, data recorded on the nearly co-located water pressure gauge are plotted.
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Though large teleseisms also excite energy with similar amplitude in this frequency band, the
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duration is short compared to the several hours of resonance seen during the calving. As the
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frequency, phase, envelope amplitude and duration of the calving seismogram closely match
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the water pressure data, it is clear that the seismometer is responding to the seiche measured
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with the pressure gauge.
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In panel C, all the seismic data are presented using a bandpass filter that accentuates large-
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amplitude surface waves at low frequencies (0.02-0.05 Hz). All signals use the same scale,
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except the teleseism, which is scaled down by a factor of 250. Though the calving event does
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generate low-frequency surface waves (in this case 2 distinct peaks separated by 20 minutes
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which may be indicative of the detachment of several icebergs as documented in Walter and
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others, 2012), the amplitudes do not exceed the background noise by more than a factor of 5.
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In Panel D, the waveforms are bandpass filtered between 1 and 3 Hz to highlight the high
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frequency components of the signal. All the signals are on the same scale. The teleseism is at
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such great distance that the high frequency signal is barely perceptible, with similar
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amplitude to the noise. The calving event produces clear energy only during the second of the
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clear low-frequency surface wave energy transients. During calving, high frequency energy is
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generated during iceberg detachment as well as motion of ice debris in the fjord and typically
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lasts several minutes (O’Neel and others, 2007; Amundson and others, 2008; Walter and
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others, 2012). The high-frequency calving seismicity typically precedes the seiche signal by
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some 10’s of minutes (Amundson and others, 2012a). It tends to be emergent and cultural
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noise can often generate a stronger signal.
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The coincidence of the surface wave arrival (panel C) with a high-frequency seismicity burst is
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in agreement with the conceptual model that glacial earthquakes are generated by contact
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forces between detaching iceberg and an obstacle coupled to the solid earth, such as the fjord
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bottom or glacier terminus (e. g. Amundson et al, 2008; Tsai and others, 2008; Amundson and
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others, 2012a; Walter and others, 2012). However, there also exist examples when seismic
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surface wave generation and high-frequency fracture seismicity do not clearly coincide
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(Walter et al, 2012). For the example shown in Figure 2 this is the case for the first surface
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wave arrival. This may indicate that during a multiple-iceberg calving event, some icebergs
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detach and capsize more ‘freely’ with relatively little englacial fracturing or displacement of
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fjord debris cover.
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In the final panel E, the long period components of the signals are displayed in the frequency
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domain. The calving event is characterized by a number of narrow, distinct, resonating
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spectral peaks. The pressure gauge data also share several of these peaks, in particular the
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dominant resonance near 0.006 Hz. None of the other event types excite significant energy
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near this frequency. The seismic spectrum contains various additional low-frequency peaks,
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which are only weakly present in the fjord pressure data. This may be due to the nature of the
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sensor installation: near NUUG, the fjord system is complex (Figure 1). Depending on the
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specific glacier terminus, any single calving event may induce seiching with different
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resonating frequencies in nearby basin systems. Whereas the water pressure sensor is only
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sensitive to resonances in the local fjord, the seismic sensor can respond to seiching-induced
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tilts that occur in nearby basins with different resonance periods.
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Figure 2 demonstrates why we focus on identification of calving events using long period
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energy (<0.01 Hz) associated with seiching. Regional and teleseismic earthquakes and even
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seismic background noise can generate energy in all of the three frequency bands shown in
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Figure 2. However, the 0.001-0.01 Hz range is least contaminated by other signals – which
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include very low frequency surface waves from relatively rare major teleseismic events; local
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tilting from wind or cultural noise and instrument glitches such as mass re-centerings.
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Cultural noise and electronic instrument glitches, in particular, can produce false alarms for
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our automatic calving seiche detector at station KULLO, as discussed below. Nevertheless,
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these sources have a far shorter duration than seiche signals. Furthermore, in this frequency
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band, teleseismic events can be clearly distinguished from seiches by comparison between
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vertical and horizontal amplitudes: teleseisms have similar amplitudes between these
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components, but in the case of calving seiches, the sensor responds to minor tilts. In this case
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the vertical component has order of magnitude smaller amplitudes than the horizontal
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components (Pino, 2012). Accordingly, the seiche seismogram in Figure 2 has an H/V ratio of
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20, (using the North-South component). In contrast, the teleseismic surface waves typically
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have an H/V ratio of around 1.
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Although calving events generate seismic signals in each frequency band, the seiche signal
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consistently has the best signal-to-noise ratio. Indeed, for some calving events, surface wave
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and/or the high frequency energy does not emerge above the noise even at distances under
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100 km. Furthermore, these higher frequency bands are rich in frequently occurring
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transient signals produced by cultural noise and, in particular, earthquake sources. The 0.001-
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0.01 Hz passband therefore is suitable for automatic detection of iceberg calving events using
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the seiche approach.
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DETECTION ALGORITHM
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Our strategy for the automated detection of calving events is to target the seiche signals. In
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order to identify all transient energy signals at long periods, we apply a simple triggering
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detector to the band-passed continuous waveforms. Maximizing the completeness of this
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first-stage catalogue we use a conservative parameter set for the triggering algorithm.
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Specifically, the parameter set is chosen trigger on calving events, whose existence is known
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from first-hand observations at Jakobshavn Isbræ (Martin Lüthi, personal communication)
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and the glacial earthquake catalogue (Veitch and Nettles, in press). Our conservative
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parameter choice also produces a large number of false detections. We therefore discriminate
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seiching from other signals by setting a threshold for signal duration. This removes brief
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transients and all but the largest teleseisms. To remove these teleseismic signals, we also
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require events to have a minimum ratio between the peak amplitudes of the horizontal and
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vertical components. Noise, or indeed small calving events that are difficult to verify are
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finally removed by requiring events to reach minimum amplitudes for the characteristic
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spectral peaks. As calving events from different sources exhibit quite different characteristics
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– in particular, the seiche frequencies and durations vary according to the fjord geometry –
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the actual parameters of the algorithm are station dependent (Table 2).
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We implement the first stage of the calving seiche detector by applying an STA/LTA (short
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term average / long term average; Allen, 1978) algorithm on band-pass filtered raw data
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streams (Table 2). Although the seiche signal has largest amplitudes on the horizontal
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components, this detection is performed on the vertical, as it has substantially less long
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period noise and hence the highest signal to noise ratio (see Section ‘CHANGING SEISMIC
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BACKGROUND NOISE'). A preliminary detection is made when the STA/LTA envelope
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amplitude exceeds 2.3. In the second stage we only retain events where the STA/LTA trigger
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threshold is maintained for a station-specific time span (Table 2). In the final stage only
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events whose spectral amplitudes exceed a station-specific value are kept and which exhibit
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horizontal-to-vertical ratios (H/V) above 7. At least one of the horizontal components has to
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pass the H/V ratio criterion. These thresholds used for the frequency bands, event durations
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and spectral amplitude were selected using a trial-and-error approach to match a manually
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generated set of calving seiche signals: Inspecting the available continuous seismic record we
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made sure that our algorithm triggers on signals similar to those of known calving events
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(Martin Lüthi, personal communication; Veitch and Nettles, in press). This STA/LTA
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detection algorithm is implemented on Seiscomp3 (Hanka et al, 2010 http://www.nat-
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hazards-earth-syst-sci.net/10/2611/2010/nhess-10-2611-2010.html), and subsequent
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analyses of the preliminary detections are performed using Seismic Analysis Code (SAC,
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Goldstein and others, 2003).
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DETECTION VERIFICATION
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Visual calving event confirmation with first-hand observations (e. g., Köhler and others, 2011;
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O’Neel and others, 2007) or time-lapse photography (Amundson and others, 2008; Amundson
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and others, 2012a; Walter and others, 2012), is unrealistic for our 250 calving events, which
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occurred over more than two years in extremely remote terrain. Instead, we relied on
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pressure data in nearby fjords. However, these sensors were only installed near ILULI and
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NUUG (Table 1), and even for these data there are extended periods without measurements.
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Furthermore, a potential problem with pressure gauge data is that occasionally they may
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record seiches caused by mechanisms other than calving, such as freely rotating icebergs,
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landslides or weather-related events.
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Satellite images are an alternative for direct observations. They can be used to verify that our
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automatic seiche detections correspond to iceberg calving events. However, the spatial
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resolution of satellite images is limited. In addition, cloud-free image pairs are rarely taken
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immediately before and after a calving event, so the temporal resolution of satellite-based
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calving event detection cannot compete with seismic methods. In this study, we use an image
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library provided daily by the Danish Meteorological Institute
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(http://ocean.dmi.dk/arctic/modis.uk.php). It contains data from the ENVISAT satellite and
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its Advanced Synthetic Aperture Radar (ASAR), © European Space Agency. The images have
350
sufficient resolution (approximately 150 m) to identify major calving episodes and are
351
generally available at intervals of 10s of days or less. A systematic effort to create an
352
independent calving catalogue for each calving front by using satellite images to monitor
353
changes in terminus geometry could be used to estimate completeness of our calving
354
catalogue. Though this is beyond the scope of the present study, we demonstrate the potential
355
of satellite images for calving event confirmation in Figures 3 and 4. The shown events at
356
KULLO and NUUG do correspond to co-eval mass wastage at a calving front.
357
Figure 3 shows ASAR images of Alison Gletscher’s terminus near KULLO taken on 01-30-2011
358
and 02-02-2011 (see also Figure 1). A seiche was detected within this time window at KULLO
359
on 2011-01-30 at 10:53. The second shown image clearly shows a missing piece in the
360
terminus due to one or more calving events. The image pair furthermore highlights a change
361
in the proglacial mélange cover, which may be due to upwelling of fresh water from subglacial
362
discharge (plume, e. g. Motyka and others, 2003; Rignot and others, 2010) or local winds.
363
There exist ASAR images taken about 5 days before and 1.5 days after the calving seiche
364
detection at NUUG on 2010-08-23 at 03:20 (see also Figure 2) (Figure 4). On these images it
365
is more difficult to trace the terminus positions and to detect changes in terminus geometry.
366
There are changes in proglacial mélange cover at all shown calving fronts. However, as these
367
changes may be due to changes in fjord currents or wind patterns they carry little
368
significance. On the other hand, we note the appearance of several kilometre-long debris
369
covers in the fjords of Ingia Isbræ (I.I.) and Kangerdlugssup sermerssua (K. s.), which suggests
370
that substantial calving occurred around the detection time.
371
372
DETECTION STATISTICS
373
Figure 5 illustrates the statistics of our automatic detection time series in the form of
374
histograms with 1-month long bins. We furthermore created a manually reviewed catalogue
375
by visually inspecting all automatic detections as well as those rejected by the thresholds for
376
amplitude and horizontal-to-vertical ratio. Moreover, where possible, we visually confirmed
377
that the seiche signal was present in the fjord pressure sensor data. This manually reviewed
378
catalogue best represents the calving activity derived from our seiche detections. The manual
379
calving catalogues for each station are included in Table A1 in the Appendix. Significant
380
additional confidence in the manual catalogue was gained by visual inspection of the entire
381
two-year continuous seismic archive. We note that missed events can occur due to gaps in
382
data, which also produces a quiet zone with the length of the long term average in the
383
detector once the waveform flow returns. However, this occurs rarely, as the data return of
384
all three stations exceeds 99 %. Furthermore, data gap occurrence is not influenced by the
385
seasons and thus cannot mimic or mask seasonal fluctuations in seiche detection.
386
Figure 5 shows that the automatic catalogue can miss up to half a dozen events per month.
387
Furthermore, it can include an even greater number of false triggers. Figure 6 further
388
illustrates this point. Like Figure 5 it shows the automatic (green bars) and manual (yellow
389
bars) detections. In addition, it shows the portion of the automatic monthly detections, which
390
are false alarms and the portion of the manual monthly detections, which were missed by the
391
automatic trigger algorithm (grey portions of respective bars).
392
The problem of false detections is particularly severe for KULLO, which has over 50 monthly
393
false detections in the summer of 2011. In total, 79% of all KULLO detections were false,
394
while the automatic detector incorrectly rejected 18% of the manually confirmed events.
395
Visual inspection of the continuous waveforms shows that station KULLO generates a large
396
amount of long-duration long-period noise, which falsely triggers our detection algorithm.
397
Similar to data gaps (also more frequent in the KULLO record), such noise can furthermore
398
decrease the trigger sensitivity for several hours, potentially leading to missed calving
399
detections. We believe this noise occurs because though the sensor is located on rock, it is
400
underneath an occupied house near one of the 4 foundation piers. It may thus be susceptible
401
to local tilting induced by transient forces on foundation due to wind or house use.
402
In an attempt to reduce the high rate of false detections at KULLO, we varied the amplitude
403
and duration cut-off values (Table 2), but were not successful. On the other hand, the
404
performance of the automatic detector at ILULI and NUUG is more reliable, with 17% and 6%
405
of the manual detections missed respectively. Conversely, 29% and 33% of the automatic
406
detections for the respective stations were false.
407
408
COMPARISON WITH OTHER CATALOGUES
409
To further evaluate the performance of our calving detector we compare our automatic and
410
manual catalogues with the global glacial earthquake catalogue of Veitch and Nettles (in
411
press). Specifically, we focus on the detections of Veitch and Nettles (in press) in our three
412
candidate regions. This catalogue spans the years 2006 to 2010 and thus builds on earlier
413
glacial earthquake catalogues of Tsai and Ekström (2007). For the particular case of calving
414
events from Jakobshavn Isbræ, we also compare our catalogues with an updated version
415
(Amundson, personal communication) of the Amundson and others (2012a) catalogue.
416
Whereas the Veitch and Nettles (in press) catalogue also served as a guideline for the choice
417
of our detection parameters, the updated version of Amundson and others (2012a), was not
418
used in the development of our trigger algorithm. The Amundson catalogue documents the
419
calving history of Jakobshavn Isbræ between 1996 and 2011 and is based on a manual
420
analysis of local high-frequency seismicity, satellite imagery and where possible time-lapse
421
footage of Jakobshavn Isbræ’s terminus. For Jakobshavn Isbræ, this is presently the most
422
complete record of calving events. Requiring low-frequency surface wave energy recorded at
423
global distances, the trigger algorithm of Veitch and Nettles (in press) targets relatively large
424
calving events, only. However, it can potentially detect calving events at all major outlet
425
glaciers of Greenland.
426
Table A1 shows that the automatic seiche detector includes all but 1 of the 10 glacial
427
earthquake events (9 detections at Jakobshavn Isbræ and 1 detection at Rink Isbræ) detected
428
by Veitch and Nettles (in press). Our automatic and manual catalogues at ILULI are compared
429
with the updated catalogue of Amundson and others (2012a) in Figure 7. In the top panel, we
430
compare their catalogue with our automatic catalogue. The number of events occurring each
431
month detected by either catalogue varies from between 0 and 10 events. During most
432
months, there exist events that are detected by both catalogues, as well as events that are
433
detected only by one of the 2 methods. When we consider our manual catalogue (Figure 7,
434
bottom), the number of events only present in our seiche catalogue decreases while the
435
number events observed by both methods increases. This confirms 1) our manual catalogue
436
based on a visual inspection all STA/LTA triggers correctly eliminates a number of false
437
calving events in the automatic catalogue; and 2) in a small number of cases, a few events that
438
match the STA/LTA trigger criterion but are subsequently rejected are likely true events as
439
they also appear in the updated catalogue of Amundson and others (2012a). On the other
440
hand, some 30 calving events (the summation of green bars in Figure 7, bottom) in the
441
updated catalogue of Amundson and others (2012a) do not trigger the STA/LTA algorithm.
442
The reason is most likely that these calving events do not produce a seiche, which is strong
443
enough to be detected by our seismic sensor at ILULI.
444
The majority of events in the manual catalogue are also in the updated catalogue of
445
Amundson and others (2012a). Combining both catalogues, there are on average 4-5 events
446
at Jakobshavn Isbræ per month. Nevertheless, there are events (represented by red bars),
447
which produce seiches, but which are not included in the updated version of Amundson and
448
others (2012a). These are less straightforward to interpret. One reason may be that events in
449
the Amundson catalogue are required to have observable high-frequency seismic energy and
450
they have to be visible in satellite and/or time-lapse images. Furthermore, Amundson and
451
others (2012a) only consider calving events, which produce multiple icebergs as indicated by
452
more than one burst in high-frequency seismicity. Consequently, the seiche catalogue may in
453
fact identify previously unknown calving events that may be too small to be visually identified
454
or emit significant high-frequency energy. At the same time we cannot exclude the possibility
455
that at least occasionally our trigger algorithm may also detect seiches, which are unrelated to
456
calving events (e. g. freely capsizing icebergs, strong wind or landslides).
457
458
DISCUSSION
459
SEASONALITY IN CALVING ACTIVITY
460
Figure 5 shows that for NUUG and KULLO the maximum monthly number of manually
461
confirmed detections exceeds 10. Fewer events are detected at station ILULI. The reason
462
could be that the catalogue from station ILULI includes only calving events from Jakobshavn
463
Isbræ (Amundson and others, 2012a), whereas calving from several nearby glaciers may
464
trigger detections at NUUG and KULLO (Figure 1). However, it is also possible that calving at
465
Jakobshavn Isbræ is characterised by few, large events.
466
The stations have only been operational since summer 2009 for KULLO and ILULI, and
467
summer 2010 for NUUG. Hence our catalogue only spans 2 full years for 2 stations, and a
468
single year for NUUG. Nevertheless, our catalogue (Figure 5) suggests that for all three regions
469
there is no seasonal period during which calving ceases altogether. Specifically, for ILULI,
470
there are altogether only four months without manual detection. Even during winter we
471
typically observe several events each month. Previous studies indicated that calving ceased
472
completely at least during some winters following the retreat of Jakobshavn Isbræ, which
473
began in the early 1990’s (Amundson and others, 2010; Amundson and others, 2012a).
474
Indeed, up to summer 2010 the glacial earthquake catalogue from Veitch and Nettles (in
475
press) showed a clear seasonal oscillation with most events detected in June/July and no
476
events detected September thru January. Therefore, our seiche detection time series, which
477
spans more recent times, suggests that Jakobshavn Isbræ has begun to discharge icebergs
478
during winter months. This is in line with the findings of Podrasky and others (‘Outlet glacier
479
response to forcing over hourly to inter-annual time scales, Jakobshavn Isbræ, Greenland’,
480
submitted to the Journal of Glaciology) that the glacier underwent only a minor winter
481
advance during the winter of 2009/2010. Accordingly, the recent glacial earthquake
482
detection time series also shows detections at Jakobshavn Isbræ which occur extraordinarily
483
early in 2010 (Veitch and Nettles, in press). In addition, recent satellite observations have
484
also suggested such an initiation of winter calving. A possible explanation is that currently
485
warming fjord waters reduce the mélange’s ability to exert a backstress on the terminus
486
during winter (Cassotto and others, 2010; Fahnestock and others, 2010; Truffer and others,
487
2010).
488
Although the detection time series from NUUG (Figure 5) is the shortest it appears to exhibit
489
seasonal fluctuations in calving activity more clearly than the other stations. The glaciers
490
near NUUG all show a seasonal presence of mélange that begins to form in January and
491
February and tends to clear out in June. Due to the resulting changes in buttressing effect of
492
the mélange, this cycle correlates well with terminus advances and retreats (Howat and
493
others, 2010). We suggest such seasonality in calving front dynamics is also responsible for
494
the seasonal fluctuations in calving seiche detections at NUUG (Figure 5).
495
Similar to ILULI, the detection time series at KULLO shows little or no seasonality. However,
496
in view of the large number of misdetections one has to be careful not to over interpret this
497
observation. We tentatively suggest that a lack of seasonality in calving activity may be due to
498
the absence of buttressing from proglacial mélange. Figure 1 does indicate that ice debris
499
accumulates in front of glacier termini near KULLO. However, compared to the NUUG and
500
ILULI regions, fewer elongated fjords exist near KULLO. As a result, there may not be
501
sufficient confinement for proglacial mélange in order to significantly influence ice discharge.
502
503
CHANGES IN SIGNAL CHARACTERISTICS
504
The recordings at NUUG and KULLO show seasonal changes of seiche amplitudes calculated as
505
maximum amplitudes of seiche seismograms. This is most clearly seen on the east-west
506
component shown in Figure 8. At NUUG and KULLO seiche amplitudes tend to be highest
507
during late summer. Such an amplitude variation over time and seasons cannot be observed
508
in the corresponding low-frequency surface wave frequency band on the same component
509
(Figure 9).
510
At periods between 0.1 and 1 Hz, sea ice can substantially dampen ocean gravity waves in
511
Arctic and Antarctic waters (Tsai and McNamara, 2011; Grob and others, 2011). However,
512
recent observations (Bromirski and Stephen, 2012) of ice shelf response to infra gravity
513
waves only documents a minor damping effect of sea ice cover at lower frequencies (0.004-
514
0.02 Hz). The seiche signals observed at KULLO, NUUG and ILULI contain energy between
515
0.001 and 0.01 Hz, which suggests that the observed seasonality in seiche amplitudes cannot
516
be fully attributed to damping effects of sea ice. Instead, we suggest that seasonal changes in
517
seiche amplitudes are another effect of changes in mélange and sea ice cover. Laboratory
518
studies (Amundson and others, 2012b; Burton and others, 2012) as well as theoretical (Tsai
519
and others, 2008; Amundson and others, 2010) and observational studies (Walter and others,
520
2012) suggest that mélange cover in the fjord affects not only the detachment but also the
521
capsizing of icebergs by adding drag forces during the rotation. Accordingly, less rotational
522
energy may be converted into standing fjord waves when a thick sea ice or mélange cover is
523
present, resulting in lower seiche amplitudes.
524
The frequency content of seiche signals also exhibits considerable temporal variation, which
525
is particularly pronounced on the North-South components of NUUG (Figure 10). Here, a
526
strong spectral peak at 0.006 Hz is particularly interesting, as it is absent during the earlier
527
months of 2011 and immediately following the station installation. There are several
528
potential explanations for changing boundary conditions, which may give rise to the observed
529
variation in spectral character. First, individual spectral peaks may be characteristic for a
530
particular fjord basin (e. g. Lee, 1971). However, this cannot explain spectral changes of
531
records at ILULI, which we have argued is only sensitive to calving events from Jakobshavn
532
Isbræ. Furthermore, this line of reasoning would imply that near NUUG, different glaciers
533
calve during different times of the year, which seems unlikely for neighbouring glaciers. An
534
alternative explanation could be seasonal fluctuations in terminus positions. Although
535
terminus positions presently vary less than one kilometre in the NUUG region (Howat and
536
others, 2010), these fluctuations may be enough to subtly but measurably alter the resonance
537
frequencies of fjord water bodies. Finally, our preferred explanation for changing seiche
538
spectra is the variation in proglacial ice mélange cover combined with the seasonal presence
539
of sea ice. This is supported by recent numerical calculations (MacAyeal and others, 2012)
540
showing that the presence of closely spaced icebergs within a fjord introduces ‘band gaps’ in
541
normal oscillations of proglacial fjords. In addition, such closely spaced icebergs can lengthen
542
the periods of certain seiche modes by over 400 %.
543
544
CHANGING SEISMIC BACKGROUND NOISE
545
In order to understand whether our detection threshold was being influenced by variations in
546
seismic noise, we followed the method of Vila and others (2006). We measure seismic
547
background noise levels in the seiche (0.001-0.01 Hz) and low-frequency surface wave (0.02-
548
0.05 Hz) frequency range for the three stations over the entire available data-set. To estimate
549
the noise for each day (and to remove transient spikes from e.g. earthquakes), the average
550
amplitude of the band-passed velocity signal over a 3-hour time window is computed, and
551
then the minimum value for each day is selected. We can compare this noise measure with
552
the recorded peak seiche amplitudes. Figure 11 shows that in both frequency ranges, the
553
events detected by our method generally carry energy significantly above our measure of
554
background noise. Exceptions are the LHN components of NUUG and KULLO.
555
We acknowledge that most of the time, the calving events will not occur during the daytime
556
when the mean noise amplitude was chosen to represent the noise level. We can nevertheless
557
draw several specific conclusions from Figure 11: First, the noise level of the horizontal
558
components generally exceeds the noise on the vertical components by an order of
559
magnitude. Thus, calving seismograms on the vertical component, on which our STA/LTA
560
detector operates, have the best signal to noise ratio due to the low noise levels on these
561
components. Second, there exist noise variations on a seasonal time scale in both the seiche
562
and surface wave bands. On the other hand, the NUUG record shows that a peak in seiche
563
detections does not coincide with the annual minimum in background noise. The last point, in
564
particular indicates that the seasonality in seiche detections at NUUG (Figure 5) is not an
565
artefact of seasonal changes in background noise levels. Concerning the reason for seasonal
566
noise level variations we note that they are most evident on the horizontal components of
567
ILULI and KULLO and have a similar phase in both frequency ranges with noise minima and
568
maxima occurring in the first and second half of 2010, respectively. Though it is possible that
569
the noise is associated with external factors, we believe there may be a more simple
570
explanation. The seismometers at these two sites are placed under residential buildings,
571
whose occupation is subject to weather conditions as well as human habit.
572
573
COMPARISON WITH GLOBAL SURFACE WAVE DETECTOR
574
Our calving detection catalogue (manually confirmed detections) consists of 257 events. This
575
includes 9 out of the 10 events detected as glacial earthquakes by teleseismic surface wave
576
detection (9 detections at Jakobshavn Isbræ and 1 detection at Rink Isbræ; Veitch and Nettles,
577
in press) during the same time-period and within the same regions. The single missed event
578
occurred on Jakobshavn Isbræ on 2010-05-21; the seiche detector rejected the event because
579
the seiche duration of 300 s is well below the discrimination threshold (1200 s), and the
580
seiche amplitude is small.
581
The large discrepancy in number of teleseismic surface wave detections and local seiche
582
detections indicates that the second approach is significantly more sensitive. It should be
583
noted that observed glacial earthquakes in the Veitch and Nettles catalogue are close to the
584
glacial earthquake detection threshold. For instance, during a 50-day period in 2007, Nettles
585
and others (2008) report 6 automatic glacial earthquake detections at Helheim Glacier, East
586
Greenland, with magnitudes between 4.5 and 4.8. However, a more sensitive, interactive
587
detection method identified 5 additional events. Another reason may be that the generation
588
of glacial earthquakes during iceberg calving is more dependent on calving style and terminus
589
geometry than is the generation of seiches. Specifically, in order to generate sufficient energy
590
for detection as a glacial earthquake, it appears necessary that capsizing icebergs collide with
591
the glacier terminus or fjord bottom (Amundson and others, 2008; Tsai and others, 2008,
592
Nettles and Ekström, 2010; Walter and others, 2012). Iceberg calving from floating termini
593
likely transfers less low-frequency surface wave energy into the solid earth (Nettles and
594
Ekström, 2010), and likely inhibits the detection of calving from floating termini using this
595
method. In this context it is interesting to note that between 2008 and 2010 no glacial
596
earthquakes were detected at Alison Glacier, near KULLO (Veitch and Nettles, in press). The
597
reason may be that from around 2009 the calving front was afloat and calving of tabular, non-
598
capsizing icebergs became the predominant mechanism (Veitch and Nettles, in press). On the
599
other hand, we continue to observe calving seiches at KULLO during this period (Figures 5
600
and 6), and Alison Glacier likely produces a substantial fraction of these events.
601
By targeting an entirely independent physical mechanism, our seiche detector can serve as a
602
complement to, and verification of, existing seismic detections of iceberg calving. It remains
603
to be shown to what extent seiches can be generated by calving of non-capsizing icebergs,
604
such as tabular icebergs calving from floating tongues. If sensitive to tabular iceberg calving,
605
our detecting scheme may find events, which at distances of 10’s of km are more difficult to
606
identify with higher frequency detectors. At the same time, seiches could be generated by
607
freely floating icebergs, which capsize in the middle of the fjord and may produce false
608
detection in our calving catalogue. At least occasionally, such spontaneous capsizing can
609
occur, and it can generate a typical high-frequency (>2 Hz) calving signature (Amundson and
610
others, 2010). These cases may be responsible for at least part of the discrepancy between
611
our catalogue at ILULI and the updated version of the catalogue by Amundson and others
612
(2012a). However, if and how often such spontaneous capsizing events can ‘falsely’ trigger
613
our seiche detection algorithm should be systematically investigated by use of satellite
614
images.
615
If the magnitudes of the teleseismic surface wave detections and seiche amplitudes scaled
616
with calving volume, for example, one would expect a clear, perhaps even linear relationship
617
between the amplitude of the low frequency surface waves and seiche signals at the local
618
station. Figure 12 suggests that this is not necessarily the case: On the east-west component,
619
only a weak trend between the two signal amplitudes exists, with some of the strongest
620
(weakest) seiche signals associated with some of the strongest (weakest) surface wave
621
amplitudes. The absence of a clearer relationship is not surprising considering that the
622
relationship between low-frequency surface wave signals and volumes of detaching icebergs
623
is likely complicated: Hydrodynamic drag forces and mélange cover play an important role in
624
the generation of contact forces between detaching icebergs and the glacier terminus, which
625
in turn can cause significant low frequency surface wave energy (Tsai and others, 2008;
626
Amundson and others, 2012b; Walter and others, 2012). Accordingly, more theoretical
627
analysis is needed in order to accurately link centroid single force amplitudes used to model
628
surface waves of glacial earthquake sources (Ekström and others, 2003) to calving volumes.
629
Similarly, one should investigate the influence of hydrodynamic drag forces on seiche
630
amplitudes.
631
An open question and interesting prospect for future work therefore concerns the existence of
632
a clear physical relationship between the observed seiche characteristics and calved iceberg
633
properties such as location, volume or style of calving. Our catalogue indicates there are
634
considerable variations in seiche amplitude, with little correlation with low frequency seismic
635
surface wave amplitude. Future investigations should aim to establish a physical meaning to
636
seiche signal characteristics, such as maximum amplitude, durations and dominant frequency.
637
This would mean that monitoring calving-induced seiches could provide additional
638
quantitative monitoring of calving volume.
639
640
CONCLUSION AND OUTLOOK
641
The present investigation demonstrates that detecting fjord seiches can be used to monitor
642
calving events in North-West Greenland. Seiching events are clearly visible as tilt signals on
643
broadband seismometers located near the shoreline in the vicinity (within 100 km) of calving
644
fronts. At this point, the most reliable seiche-based calving catalogue can only be attained
645
after visual review of continuous seismic records and the output of trigger algorithms.
646
However, although the numbers of missed events and false detections given by our automatic
647
detector can be considerable and at certain times dominant, the presented results
648
nevertheless indicate that real-time seismic monitoring of major iceberg discharge events
649
with little or no user interaction is in principle possible. In its current state, the automatic
650
catalogue is already capable of highlighting qualitative aspects of calving activity in a specific
651
region, such as the seasonal fluctuations near NUUG (Figure 6). According to our background
652
noise analysis, this pattern cannot be attributed to seasonal changes in trigger sensitivity.
653
Consequently, the automatic catalogue could already be used as a monitoring tool to identify
654
transient and long-term changes in calving activity.
655
Nevertheless, at this point, instrumental and/or site noise inhibits reliable detection records
656
at one particular station, KULLO. Incorporating more sophisticated waveform recognition
657
techniques will likely mitigate this problem and significantly improve the overall performance
658
of our detection algorithm. This may also allow inclusion of additional seismic signals
659
associated with iceberg calving such as high frequency (>1 Hz) seismicity and long period (35
660
-150 s) surface wave energy. Another possibility would be to include other features of seiche
661
seismograms, such as polarization and relative heights of spectral peaks.
662
The calving catalogue for NUUG identified seasonal fluctuations in calving activity at the
663
glaciers in the Uummannaq district (Figure 1). This is in agreement with previously reported
664
seasonal fluctuations in terminus positions (Howat and others, 2010). For Jakobshavn Isbræ,
665
the occurrence of events throughout the year at ILULI indicates that the glacier has started to
666
calve in winter as previously suggested by other workers (e. g. Fahnestock and others, 2010,
667
Podrasky and others, ‘Outlet glacier response to forcing over hourly to inter-annual time scales,
668
Jakobshavn Isbræ, Greenland’, submitted to the Journal of Glaciology). These observations
669
indicate that seismic monitoring of calving activity using seiche signals can serve as a means
670
to study changes in glacier dynamics, which have been attracting much scientific attention,
671
especially in Greenland.
672
The present seiche detection technique should be extended to incorporate more GLISN
673
stations at the periphery of the Greenland ice sheet. At the same time, it will be important to
674
establish relationships between physical parameters and seiche duration, amplitude and
675
frequency content. High-resolution satellite images and denser networks of seismometers
676
and fjord pressure sensors will be a valuable tool for this task. Ideally, this will allow for
677
identification of various calving styles and estimation of calving volumes, which are difficult to
678
quantify with existing methods.
679
680
ACKNOWLEDGEMENTS
681
Seismic stations ILULI, KULLO and NUUG are operated by ETH Zurich, and their installation
682
was funded by the Swiss National Science Foundation. We acknowledge the technical support
683
of ELAB and Domenico Giardini of the Swiss Seismological Service for station installation. The
684
seismic data were collected and distributed by the Greenland Ice Sheet Monitoring Network
685
(GLISN) federation and its members. Jan Becker, from GEMPA, provided some useful specific
686
support for SeisComp3 configuration. We thank Martin Lüthi for providing fjord pressure
687
data from station ILULF and Jason Amundson for sharing an updated version of the calving
688
record from Jakobshavn Isbræ. Furthermore, we acknowledge Leif Toudal Pedersen for the
689
data processing of ENVISAT ASAR images (C) European Space Agency, provided by the Danish
690
Meteorological Institute and the PolarView project. The thorough reviews of Meredith Nettles
691
and Tim Bartholomaus substantially improved the scientific quality and readability of this
692
manuscript.