Complex rupture of the 13 November 2016 Mw 7.8 Kaikoura, New Zealand earthquake: Comparison of high-frequency and low-frequency observations

Accepted Manuscript Complex rupture of the 13 November 2016 Mw 7.8 Kaikoura, New Zealand earthquake: Comparison of high-frequency and low-frequency observations

Dun Wang, Yunguo Chen, Qi Wang, Jim Mori PII: DOI: Reference:

S0040-1951(18)30064-7 https://doi.org/10.1016/j.tecto.2018.02.004 TECTO 127776

To appear in:

Tectonophysics

Received date: Revised date: Accepted date:

31 August 2017 31 January 2018 2 February 2018

Please cite this article as: Dun Wang, Yunguo Chen, Qi Wang, Jim Mori , Complex rupture of the 13 November 2016 Mw 7.8 Kaikoura, New Zealand earthquake: Comparison of high-frequency and low-frequency observations. The address for the corresponding author was captured as affiliation for all authors. Please check if appropriate. Tecto(2017), https://doi.org/10.1016/j.tecto.2018.02.004

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ACCEPTED MANUSCRIPT Complex Rupture of the 13 November 2016 Mw 7.8 Kaikoura, New Zealand Earthquake: Comparison of High-frequency and Low-Frequency Observations

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Dun Wang1, Yunguo Chen2, Qi Wang2, and Jim Mori3

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1. State Key Laboratory of Geological Processes and Mineral Resources, School of Earth Sciences, China University of Geosciences, Wuhan, Hubei 430074, China

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2. School of Geophysics, China University of Geosciences, Wuhan, Hubei 430074, China

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3. Disaster Prevention Research Institute, Kyoto University, Gokasho, Uji, Kyoto 6110011, Japan

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Abstract：We apply a back-projection analysis to determine the locations and timing of the

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sources of short-period (0.5 to 2 s) energy generated by the 13 November 2016 Mw 7.8 Kaikoura, New Zealand earthquake using data from Australian and Southeast Asia. The sources of strong

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short-period energy are distributed northeast of the epicenter at distances of 70 to 80 km during

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the time period of 70 to 80 s after the initiation. The locations of sources of long-period energy derived from global seismic and local GPS data are close to the northeastern edge of the source area, and complementary to the areas of short-period energy which occur in the converging region of the Upper Kowhal, Papatea, and Jordan Thrust faults. The obvious frequency dependence might be attributed to complexities in fault geometry, possible rupture in the subduction interface, or varying focal mechanisms during the earthquake.

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1. Introduction On 13 November 2016, a Mw 7.8 earthquake occurred in the northeast region of the South Island of New Zealand. Most of New Zealand lies in a NE–SW direction, parallel to and

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straddling the active segment of the Pacific–Australian plate boundary [Campbell et al., 2012].

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The plate motion in the northeast South Island of New Zealand is dextral transpression on the

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Alpine fault system. The Alpine fault splays into the more easterly striking faults of the Marlborough Fault System, including the Wairau, Hope, Awatere, and Clarence faults (Fig. 1),

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which progressively accommodate the plate boundary displacement [Norris and Cooper, 2001].

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The earthquake rupture started from the Humps fault which is located south of the Hope Fault. Aftershocks for one week following the mainshock generally show a NE trend with an extent of

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170 km in length and 60-100 km in width (Figure1). Aftershocks that occurred off shore of

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Kaikoura are scattered over a wide area. Focal mechanisms of the aftershocks are diverse, with mostly thrust mechanisms in the area around and to the southwest of Kaikoura, and strike-slip and

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thrust mechanisms in the area northeast of Kaikoura. Previous studies [Duputel and Rivera, 2017]

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show that the earthquake was initiated with strike-slip faulting and became strike-slip in the later part, then triggered a shallow-dipping thrust subevent, implying a complex rupture process. Field investigations identify surface ruptures on more than 13 faults, including possible slip along the southern Hikurangi subduction interface [Bai et al., 2017; Hamling et al., 2017; Kaiser et al., 2017]. In this study we investigate the two extremes of high-frequency and low-frequency source models for the earthquake. The high-frequency model is derived from teleseismic P-wave data

ACCEPTED MANUSCRIPT (0.5-2.0 Hz) and reflects energy radiation that is likely caused by small-scale structural features and details of the rupture propagation for this complex event. The high-frequency model is important for evaluating the damaging ground shaking produced by the earthquake. The low-frequency model is derived from regional GPS data (static displacements) and global

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seismograms, and reflects the tectonic faulting. The low-frequency model contributes to the

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understanding of the distribution of slip across the many faults that were activated during the

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earthquake. The high-frequency and low-frequency models show quite different patterns and this comparison contributes to a better understanding of the complicated relationship between fault slip

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and damaging seismic radiation.

2. Back-projection analyses

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Data

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For this earthquake, stations in Australia and Southeast Asia stations provide the best dense distribution for the back-projection analyses. The total number of the stations is ~100 with

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epicentral distances ranging from 30o to 85o. The azimuths from the New Zealand earthquake are

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260o to 310o. Seismic arrays in Japan, Europe and the US are located at unfavorable distances for this event.

Figure 2 shows the distribution of stations in Australia and Southeast Asia and focal planes of the Mw 7.8 earthquake from the U.S. Geological Survey (USGS) and Global CMT (GCMT) focal mechanisms. There is a good similarity of waveforms within a recording network but there are some differences in the waveform shapes at global stations with wider azimuth ranges. Consistency of the waveforms within an array is important for obtaining good results. In order to

ACCEPTED MANUSCRIPT ensure similar waveform shapes for the data included in our analyses, we use a threshold value of 0.4 for the correlation coefficient of the waveforms.

Method

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In the back-projection method, we align stacks of time windows of the P wave to search for the

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grid point that produces the highest stack amplitude, which is interpreted to be the most

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likely/efficient radiator [Ishii et al., 2005]. In this procedure we use the squared of the stack amplitude, as described in details in [D Wang et al., 2016b]. The linear stack is applied since we

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need to get the accurate estimate of the amplitudes for the short-period energy radiation [Xu et al.,

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2009].

We first align the initial 10 s of the filtered (2.0 to 100 s) P arrival using cross correlations with

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a model waveform (AU.WC2). The predicted travel time differences between the stations are

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calculated using the Earth model IASP 91 [Kennett and Engdahl, 1991] . The assumed location of the starting point for earthquake is fixed at the hypocenter determined by USGS (173.0770o E,

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-42.7568o S, and depth 15 km). We set the grid points with a fixed depth of 15 km for all the

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source locations, since back-projection method doesn’t have a good resolution in depth. The horizontal location of the back-projected energy is less affected by the fixed depth as tested in many studies [such as Kiser and Ishii, 2012; D Wang et al., 2016a; Yao et al., 2013] For each time window, we test locations for a wide area in the source region using a grid of 46 by 46 points spaced at 8 km. The time windows have a duration of 10 s and are offset by 1 s. Then, the location with the largest stack amplitude is inferred to be the most likely/efficient source location for that time window.

ACCEPTED MANUSCRIPT For the back-projection procedure, we filter the data between 0.5 and 2.0 s to look at the short-period content of the radiated energy. The chosen period range of these results represents a bandwidth where there are good correlation of the waveforms and sufficient time resolution to

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study the details of the rupture [Koper et al., 2011].

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Results

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Figure 3(a) shows the determined locations of the most likely/efficient radiator (i.e. locations of highest stack amplitude) for each time window, as determined using data from the Australia and

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Southeast Asia stations. The size of the circles is proportional to the square of the stack amplitude.

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The rupture shows a clear northeastward propagation, with the strongest short-period energy radiated from an area about 70 to 80 km northeast of the epicenter during a period from 60 to 80 s

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after the rupture initiation. Figure 3(b) show the distance from the epicenter as a function of time

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for the source locations of each time window. If we believe that the rupture propagation front for the earthquake produces more high-frequency energy due to the initiation of brittle failure, the

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determined expansion speed of the source points would represent the rupture speed. The

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determined average rupture extension speeds is 1.0-1.5 km/s, which is less than half of the local shear-wave velocity [Laske et al., 2001]. Notice that here multiple faults were involved, and the rupture was probably a cascade process instead of a continuous rupture propagation. So the rupture extension speed here is not necessarily the propagation speed of rupture tip along a single fault plane. In the beginning, the rupture shows a very slow rupture expansion, and emitted an energy burst around the epicentral area. Later as larger amplitude high-frequency energy is produced, the rupture expands with a speed of ~ 1.5 km/s. The total duration is around 80 to 100 s,

ACCEPTED MANUSCRIPT with two large energy bursts occurring at 15 and 70 s (Figure 3(c)). Our results are similar to the back-projection results of Zhang et al. [2017] and Hollingsworth et al. [2017].

Resolution Test

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In order to evaluate the possible location bias in the back-projection analysis, we perform

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back-projections using data recorded on the Australia and Southeast Asia stations for 12 moderate

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earthquakes (previous earthquakes and aftershocks) with magnitudes from M5.7 to M6.5 (similar to Fan and Shearer [2017]). The same station corrections derived for the main shock are used in

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analyzing these smaller events (Figure 4). The waveforms were filtered using the same frequency

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range (0.5-2.0 Hz). Our back-projection locations are compared to the published Geonet, USGS and GCMT locations.

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For events close to the 2016 mainshock epicenter there is a small difference of about 10 km

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between back projection locations and the USGS/GMCT locations. The back-projection results are located to the west or southwest of the published locations. In the northeast region of the 2016

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earthquake there appears to be a larger bias of about 20 to 40 km in the southwest direction.

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Considering the finite length for M6-7 earthquakes and the location uncertainties for the epicenters, we infer that the average resolution for our back projection results is 20 – 40 km.

3. Global seismic observation As illustrated in previous studies [Bai et al., 2017; Clark et al., 2017; Duputel and Rivera, 2017; Furlong and Herman; Hamling et al., 2017; Kaiser et al., 2017; Stirling et al., 2017; Zhang et al., 2017], this earthquake consists of a complex rupture that involves a number of fault planes in

ACCEPTED MANUSCRIPT different geodynamic environments (crustal faults and interplate interfaces), making it one of the most complicated seismic sources to have ever been recorded by modern seismometers. Looking at waveforms recorded on a wide distribution of global stations can display the direction of rupture propagation and the locations of large source pulses of slip in a straightforward way,

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independent of model results (e.g., Ni et al. [2005]; D Wang et al. [2016a]; Zhan et al. [2014]).

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Also, comparing the shapes of globally recorded waveforms is a qualitative way to evaluate the

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results derived from back-projections using data recorded at a narrow azimuth range. We aligned vertical broadband velocity waveforms on the P initiation for seismograms recorded

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at distances of 30o to 85o (Figure 5a). The data were filtered between 0.05 and 0.2 Hz. One can

directivity effect and radiation pattern.

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observe in Figure 5b that the low-frequency global waveforms are obviously dissimilar due to the

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There appear to be three (groups) of subevents that occur 20, 40, and 70 s after the origin time,

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with relatively small amplitudes for the first two and a much larger amplitude for the last. The arrivals of the pulses for the first two are not clearly shown in the waveforms in all azimuths. For

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the first 20 s, there is not much moveout, indicating a location close to the initial epicenter. Then

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from 40 to 80 s, the rupture appears to expand toward northeast with a clear burst of large amplitude from 70 to 80 s. We picked the times of the largest pulses that are clearly recorded at all azimuths, and determined the source position using a relative location method [D Wang et al., 2016a]. The location of the source of the pulse is 170 km northeast of the epicenter (Figure 5c), which is consistent with slip model derived from strong motion observations [Bradley et al., 2017; Kaiser et al., 2017], and is generally similar to slip models derived from teleseismic seismic data [Zhang et al., 2017] and GPS observations [Hamling et al., 2017]. 100 s after the P initiation, the

ACCEPTED MANUSCRIPT amplitudes drop close to the noise level, so further slip is not resolvable. These observations give a source duration of 100 s, and an average speed of ~ 1.5-2.0 km/s for the slip expansion. Results obtained from the global observations show the rupture propagated northeast with a slow rupture propagation speed 1.0-2.0 km/s, and a total duration of 80 to 100 s, which generally

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agree with the rupture direction and source duration obtained in our back-projection. However, the

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locations of strong energy radiations in the high-frequency range (0.5-2.0 Hz) seem to be

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inconsistent with the location of the large low-frequency pulse, even considering the location uncertainties in the back-projection results, as also reported in several previous earthquakes [Fan

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et al., 2016; Kiser and Ishii, 2011; Koper et al., 2011; Lay et al., 2012; Meng et al., 2011; Satriano

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et al., 2014; D Wang and Mori, 2011; Yao et al., 2013].

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4. Coseismic displacements

Coseismic displacements of the Mw 7.8 Kaikoura earthquake are recorded by the continuous

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and campaign GPS stations, which show intriguing characteristics of the 3D coseismic

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displacement field over the source region [Hamling et al., 2017]. Coseismic displacement field for continuous-GPS stations were estimated based on the five days prior to the earthquake and 12 hours following the event. For the camp-GPS sites, the inter-seismic and pre-seismic site velocities from 1999 to 2016 and the observed data following the event are used. Therefore the deduced coseismic displacements inevitably include some early afterslips in the camp-GPS data. As shown in Figure 6, the coseismic displacements in the epicenter area shows thrust motion with some strike slip components, which is consistent with the oblique (meter-sclae) surface

ACCEPTED MANUSCRIPT displacements of two pre-exist ENE to NE-striking faults in this area. There are large eastward displacements observed in the GPS sites northeast of Kaikoura, coincident with the location of the largest thrust subevent by W-phase inversion [Duputel and Rivera, 2017]. In the northeastern edge of the south island, the displacements are dominated by large northeast displacements with

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moderate vertical uplifts.

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We use a fault model with four faults [Kaiser et al., 2017] to invert slip distribution by utilizing

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the coseismic offsets observed in the GPS sites. The strike and dip of each fault from south to north is 248/61 (Fault 1), 210/49 (Fault 2), 226/49 (Fault 3), and 220/80 (Fault 4), respectively

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[Kaiser et al., 2017]. The four faults from south to north are divided into 30 ×15, 20 ×12, 20 ×12,

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25 × 10 subfaults, respectively (Figure 7(a)). The size of each subfault is 3 × 3 km2. Therefore the lengths/widths for faults 1 to 4 are, 90/45 km, 60/36 km, 60/36 km, and 75/30 km, respectively.

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Then, we fix the geometric parameters of four faults and invert slips on the fault planes by the

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Non-negative least-squares inversion [Lawson and Hanson, 1974; Li et al., 2017; Q Wang et al., 2011].

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The best fitting model of the coseismic slip distribution for the Kaikoura earthquake, is

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illustrated in Figure 7(b). Generally there are two large slip regions, one close to the epicenter, and the other is located in the north edge of the Off-shore fault (fault 4) with a maximum slip of 32 m (Figure S1), which are generally consistent with the slip model derived from seismic data [Bai et al., 2017; Kaiser et al., 2017]. Most of the model displacement vectors fit the observations well, except for a few camp-GPS sites located on the southwestern segment of the fault 1 due to the complexities of the fault geometry (Figure 8). Misfits (residuals) between the observations and simulations are about 0.2 m

ACCEPTED MANUSCRIPT in horizontal component, and are about 0.3 m in vertical component, suggesting that the geodetic observations can be generally explained by the model. ,

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5. Discussion

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Back-projection in high-frequency band (0.5-2.0 Hz) shows largest high-frequency energy

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radiations 70-80 km northeast to the epicenter, whereas the strong low-frequency pulse that shows in the global seismograms and slip model derived from the GPS observations are located in the

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northeastern end, possibly the Needles fault. Those observations are generally supported by the

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slip models derived from local strong motion recordings [Kaiser et al., 2017], and derived from teleseismic waveforms [Bai et al., 2017]. Back-projection of strong motion data shows the

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high-frequency energies (over 0.25 Hz) were mainly radiated around the epicenter area and

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Papatea faults, which generally agree well with our back-projection location. The slip model derived from strong motion data filtered in relatively low-frequency band (0.1 to 0.3 Hz) indicates

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that large slip occurred in the Needles fault, consistent with our location of the strong

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low-frequency pulse show in global waveforms (Figure 5), and large slip in the north edge of the Needles faults in the slip model inverted from the GPS data. However, different fault models and different types of observations resulted in varying slip models [Bai et al., 2017; Hamling et al., 2017; Kaiser et al., 2017; Zhang et al., 2017]. For example, compared to GPS observations, InSAR data has limited resolution for the fault slips in and off the coast area [Hamling et al., 2017]. Combining both could possibly downgrade the resolution of inverted slip in the Needles fault.

ACCEPTED MANUSCRIPT Frequency dependence of energy radiation has been convincingly observed for several past megathrust earthquakes, for example, the 2010 Mw 8.8 Chile and the 2011 Mw 9.0 Tohoku, Japan earthquakes [Koper et al., 2011; Lay et al., 2012; Meng et al., 2011; D Wang and Mori, 2011; Yao et al., 2013]. For the Tohoku earthquake, depth-varying frictional property in the subducted

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interface might contribute to the frequency dependent energy radiation. However, it might be even

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more complicated in this case, since there are many (over 13) individual faults were ruptured in

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the earthquake with different focal mechanisms. Fault geometry, possible rupture in the interplate interface, and radiation pattern can be candidates for the cause of observed location difference

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between the low- and high-frequency differences.

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Complexities in fault geometry, such as a fault kink, branch or a coalescence of multiple cracks, trend to generate high-frequency radiation [Adda-Bedia and Madariaga, 2008; Dunham et al.,

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2011]. Fault segmentation might be a cause for the high-frequency energy radiation that occurred

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20 km north of the Kaikoura. The edges of faults 2 and 3 and the area in between slip patches along each fault are potential sites for high-frequency waves [Madariaga, 1979]. Geological field

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investigations indicate that Upper Kowhal fault, Papatea fault, and Jordan Thrust fault converge in

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the area where the high-frequency energy were radiated, showing sophisticated fault layouts there [Kaiser et al., 2017]. Therefore it is also possible that the complexities in the fault geometry contribute to the intensive high-frequency emission. Another possible reason for the high-frequency energy is the megathrust interface, which seems to be ruptured ~6 m beneath the place of high-frequency radiation [Bai et al., 2017; Furlong and Herman, 2017]. However, due to limited resolution in depth for the back-projection method, the slip in megathrust interface need further investigations using better constrained fault geometry and local velocity structure.

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6. Conclusions We analyzed the short-period energy (0.5 to 2 s) radiated by the 13 November 2016 Mw 7.8 New Zealand earthquake using Australia and Southeast Asia stations. The rupture started with a

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small amplitude and very slow rupture speed for the first 20 seconds, then expanded with a speed

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of ~1.0-2.0 km/s for another 60-80 seconds. The short-period energy is mainly coming from the

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area where the Upper Kowhal, Fidget, and Jordan Thrust faults converge. The centroid of the large slips is located on the Needles fault in northeastern edge of the source area. This location

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difference in the radiations may be associated with the complexities in fault geometry, different

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focal mechanisms, or differences in fault plane properties for crust faults and megathrust

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Data and resources

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interfaces.

Seismic data used in this study can be obtained from the Incorporated Research Institutions for (IRIS).

Focal

mechanisms

are

downloaded

from

the

USGS

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Seismology

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(https://earthquake.usgs.gov/, last accessed August 3, 2017) and GCMT (www.globalcmt.org, last accessed December 3, 2017), Geonet (https://www.geonet.org.nz/, last accessed December 3, 2017), and are from Duputel and Rivera [2017]. The GPS data are from Hamling et al. [2017]. All other data used in the paper came from published sources in the references. All the figures were created using the Generic Mapping Tools (GMT) of Wessel and Smith [1991].

Acknowledgements

ACCEPTED MANUSCRIPT This work was supported by NSFC grants 41474050 (D.W.), the Fundamental Research Funds for the Central Universities, China University of Geosciences (Wuhan) CUG170602 (D.W.), and National Programme on Global Change and Air-Sea Interaction (GASI-GEOGE-02). Comments from the editor Kelin Wang, guest editor, and two anonymous reviewers have greatly improved

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the manuscript. We thank Hao Zhao and Qiang Yao for sharing the data of surface faults.

References

MA

Seismol. Soc. Am., 98(5), 2291-2302.

NU

Adda-Bedia, M., and R. Madariaga (2008), Seismic radiation from a kink on an antiplane fault, Bull.

Armijo, R., P. Tapponnier, J. L. Mercier, and T. L. Han (1986), Quaternary extension in southern

D

Tibet: field observations and tectonic implications, Journal of Geophysical Research

PT E

Atmospheres, 91(B14), 13803–13872. Bai, Y., T. Lay, K. F. Cheung, and L. Ye (2017), Two regions of seafloor deformation generated the

CE

tsunami for the 13 November 2016, Kaikoura, New Zealand earthquake, Geophys. Res.

AC

Lett. , 44(13), 6597-6606. Bradley, B. A., H. N. Razafindrakoto, and V. Polak (2017), Ground‐ Motion Observations from the 14 November 2016 M w 7.8 Kaikoura, New Zealand, Earthquake and Insights from Broadband Simulations, Seismol. Res. Lett., 88(3), 740-756. Campbell, H., A. Malahoff, G. Browne, I. Graham, and R. Sutherland (2012), New Zealand Geology, Episodes, 35(1), 57-71.

ACCEPTED MANUSCRIPT Clark, K., E. Nissen, J. Howarth, I. Hamling, J. Mountjoy, W. Ries, K. Jones, S. Goldstien, U. Cochran, and P. Villamor (2017), Highly variable coastal deformation in the 2016 M W 7.8 Kaikōura earthquake reflects rupture complexity along a transpressional plate boundary, Earth Planet. Sci. Lett. , 474, 334-344.

PT

Dunham, E. M., D. Belanger, L. Cong, and J. E. Kozdon (2011), Earthquake ruptures with strongly

RI

rate-weakening friction and off-fault plasticity, Part 2: Nonplanar faults, Bull. Seismol. Soc.

SC

Am., 101(5), 2308-2322.

Duputel, Z., and L. Rivera (2017), Long-period analysis of the 2016 Kaikoura earthquake, Physics

NU

of the Earth and Planetary Interiors, 265, 62-66.

MA

Elliott, J. R., R. Jolivet, P. J. González, J.-P. Avouac, J. Hollingsworth, M. P. Searle, and V. L. Stevens (2016), Himalayan megathrust geometry and relation to topography revealed by

D

the Gorkha earthquake, Nature Geoscience, 9, 174-180.

PT E

Fan, W., and P. M. Shearer (2017), Investigation of back‐ projection uncertainties with M6 earthquakes, Journal of Geophysical Research Solid Earth, 122, 7966-7986.

CE

Fan, W., P. M. Shearer, C. Ji, and D. Bassett (2016), Multiple branching rupture of the 2009

AC

Tonga–Samoa earthquake, Journal of Geophysical Research Solid Earth, 121, 5809-5827.

Furlong, K. P., and M. Herman (2017), Reconciling the Deformational Dichotomy of the 2016 Mw 7.8 Kaikoura NZ Earthquake, Geophys. Res. Lett. , 44(13), 6788-6791. Hamling, I. J., S. Hreinsdóttir, K. Clark, J. Elliott, C. Liang, E. Fielding, N. Litchfield, P. Villamor, L. Wallace, and T. J. Wright (2017), Complex multifault rupture during the 2016 Mw 7.8 Kaikōura earthquake, New Zealand, Science, 356(6334), eaam7194.

ACCEPTED MANUSCRIPT Hollingsworth, J., L. Ye, and J. P. Avouac (2017), Dynamically triggered slip on a splay fault in the Mw 7.8, 2016 Kaikoura (New Zealand) earthquake, Geophys. Res. Lett., 44(8), 3517-3525. Ishii, M., P. M. Shearer, H. Houston, and J. E. Vidale (2005), Extent, duration and speed of the 2004 Sumatra-Andaman earthquake imaged by the Hi-Net array, Nature, 435(7044), 933-936,

PT

doi:Doi 10.1038/Nature03675.

RI

Kaiser, A., N. Balfour, B. Fry, C. Holden, N. Litchfield, M. Gerstenberger, E. D’Anastasio, N.

SC

Horspool, G. McVerry, and J. Ristau (2017), The 2016 Kaikōura, New Zealand, Earthquake: Preliminary Seismological Report, Seismol. Res. Lett., 88(3), 727-739.

NU

Kennett, B., and E. Engdahl (1991), Traveltimes for global earthquake location and phase

MA

identification, Geophys. J. Int., 105(2), 429-465.

Kiser, E., and M. Ishii (2011), The 2010 Mw 8.8 Chile earthquake: Triggering on multiple segments

D

and frequency‐ dependent rupture behavior, Geophys. Res. Lett., 38(7).

PT E

Kiser, E., and M. Ishii (2012), Combining seismic arrays to image the high‐ frequency characteristics of large earthquakes, Geophys. J. Int., 188(3), 1117-1128.

CE

Koper, K. D., A. R. Hutko, T. Lay, C. J. Ammon, and H. Kanamori (2011), Frequency-dependent

AC

rupture process of the 2011 M w 9.0 Tohoku Earthquake: Comparison of short-period P wave backprojection images and broadband seismic rupture models, Earth, planets and space, 63(7), 599-602. Laske, G., G. Masters, and C. Reif (2001), CRUST 2.0: A new global crustal model at 2× 2 degrees, Institute of Geophysics and Planetary Physics, The University of California, San Diego, website: http://mahi. ucsd. edu/Gabi/rem. dir/crust/crust2. html. Lawson, C. L., and R. J. Hanson (1974), Solving least squares problems, SIAM.

ACCEPTED MANUSCRIPT Lay, T., H. Kanamori, C. J. Ammon, K. D. Koper, A. R. Hutko, L. Ye, H. Yue, and T. M. Rushing (2012), Depth‐ varying rupture properties of subduction zone megathrust faults, Journal of Geophysical Research: Solid Earth (1978–2012), 117(B4) , 2156-2202. Li, J., C. Liu, Y. Zheng, and X. Xiong (2017), Rupture Process of the Ms 7.0 Lushan Earthquake

PT

Determined by Joint Inversion of Local Static GPS Records, Strong Motion Data, and

RI

Teleseismograms, J. Earth Sci., 28(2), 404-410.

SC

Madariaga, R. (1979), On the relation between seismic moment and stress drop in the presence of stress and strength heterogeneity, Journal of Geophysical Research Solid Earth, 84(B5),

NU

2243–2250.

MA

Meng, L., A. Inbal, and J. P. Ampuero (2011), A window into the complexity of the dynamic rupture of the 2011 Mw 9 Tohoku‐ Oki earthquake, Geophys. Res. Lett., 38(7).

D

Ni, S., H. Kanamori, and D. Helmberger (2005), Seismology: energy radiation from the Sumatra

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earthquake, Nature, 434(7033), 582-582. Norris, R. J., and A. F. Cooper (2001), Late Quaternary slip rates and slip partitioning on the Alpine

CE

Fault, New Zealand, J. Struct. Geol., 23(2), 507-520.

AC

Satriano, C., V. Dionicio, H. Miyake, N. Uchida, J.-P. Vilotte, and P. Bernard (2014), Structural and thermal control of seismic activity and megathrust rupture dynamics in subduction zones: Lessons from the Mw 9.0, 2011 Tohoku earthquake, Earth Planet. Sci. Lett., 403, 287-298. Stirling, M. W., N. Litchfield, P. Villamor, R. Van Dissen, A. Nicol, J. Pettinga, P. Barnes, R. Langridge, T. Little, and D. Barrell (2017), The Mw7. 8 2016 Kaikōura earthquake: Surface fault rupture and seismic hazard context, Bulletin of the New Zealand Society for Earthquake Engineering, 50(2), 73-84.

ACCEPTED MANUSCRIPT Wang, D., H. Kawakatsu, J. Mori, B. Ali, Z. Ren, and X. Shen (2016a), Backprojection analyses from four regional arrays for rupture over a curved dipping fault: The Mw 7.7 24 September 2013 Pakistan earthquake, J. Geophys. Res. B Solid Earth, 121(3), 1948-1961. Wang, D., and J. Mori (2011), Frequency‐ dependent energy radiation and fault coupling for the

PT

2010 Mw8. 8 Maule, Chile, and 2011 Mw9. 0 Tohoku, Japan, earthquakes, Geophys. Res.

RI

Lett., 38(22).

SC

Wang, D., N. Takeuchi, H. Kawakatsu, and J. Mori (2016b), Estimating high frequency energy radiation of large earthquakes by image deconvolution back-projection, Earth & Planetary

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Science Letters, 449, 155-163.

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Wang, Q., X. Qiao, Q. Lan, J. Freymueller, S. Yang, C. Xu, Y. Yang, X. You, T. Kai, and C. Gang (2011), Rupture of deep faults in the 2008 Wenchuan earthquake and uplift of the Longmen

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Shan, Nature Geoscience, 4(9), 634-640.

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Wessel, P., and W. H. Smith (1991), Free software helps map and display data, Eos, Transactions American Geophysical Union, 72(41), 441-446.

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Xu, Y., K. D. Koper, O. Sufri, L. P. Zhu, and A. R. Hutko (2009), Rupture imaging of the M-w 7.9

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12 May 2008 Wenchuan earthquake from back projection of teleseismic P waves, Geochem Geophy Geosy, 10(4), 1525-2027. Yao, H., P. M. Shearer, and P. Gerstoft (2013), Compressive sensing of frequency-dependent seismic radiation from subduction zone megathrust ruptures, Proc. Nat. Acad. Sci. U.S.A., 110(12), 4512-4517.

ACCEPTED MANUSCRIPT Zhan, Z., H. Kanamori, V. C. Tsai, D. V. Helmberger, and S. Wei (2014), Rupture complexity of the 1994 Bolivia and 2013 Sea of Okhotsk deep earthquakes, Earth Planet. Sci. Lett., 385, 89-96. Zhang, H., K. D. Koper, K. Pankow, and Z. Ge (2017), Imaging the 2016 MW 7.8 Kaikoura, New

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Zealand Earthquake with Teleseismic P Waves: A Cascading Rupture Across Multiple

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Faults, Geophys. Res. Lett. , 44(10), 4790-4798.

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List of figure captions

Figure 1 Left: Locations of aftershocks (yellow circles) that occurred within one week following

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the mainshock and previous seismicity (gray circles) according to the USGS. Black lines indicate surface faults [Hamling et al., 2017]. The red star indicates the epicenter determined by the USGS.

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The red circles show the aftershocks with magnitude larger or equal to 5.0. Red lines represent surface ruptures in this earthquake. Focal mechanisms are determined by the GCMT. Right: Same

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as in left except that the aftershocks from one to four weeks following the mainshock are plotted.

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Figure 2 Station map (left) and waveforms (right) for the Australia and Southeast Asia stations (red star).Hi-net stations (yellow star) in Japan are also shown. Solid and dashed lines show the epicenter distances and strikes of the fault planes determined by USGS, respectively. Green dashed lines indicate the fault planes determined by GCMT. Large black star shows the epicenter determined by the USGS.

Figure 3 (a): Locations, timings and amplitudes for the stack with the maximum correlation at each time step (1 s) in high-frequency bands (0.5 to 2.0 Hz) for the November 13, 2016 Mw 7.8

ACCEPTED MANUSCRIPT New Zealand earthquake. Red lines represent surface ruptures in this earthquake. (b): Location (distance from the epicenter) of the energy release in each time window. The slope represents the rupture propagation speed. (c): Relative energy release as a function of time.

Figure 4 Back-projection results for a series of moderate earthquakes (M5.7 to M6.5) using

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station corrections derived from the mainshock. The circles are the local maximums of the stacked

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amplitudes for each time window. The size is proportional to the amplitude. Red lines represent

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surface ruptures of the 2016 Kaikoura mainshock. The diamond, triangle, and square indicate the

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epicenter/centroid determined by the Geonet, GCMT, and USGS, respectively. Available focal mechanisms (red for the Geonet and black for the GCMT) are also plotted.

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Figure 5 (a) shows the locations of the global broadband stations (red dots) and the epicenter (red

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star). (b) shows vertical broadband seismograms from global networks for distance of 30o to 85o

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aligned on the P initiation and sorted by azimuth. Shaded area indicates the azimuth range for the Australia and Southeast Asia stations. (c) Location of a large picked pulse (red square) using a

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relative location method. The red star represents the epicenter of the November 13, 2016 Mw 7.8 New Zealand earthquake. Green square represents the centroid location of the high-frequency

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radiation. (d) Black triangles indicate the peaks of the largest pulse, which constrain a location (red square on subfigure (c)) that is determined to be similar to large slip area estimated from strong motion data [Kaiser et al., 2017]. The red squares indicate the forward arrival times using the determined location of the pulse in the waveforms. The green squares indicate the forward arrival times using the centroid location of the high-frequency radiation (green square on subfigure (c)), which constitutes a different curve of the arrival times as compared to the observed arrival times of the pulse in the waveforms.

ACCEPTED MANUSCRIPT Figure 6 Horizontal (A) and vertical (B) coseismic offsets of the Mw 7.8 Kaikoura earthquake (different color arrows represent different scales). Focal mechanisms are for four subevents inverted from W-phase waveforms [Duputel and Rivera, 2017]. Red star indicates the epicenter determined by the USGS.

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Figure 7 (a): Fault model in map view. The strike/dip of each fault plane is as follows: 248/61

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(Fault 1), 210/49 (Fault 2), 226/49 (Fault 3), and 220/80 (Fault 4). The red star indicates the

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epicenter of the main earthquake. (b): Slip distribution inverted from the GPS data. The color-bar

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represents the slip range of the inverted slip model from the minimum 0 m to maximum ~32 m. The red star indicates the epicenter of the main earthquake.

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Figure 8 Fitting between the observed GPS data and the prediction of the inverted slip model in

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Figure 7b in horizontal component (a) and in vertical component (b).

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Highlights Determined high-frequency energy radiation of the 2016 M7.8 New Zealand earthquake Obtained slip models inverted from near field GPS observations The high-frequency and low-frequency models show quite different patterns

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