Hunt for Slow Slip Events Along the Sumatran Subduction Zone in A

Journal of Geophysical Research: Solid Earth RESEARCH ARTICLE Hunt for slow slip events along the Sumatran subduction 10.1002/2015JB012503 zone in a decade of continuous GPS data Key Points: Lujia Feng1, Emma M. Hill1, Pedro Elósegui2,3, Qiang Qiu1, Iwan Hermawan1, Paramesh Banerjee1, • No confirming evidence for slow slip 1 events in continuous data from the and Kerry Sieh Sumatran GPS Array • Suspicious signals that resemble 1Earth Observatory of Singapore, Nanyang Technological University, Singapore, 2Haystack Observatory, Massachusetts slow slip events exist but cannot Institute of Technology, Westford, Massachusetts, USA, 3Institute of Marine Sciences, ICM-CSIC, Barcelona, Spain be confirmed • Slow slip events that are either too small or too large may go undetected Abstract Slow slip events (SSEs) have been observed in GPS time series for many subduction zones worldwide but not in decade-long GPS time series from the Sumatran GPS Array (SuGAr). An outstanding Supporting Information: question has been whether SSEs have simply not occurred on the Sunda megathrust or whether they have • Texts S1–S3 and Figures S1–S31 been obscured by the prodigious number of earthquakes and their ensuing postseismic deformation within the time of geodetic observation. We remove all known tectonic signals from the time series to search Correspondence to: for evidence of SSEs. The residuals are essentially flat at the centimeter scale. To search for signals at the L. Feng, [email protected] millimeter scale we test various filtering and visualization techniques. Despite these efforts, we conclude that it is difficult to confirm that SSEs exist at this scale using the current data, although we do see a few suspicious signals. The lack of evidence for events may reflect SSEs occurring at a magnitude, location, or Citation: timescale that renders them undetectable with the current resolution of the SuGAr, that the properties Feng, L., E. M. Hill, P. Elósegui, Q. Qiu, I. Hermawan, P. Banerjee, of this megathrust are not conducive to SSEs, or because the megathrust is in an active period of the and K. Sieh (2015), Hunt for slow slip earthquake cycle. events along the Sumatran subduction zone in a decade of continuous GPS data, J. Geophys. Res. Solid Earth, 120, 8623–8632, 1. Introduction doi:10.1002/2015JB012503. Slow slip events (SSEs) detected by geodetic instruments have earned the name “silent earthquakes” because they release tectonic fault strain more slowly than ordinary earthquakes (∼1 m/s). At rates of several centime- Received 6 SEP 2015 Accepted 9 NOV 2015 ters per year to several centimeters per day, SSEs slip faster than plate motions but too slowly to generate Accepted article online 18 NOV 2015 detectable seismic shaking, allowing them to release accumulated strain with less damage than earthquakes. Published online 11 DEC 2015 However, SSEs can also be a hidden danger if the slowly released strain perturbs the surrounding stress field in a way that leads to a catastrophic quake. SSEs have been detected at many subduction zones worldwide, with their characteristics (e.g., style, size, dura- tion, recurrence interval, and depth) varying widely from place to place [e.g., Schwartz and Rokosky, 2007; Peng and Gomberg, 2010]. While the list of subduction zones with documented SSEs continues to grow, it presently includes Cascadia [Dragert et al., 2001; Miller et al., 2002], central Japan at Boso [Ozawa et al., 2003], southwest Japan at Nankai [Hirose et al., 1999; Ozawa et al., 2002; Obara et al., 2004] and Ryukyu [Heki and Kataoka, 2008; Nishimura, 2014], Mexico [Lowryetal., 2001; Kostoglodovetal., 2003], New Zealand [Douglasetal., 2005; Wallace and Beavan, 2010], Alaska [Ohta et al., 2006; Wei et al., 2012; Fu and Freymueller, 2013], Costa Rica [Outerbridge et al., 2010; Jiang et al., 2012; Dixon et al., 2014], and Ecuador [Vallée et al., 2013]. If we also include subduction zones with preseismic transient slip reported, we add to the list northern Chile and northeast Japan, where preslip but no SSEs in the interseismic period have been yet identified [Obara, 2011; Ito et al., 2013; Ruiz et al., 2014; Schurr et al., 2014]. Although afterslip is sometimes also categorized as one type of SSE [e.g., Schwartz and Rokosky, 2007], in this paper we use SSEs to refer only to slow slip not triggered by a large seismic event. Of the areas that have not had SSEs documented, for some (e.g., the Java, Philippine, and Tonga-Kermadec subduction zones) this reflects a simple lack of data. For some, data are available, and this reflects a lack of systematic search (e.g., the Ryukyu subduction zone before Nishimura [2014] conducted such a search). And for others, scientists have searched for evidence of SSEs but found none (e.g., the Himalaya [Ader et al., 2012]). The Sumatran subduction zone used to be an example of having had no SSEs identified, until recently, a postulated very long SSE was discovered in coral microatoll records [Tsang et al., 2015]. Based on a long-term ©2015. American Geophysical Union. vertical reversal from subsidence to uplift in coral records, this SSE is inferred to have occurred on the Sunda All Rights Reserved. megathrust in the Banyak Islands between 1966 and 1981. FENG ET AL. NO CLEAR EVIDENCE FOR SSES IN SUMATRA 8623 Journal of Geophysical Research: Solid Earth 10.1002/2015JB012503 Figure 1. Map of stations in the Sumatran GPS Array (SuGAr). Stations used in this study are marked in red, while stations not used are marked in white. According to the Advanced National Seismic System composite catalog, the map area experienced 5 earthquakes of M≥8, 11 earthquakes of 7≤M<8, 86 earthquakes of 6≤M<7, and 7881 earthquakes of 4≤M<6 from 2002 to 2014. At least 30 of these events were recorded by the SuGAr in the daily position solutions [Feng et al., 2015]. Colored patches or thick purple lines indicate the estimated rupture patches or segments for the five largest events [Chlieh et al., 2007; Konca et al., 2007, 2008; Hill et al., 2015]. Thin green lines are slab contours at 20 km, 40 km, and 60 km intervals from Slab1.0 [Hayes et al., 2012]. The downdip limit of coupling has been inferred to range from 40 to 60 km depth in previous studies [Chlieh et al., 2008; Prawirodirdjo et al., 2010]. The Sumatran subduction zone has been equipped and monitored with the continuous Sumatran GPS Array (SuGAr) since 2002 [Feng et al., 2015]. Whether the SuGAr has ever recorded any SSEs has become a frequently asked but until now unanswered question. Unfortunately, obtaining an answer is not easy, as the SuGAr is located in one of the most seismically active regions in the world; the SuGAr time series are saturated with coseismic and postseismic signals from many large earthquakes. Removing all these earthquake-related over- lapping spatial and temporal signals has been a daunting task, but one that we tackled in Feng et al. [2015], in which we developed a technique to robustly and self-consistently remove the tectonic signals from all earthquakes recorded by the SuGAr. Building on our prior work, here we use the residual position time series from that effort to hunt for SSEs along the Sumatran subduction zone. 2. Hunt for Slow Slip Events in Sumatra To obtain the residual position time series, we added data from 2014 to extend the time series used in Feng et al. [2015], who analyzed data from 39 continuous GPS stations (Figure 1) from as early as August 2002 through the end of 2013. Since for this study, we otherwise followed the methods described in Feng et al. [2015]; we here only summarize the main steps. First, we reprocessed the GPS data using the GPS-Inferred Positioning System and Orbit Analysis Simulation Software (GIPSY-OASIS) version 6.2. In order to reduce noise from various delays and loading processes that could mask SSEs in the time series, we made efforts to model most of these noise sources directly in the processing (see the supporting information). On the other hand, in order to preserve as many tectonic signals as possible, we did not apply postprocessing filtering at this stage. Second, by carefully examining the result- ing SuGAr time series and comparing them with a seismicity catalog, we identified all recorded earthquakes (30 in total). Third, we fit the north, east, and vertical time series of each station in one optimization procedure FENG ET AL. NO CLEAR EVIDENCE FOR SSES IN SUMATRA 8624 Journal of Geophysical Research: Solid Earth 10.1002/2015JB012503 to simultaneously estimate known signals that include (1) long-term rates, (2) annual and semiannual signals with constant amplitudes and fixed phases, and (3) coseismic offsets and postseismic decays for the identified earthquakes. Lastly, we removed from the raw position time series all the aforementioned known signals based on our final best fit models to obtain postfit residual position time series. The obtained postfit residual time series have an average root-mean-square (RMS) scatter of 2.2, 2.4, and 7.7 mm for the north, east, and vertical components, respectively. When plotting the residual time series for all 39 stations together (Figure S1 in the supporting information), we find that they are essentially flat at the centimeter scale. However, when inspecting the closeup views of the residual time series for subsets of the stations (Figures S2–S10), we see many small wiggles and ramps at the millimeter scale. In the inter- est of better visualizing the pattern of the wiggles and ramps, we filtered the residual time series with a forward-backward Kalman filter and smoother [Simon, 2006] and constructed velocity geodograms [Wernicke and Davis, 2010] with contrasting colors to represent velocities toward north, east, or up (blue positives) and velocities toward south, west, or down (red negatives) (Figure S11) (details in the supporting information).

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