From temblor: “Quake Connectivity: 3 January 2019 M=5.1 Japan shock was promoted by the April 2016 M=7.0 Kumamoto earthquake”


From temblor

January 7, 2019
By Shinji Toda, Ph.D. (IRIDeS, Tohoku University)
Ross S. Stein, Ph.D. (Temblor, Inc.)

Was the small but strong shock in southern Japan a random event?

In the late evening on January 3, a M=5.1 earthquake caused strong local ground shaking (JMA Intensity 6-, equivalent to MMI Intensity IX-X) in Nagomi-machi, ~25 km north of Kumamoto City (Fig. 1). Although the quake brought only light damage to the town, it stopped the Shinkansen ‘bullet trains’ and highway services for an emergency check-up during Japan’s well-traveled New Year holiday.

Figure 1. JMA intensity distribution of the January 3 M=5.1 earthquake. At the epicenter (X), the shaking reached JMA 6-.

Japan’s Headquarters for Earthquake Research Promotion (HERP) declares the M=5.1 to be unrelated to the 2016 M=7.0 shock. We beg to differ.

This quake recalls the devastating 2016 Mw=7.0 (Mjma=7.3) Kumamoto earthquake that killed 50 people and destroyed thousands of houses (Hashimoto et al., 2017). Immediately after the M=5.1 shock, HERP (2019) announced that there is no causal relation between the 3 Jan 2019 shock and the 15 April 2016 Kumamoto earthquake. In contrast, we contend that the M=5.1 is instead part of the long-lasting and remarkably widespread aftershock sequence of the M=7.0 Kumamoto earthquake.

Figure 2. (Left panel) Coulomb stress imparted by the 2016 Kumamoto earthquake sequence to the surrounding crust as a result of the combined Mw=6.0 and Mw=7.0 shocks. This figure was originally posted in a Temblor blog (Stein and Toda, 2016). Regions in which strike-slip faults are brought closer to failure are red (‘stress trigger zones’); regions now inhibited from failure are blue (‘stress shadows’). Aftershocks during first three months (translucent green dots) generally lie in regions brought closer to failure. The January 3 event (yellow star) is located in one of the stress trigger zones.

(Right panel) Seismicity rate change between before (2009/01/01-2016/04/14) and after (2016/04/14-2019/01/02) the 2016 Kumamoto earthquake sequence. Red areas ‘turned on’ after the 2016 mainshock; blue areas ‘shut down.’

The M=5.1 shock struck in a previously published Coulomb ‘stress trigger zone’

In the web article of the IRIDeS Tohoku University released immediately after the 2016 shock (IRIDeS, 2016) and our blog article posted on September 2, 2016 (Stein and Toda, 2016), we emphasized the effect of Coulomb stress transfer to nearby regions (warmer color regions in Fig. 2 left panel), and mentioned the initial aftershocks mostly occurred in the regions where we calculated that the Coulomb stress increased. The Jan 3, 2019 M=5.1 shock indeed occurred in one of the stress increased lobes (yellow star in Fig. 2). This lobe experienced an increase in seismicity after the Kumamoto mainshock (Box A in Fig. 3 below).

Figure 3. Epicenters of all earthquakes shallower than 20 km during the period of 2015-2018 (JMA catalog). Although there are several dense clusters that have nothing to do with the Kumamoto earthquake, we nevertheless see that the aftershock zone is extends up to five rupture lengths from the fault (thick black line). The three boxes are where we examined the seismicity over time in Figure 4.

The quake rate doubled in the stress trigger zone of the 2016 Mw=7.0 quake, and dropped by a factor of 5 in its stress shadow.

Given that Japan is such an earthquake-prone country, one could argue that it was simply a random accident that the M=5.1 quake struck in the stress trigger zone. To address this possibility, we first examined the change in earthquake occurrence rate (‘seismicity rate change’) before and after the 2016 Kumamoto earthquake (Fig. 2 right panel). A visual comparison of our Coulomb calculation (Fig. 2 left panel) with seismicity rate change (Fig. 2 right panel) shows they match reasonably well. The epicenter of the 3 January 2019 event is in the red spot on both maps. Furthermore, regions north and south of the 2016 rupture zone, in which the faults were inhibited from failure by the stress changes, indeed show a seismicity decrease.

To make sure that the local seismicity responded to the Kumamoto earthquake and not some other event at roughly the same time, we have chosen three sub-regions (boxes in Fig. 3) and looked at their seismicity time series (Fig. 4). In box A, the number of shocks, most of which are very small, was ~600 a year before the 2016 mainshock. But it has risen by over 2, to ~1500 per year since the mainshock. Thus, the M=5.1 event occurred in the zone of sustained higher rate of seismicity associated with the 2016 Kumamoto earthquake. A similar continuous and long-lasting seismicity increase also occurred in box C (northern Miyazaki Prefecture) where Coulomb stress was also imparted by the mainshock. The opposite response is observed in box B, where Coulomb stress was calculated to have decreased. There, the seismicity plummeted to 1/5 of the pre-Kumamoto level.

Figure 4. Seismic time series in the particular sub-regions, A, B, and C, corresponding to the boxes in Fig. 2 left panel and Fig. 3. The blue line indicates cumulative number of earthquakes since 2015 (with the corresponding blue scale at left), whereas the green stems identify each earthquake time and magnitude (green scale at right). What’s clear is that in all cases, the seismicity rates changed roughly at the time of the 2016 Kumamoto mainshock, and in the manner forecast by the Coulomb stress changes.

There is a caveat that the Japan Meteorological Agency (JMA) has changed their earthquake determination algorithm after April 2016. However, it should have been homogeneously implemented in Kyushu. Since we confirmed the regional-dependent seismic behaviors in Fig. 4, we do not think the increased seismicity in the box A in Fig. 4 is an artifact. We also note that the rate of shallow M≥5 earthquakes under inland Japan (378,000 km2) is roughly about 10 a year. It enables us to say the probability to have one M≥5 quake in the box A (1168 km2) per year is ~3%, and so it is rare enough to make an accidental or coincidental occurrence unlikely.

The long-lasting and far-reaching impact of stress transfer on seismic hazard.

A key lesson learned from this M=5.1 quake is the effect of stress disturbance due to the three-year-old M=7 event continues over a large area in central Kyushu. And even though the size of the January 3 quake is much smaller than the M=7.0, it can nevertheless cause serious damage. Further, aftershocks do not get smaller with time after a mainshock; instead they only get more spaced out in time. So, a larger shock could still strike. The most likely place for such an event is unfortunately the highly-populated Kumamoto city, because there the stress imparted by the 2016 mainshock was greater than anywhere else.


Manabu Hashimoto, Martha Savage, Takuya Nishimura, Haruo Horikawa and Hiroyuki Tsutsumi (2017), Special issue “2016 Kumamoto earthquake sequence and its impact on earthquake science and hazard assessment” Earth, Planets and Space, 69-98,

Headquarters for Earthquake Research Promotion (2019),

IRIDeS (International Research Institute of Disaster Science) (2016),

Ross S. Stein and Volkan Sevilgen (2016), The Tail that Wagged the Dog: M=7.0 Kumamoto, Japan shock promoted by M=6.1 quake that struck 28 hr beforehand

Ross S. Stein and Shinji Toda (2016), How a M=6 earthquake triggered a deadly M=7 in Japan, Temblor

See the full article here .


Please help promote STEM in your local schools.

Stem Education Coalition

Earthquake Alert


Earthquake Alert

Earthquake Network project

Earthquake Network is a research project which aims at developing and maintaining a crowdsourced smartphone-based earthquake warning system at a global level. Smartphones made available by the population are used to detect the earthquake waves using the on-board accelerometers. When an earthquake is detected, an earthquake warning is issued in order to alert the population not yet reached by the damaging waves of the earthquake.

The project started on January 1, 2013 with the release of the homonymous Android application Earthquake Network. The author of the research project and developer of the smartphone application is Francesco Finazzi of the University of Bergamo, Italy.

Get the app in the Google Play store.

Smartphone network spatial distribution (green and red dots) on December 4, 2015

Meet The Quake-Catcher Network

QCN bloc

Quake-Catcher Network

The Quake-Catcher Network is a collaborative initiative for developing the world’s largest, low-cost strong-motion seismic network by utilizing sensors in and attached to internet-connected computers. With your help, the Quake-Catcher Network can provide better understanding of earthquakes, give early warning to schools, emergency response systems, and others. The Quake-Catcher Network also provides educational software designed to help teach about earthquakes and earthquake hazards.

After almost eight years at Stanford, and a year at CalTech, the QCN project is moving to the University of Southern California Dept. of Earth Sciences. QCN will be sponsored by the Incorporated Research Institutions for Seismology (IRIS) and the Southern California Earthquake Center (SCEC).

The Quake-Catcher Network is a distributed computing network that links volunteer hosted computers into a real-time motion sensing network. QCN is one of many scientific computing projects that runs on the world-renowned distributed computing platform Berkeley Open Infrastructure for Network Computing (BOINC).

The volunteer computers monitor vibrational sensors called MEMS accelerometers, and digitally transmit “triggers” to QCN’s servers whenever strong new motions are observed. QCN’s servers sift through these signals, and determine which ones represent earthquakes, and which ones represent cultural noise (like doors slamming, or trucks driving by).

There are two categories of sensors used by QCN: 1) internal mobile device sensors, and 2) external USB sensors.

Mobile Devices: MEMS sensors are often included in laptops, games, cell phones, and other electronic devices for hardware protection, navigation, and game control. When these devices are still and connected to QCN, QCN software monitors the internal accelerometer for strong new shaking. Unfortunately, these devices are rarely secured to the floor, so they may bounce around when a large earthquake occurs. While this is less than ideal for characterizing the regional ground shaking, many such sensors can still provide useful information about earthquake locations and magnitudes.

USB Sensors: MEMS sensors can be mounted to the floor and connected to a desktop computer via a USB cable. These sensors have several advantages over mobile device sensors. 1) By mounting them to the floor, they measure more reliable shaking than mobile devices. 2) These sensors typically have lower noise and better resolution of 3D motion. 3) Desktops are often left on and do not move. 4) The USB sensor is physically removed from the game, phone, or laptop, so human interaction with the device doesn’t reduce the sensors’ performance. 5) USB sensors can be aligned to North, so we know what direction the horizontal “X” and “Y” axes correspond to.

If you are a science teacher at a K-12 school, please apply for a free USB sensor and accompanying QCN software. QCN has been able to purchase sensors to donate to schools in need. If you are interested in donating to the program or requesting a sensor, click here.

BOINC is a leader in the field(s) of Distributed Computing, Grid Computing and Citizen Cyberscience.BOINC is more properly the Berkeley Open Infrastructure for Network Computing, developed at UC Berkeley.

Earthquake safety is a responsibility shared by billions worldwide. The Quake-Catcher Network (QCN) provides software so that individuals can join together to improve earthquake monitoring, earthquake awareness, and the science of earthquakes. The Quake-Catcher Network (QCN) links existing networked laptops and desktops in hopes to form the worlds largest strong-motion seismic network.

Below, the QCN Quake Catcher Network map
QCN Quake Catcher Network map

ShakeAlert: An Earthquake Early Warning System for the West Coast of the United States

The U. S. Geological Survey (USGS) along with a coalition of State and university partners is developing and testing an earthquake early warning (EEW) system called ShakeAlert for the west coast of the United States. Long term funding must be secured before the system can begin sending general public notifications, however, some limited pilot projects are active and more are being developed. The USGS has set the goal of beginning limited public notifications in 2018.

Watch a video describing how ShakeAlert works in English or Spanish.

The primary project partners include:

United States Geological Survey
California Governor’s Office of Emergency Services (CalOES)
California Geological Survey
California Institute of Technology
University of California Berkeley
University of Washington
University of Oregon
Gordon and Betty Moore Foundation

The Earthquake Threat

Earthquakes pose a national challenge because more than 143 million Americans live in areas of significant seismic risk across 39 states. Most of our Nation’s earthquake risk is concentrated on the West Coast of the United States. The Federal Emergency Management Agency (FEMA) has estimated the average annualized loss from earthquakes, nationwide, to be $5.3 billion, with 77 percent of that figure ($4.1 billion) coming from California, Washington, and Oregon, and 66 percent ($3.5 billion) from California alone. In the next 30 years, California has a 99.7 percent chance of a magnitude 6.7 or larger earthquake and the Pacific Northwest has a 10 percent chance of a magnitude 8 to 9 megathrust earthquake on the Cascadia subduction zone.

Part of the Solution

Today, the technology exists to detect earthquakes, so quickly, that an alert can reach some areas before strong shaking arrives. The purpose of the ShakeAlert system is to identify and characterize an earthquake a few seconds after it begins, calculate the likely intensity of ground shaking that will result, and deliver warnings to people and infrastructure in harm’s way. This can be done by detecting the first energy to radiate from an earthquake, the P-wave energy, which rarely causes damage. Using P-wave information, we first estimate the location and the magnitude of the earthquake. Then, the anticipated ground shaking across the region to be affected is estimated and a warning is provided to local populations. The method can provide warning before the S-wave arrives, bringing the strong shaking that usually causes most of the damage.

Studies of earthquake early warning methods in California have shown that the warning time would range from a few seconds to a few tens of seconds. ShakeAlert can give enough time to slow trains and taxiing planes, to prevent cars from entering bridges and tunnels, to move away from dangerous machines or chemicals in work environments and to take cover under a desk, or to automatically shut down and isolate industrial systems. Taking such actions before shaking starts can reduce damage and casualties during an earthquake. It can also prevent cascading failures in the aftermath of an event. For example, isolating utilities before shaking starts can reduce the number of fire initiations.

System Goal

The USGS will issue public warnings of potentially damaging earthquakes and provide warning parameter data to government agencies and private users on a region-by-region basis, as soon as the ShakeAlert system, its products, and its parametric data meet minimum quality and reliability standards in those geographic regions. The USGS has set the goal of beginning limited public notifications in 2018. Product availability will expand geographically via ANSS regional seismic networks, such that ShakeAlert products and warnings become available for all regions with dense seismic instrumentation.

Current Status

The West Coast ShakeAlert system is being developed by expanding and upgrading the infrastructure of regional seismic networks that are part of the Advanced National Seismic System (ANSS); the California Integrated Seismic Network (CISN) is made up of the Southern California Seismic Network, SCSN) and the Northern California Seismic System, NCSS and the Pacific Northwest Seismic Network (PNSN). This enables the USGS and ANSS to leverage their substantial investment in sensor networks, data telemetry systems, data processing centers, and software for earthquake monitoring activities residing in these network centers. The ShakeAlert system has been sending live alerts to “beta” users in California since January of 2012 and in the Pacific Northwest since February of 2015.

In February of 2016 the USGS, along with its partners, rolled-out the next-generation ShakeAlert early warning test system in California joined by Oregon and Washington in April 2017. This West Coast-wide “production prototype” has been designed for redundant, reliable operations. The system includes geographically distributed servers, and allows for automatic fail-over if connection is lost.

This next-generation system will not yet support public warnings but does allow selected early adopters to develop and deploy pilot implementations that take protective actions triggered by the ShakeAlert notifications in areas with sufficient sensor coverage.


The USGS will develop and operate the ShakeAlert system, and issue public notifications under collaborative authorities with FEMA, as part of the National Earthquake Hazard Reduction Program, as enacted by the Earthquake Hazards Reduction Act of 1977, 42 U.S.C. §§ 7704 SEC. 2.

For More Information

Robert de Groot, ShakeAlert National Coordinator for Communication, Education, and Outreach

Learn more about EEW Research

ShakeAlert Fact Sheet

ShakeAlert Implementation Plan