From Eos: “Distant Quake Triggered Slow Slip on Southern San Andreas”

From AGU

From Eos

23 September 2019
Terri Cook

A high-resolution map of surface displacements indicates that the 2017 Chiapas earthquake caused substantial creep along a segment of the San Andreas Fault, located 3,000 kilometers away.

The 2017 magnitude 8.3 Chiapas earthquake caused up to 15 millimeters of creep on the segment of the San Andreas Fault that runs along the northeastern edge of California’s Salton Sea. Credit: USGS/NASA’s Earth Observatory

In the traditional model of the earthquake cycle, a seismic event occurs when an active fault abruptly releases strain that has built up over time. About 20 years ago, however, seismologists began finding that some faults, or sections of faults, can experience slow earthquakes—a gradual type of aseismic slip, or “creep,” that can last for months. Because both types of events release pent-up energy, determining the proportion of seismic versus aseismic slip along active faults is crucial for estimating their potential hazard.

Although conventional interpretations predict that aseismic slip should occur at a roughly constant rate, geodetic observations have shown that at some locations fault creep is anything but steady. Measurements along the southern San Andreas Fault in California, one of the most studied examples of a creeping fault, have shown that this section often experiences bouts of accelerated creep and that these events can be spontaneous or triggered by seismic events. But the underlying conditions and mechanisms that cause slow slip are still poorly understood.

San Andreas Fault. Temblor

Now Tymofyeyeva et al. [JGR Solid Earth] report detailed observations of a slow-slip event that occurred along the southern San Andreas Fault following the magnitude 8.3 earthquake that hit offshore Chiapas, Mexico, in September 2017. The team combined the results of field mapping with creepmeter and Sentinel-1 interferometric synthetic aperture radar observations to create a high-resolution map of surface displacements near the Salton Sea. The researchers then entered the results into numerical models to constrain the crustal properties that could generate the observed behavior.

The results indicated that surface slip along the 40-kilometer-long section between Bombay Beach and the Mecca Hills accelerated within minutes of the Chiapas earthquake and continued for more than a year. The event resulted in total surface offsets that averaged 5-10 millimeters, comparable to the slow slip triggered by the 2010 magnitude 7.2 El Mayor-Cucapah (Baja) earthquake, even though the stress changes along the southern San Andreas due to the Chiapas earthquake were several orders of magnitude lower.

The findings offer compelling evidence that the Chiapas earthquake triggered the 2017 slow-slip event along the southern San Andreas Fault, according to the researchers, and show that although shallow creep near the Salton Sea is roughly constant on decadal timescales, it can vary significantly over shorter periods of time. The authors conclude that the response of the southern San Andreas, and potentially other major faults, to different seismic events is complex and likely reflects crustal conditions as well as local creep history.

See the full article here .

Earthquake Alert

Earthquake Alert

Earthquake Network projectEarthquake 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

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

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.

Authorities

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
rdegroot@usgs.gov
626-583-7225

Learn more about EEW Research

ShakeAlert Fact Sheet

ShakeAlert Implementation Plan

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Eos is the leading source for trustworthy news and perspectives about the Earth and space sciences and their impact. Its namesake is Eos, the Greek goddess of the dawn, who represents the light shed on understanding our planet and its environment in space by the Earth and space sciences.

From LANL via WIRED: “AI Helps Seismologists Predict Earthquakes”

Los Alamos National Laboratory

via

From WIRED

Machine learning is bringing seismologists closer to an elusive goal: forecasting quakes well before they strike.

Remnants of a 2,000-year-old spruce forest on Neskowin Beach, Oregon — one of dozens of “ghost forests” along the Oregon and Washington coast. It’s thought that a mega-earthquake of the Cascadia subduction zone felled the trees, and that the stumps were then buried by tsunami debris.Photograph: Race Jones/Outlive Creative

In May of last year, after a 13-month slumber, the ground beneath Washington’s Puget Sound rumbled to life. The quake began more than 20 miles below the Olympic mountains and, over the course of a few weeks, drifted northwest, reaching Canada’s Vancouver Island. It then briefly reversed course, migrating back across the US border before going silent again. All told, the monthlong earthquake likely released enough energy to register as a magnitude 6. By the time it was done, the southern tip of Vancouver Island had been thrust a centimeter or so closer to the Pacific Ocean.

Because the quake was so spread out in time and space, however, it’s likely that no one felt it. These kinds of phantom earthquakes, which occur deeper underground than conventional, fast earthquakes, are known as “slow slips.” They occur roughly once a year in the Pacific Northwest, along a stretch of fault where the Juan de Fuca plate is slowly wedging itself beneath the North American plate. More than a dozen slow slips have been detected by the region’s sprawling network of seismic stations since 2003. And for the past year and a half, these events have been the focus of a new effort at earthquake prediction by the geophysicist Paul Johnson.

Johnson’s team is among a handful of groups that are using machine learning to try to demystify earthquake physics and tease out the warning signs of impending quakes. Two years ago, using pattern-finding algorithms similar to those behind recent advances in image and speech recognition and other forms of artificial intelligence, he and his collaborators successfully predicted temblors in a model laboratory system—a feat that has since been duplicated by researchers in Europe.

Now, in a paper posted this week on the scientific preprint site arxiv.org, Johnson and his team report that they’ve tested their algorithm on slow slip quakes in the Pacific Northwest. The paper has yet to undergo peer review, but outside experts say the results are tantalizing. According to Johnson, they indicate that the algorithm can predict the start of a slow slip earthquake to “within a few days—and possibly better.”

“This is an exciting development,” said Maarten de Hoop, a seismologist at Rice University who was not involved with the work. “For the first time, I think there’s a moment where we’re really making progress” toward earthquake prediction.

Mostafa Mousavi, a geophysicist at Stanford University, called the new results “interesting and motivating.” He, de Hoop, and others in the field stress that machine learning has a long way to go before it can reliably predict catastrophic earthquakes—and that some hurdles may be difficult, if not impossible, to surmount. Still, in a field where scientists have struggled for decades and seen few glimmers of hope, machine learning may be their best shot.

Sticks and Slips

The late seismologist Charles Richter, for whom the Richter magnitude scale is named, noted in 1977 that earthquake prediction can provide “a happy hunting ground for amateurs, cranks, and outright publicity-seeking fakers.” Today, many seismologists will tell you that they’ve seen their fair share of all three.

But there have also been reputable scientists who concocted theories that, in hindsight, seem woefully misguided, if not downright wacky. There was the University of Athens geophysicist Panayiotis Varotsos, who claimed he could detect impending earthquakes by measuring “seismic electric signals.” There was Brian Brady, the physicist from the US Bureau of Mines who in the early 1980s sounded successive false alarms in Peru, basing them on a tenuous notion that rock bursts in underground mines were telltale signs of coming quakes.

Paul Johnson is well aware of this checkered history. He knows that the mere phrase “earthquake prediction” is taboo in many quarters. He knows about the six Italian scientists who were convicted of manslaughter in 2012 for downplaying the chances of an earthquake near the central Italian town of L’Aquila, days before the region was devastated by a magnitude 6.3 temblor. (The convictions were later overturned.) He knows about the prominent seismologists who have forcefully declared that “earthquakes cannot be predicted.”

But Johnson also knows that earthquakes are physical processes, no different in that respect from the collapse of a dying star or the shifting of the winds. And though he stresses that his primary aim is to better understand fault physics, he hasn’t shied away from the prediction problem.

Paul Johnson, a geophysicist at Los Alamos National Laboratory, photographed in 2008 with a block of acrylic plastic, one of the materials his team uses to simulate earthquakes in the laboratory.Photograph: Los Alamos National Laboratory

More than a decade ago, Johnson began studying “laboratory earthquakes,” made with sliding blocks separated by thin layers of granular material. Like tectonic plates, the blocks don’t slide smoothly but in fits and starts: They’ll typically stick together for seconds at a time, held in place by friction, until the shear stress grows large enough that they suddenly slip. That slip—the laboratory version of an earthquake—releases the stress, and then the stick-slip cycle begins anew.

When Johnson and his colleagues recorded the acoustic signal emitted during those stick-slip cycles, they noticed sharp peaks just before each slip. Those precursor events were the laboratory equivalent of the seismic waves produced by foreshocks before an earthquake. But just as seismologists have struggled to translate foreshocks into forecasts of when the main quake will occur, Johnson and his colleagues couldn’t figure out how to turn the precursor events into reliable predictions of laboratory quakes. “We were sort of at a dead end,” Johnson recalled. “I couldn’t see any way to proceed.”

At a meeting a few years ago in Los Alamos, Johnson explained his dilemma to a group of theoreticians. They suggested he reanalyze his data using machine learning—an approach that was well known by then for its prowess at recognizing patterns in audio data.

Together, the scientists hatched a plan. They would take the roughly five minutes of audio recorded during each experimental run—encompassing 20 or so stick-slip cycles—and chop it up into many tiny segments. For each segment, the researchers calculated more than 80 statistical features, including the mean signal, the variation about that mean, and information about whether the segment contained a precursor event. Because the researchers were analyzing the data in hindsight, they also knew how much time had elapsed between each sound segment and the subsequent failure of the laboratory fault.

Armed with this training data, they used what’s known as a “random forest” machine learning algorithm to systematically look for combinations of features that were strongly associated with the amount of time left before failure. After seeing a couple of minutes’ worth of experimental data, the algorithm could begin to predict failure times based on the features of the acoustic emission alone.

Johnson and his co-workers chose to employ a random forest algorithm to predict the time before the next slip in part because—compared with neural networks and other popular machine learning algorithms—random forests are relatively easy to interpret. The algorithm essentially works like a decision tree in which each branch splits the data set according to some statistical feature. The tree thus preserves a record of which features the algorithm used to make its predictions—and the relative importance of each feature in helping the algorithm arrive at those predictions.

A polarizing lens shows the buildup of stress as a model tectonic plate slides laterally along a fault line in an experiment at Los Alamos National Laboratory.Photograph: Los Alamos National Laboratory.

When the Los Alamos researchers probed those inner workings of their algorithm, what they learned surprised them. The statistical feature the algorithm leaned on most heavily for its predictions was unrelated to the precursor events just before a laboratory quake. Rather, it was the variance—a measure of how the signal fluctuates about the mean—and it was broadcast throughout the stick-slip cycle, not just in the moments immediately before failure. The variance would start off small and then gradually climb during the run-up to a quake, presumably as the grains between the blocks increasingly jostled one another under the mounting shear stress. Just by knowing this variance, the algorithm could make a decent guess at when a slip would occur; information about precursor events helped refine those guesses.

The finding had big potential implications. For decades, would-be earthquake prognosticators had keyed in on foreshocks and other isolated seismic events. The Los Alamos result suggested that everyone had been looking in the wrong place—that the key to prediction lay instead in the more subtle information broadcast during the relatively calm periods between the big seismic events.

To be sure, sliding blocks don’t begin to capture the chemical, thermal and morphological complexity of true geological faults. To show that machine learning could predict real earthquakes, Johnson needed to test it out on a real fault. What better place to do that, he figured, than in the Pacific Northwest?

Out of the Lab

Most if not all of the places on Earth that can experience a magnitude 9 earthquake are subduction zones, where one tectonic plate dives beneath another. A subduction zone just east of Japan was responsible for the Tohoku earthquake and the subsequent tsunami that devastated the country’s coastline in 2011. One day, the Cascadia subduction zone, where the Juan de Fuca plate dives beneath the North American plate, will similarly devastate Puget Sound, Vancouver Island and the surrounding Pacific Northwest.

Cascadia plate zones

Cascadia subduction zone

The Cascadia subduction zone stretches along roughly 1,000 kilometers of the Pacific coastline from Cape Mendocino in Northern California to Vancouver Island. The last time it breached, in January 1700, it begot a magnitude 9 temblor and a tsunami that reached the coast of Japan. Geological records suggest that throughout the Holocene, the fault has produced such megaquakes roughly once every half-millennium, give or take a few hundred years. Statistically speaking, the next big one is due any century now.

That’s one reason seismologists have paid such close attention to the region’s slow slip earthquakes. The slow slips in the lower reaches of a subduction-zone fault are thought to transmit small amounts of stress to the brittle crust above, where fast, catastrophic quakes occur. With each slow slip in the Puget Sound-Vancouver Island area, the chances of a Pacific Northwest megaquake ratchet up ever so slightly. Indeed, a slow slip was observed in Japan in the month leading up to the Tohoku quake.

For Johnson, however, there’s another reason to pay attention to slow slip earthquakes: They produce lots and lots of data. For comparison, there have been no major fast earthquakes on the stretch of fault between Puget Sound and Vancouver Island in the past 12 years. In the same time span, the fault has produced a dozen slow slips, each one recorded in a detailed seismic catalog.

That seismic catalog is the real-world counterpart to the acoustic recordings from Johnson’s laboratory earthquake experiment. Just as they did with the acoustic recordings, Johnson and his co-workers chopped the seismic data into small segments, characterizing each segment with a suite of statistical features. They then fed that training data, along with information about the timing of past slow slip events, to their machine learning algorithm.

After being trained on data from 2007 to 2013, the algorithm was able to make predictions about slow slips that occurred between 2013 and 2018, based on the data logged in the months before each event. The key feature was the seismic energy, a quantity closely related to the variance of the acoustic signal in the laboratory experiments. Like the variance, the seismic energy climbed in a characteristic fashion in the run-up to each slow slip.

The Cascadia forecasts weren’t quite as accurate as the ones for laboratory quakes. The correlation coefficients characterizing how well the predictions fit observations were substantially lower in the new results than they were in the laboratory study. Still, the algorithm was able to predict all but one of the five slow slips that occurred between 2013 and 2018, pinpointing the start times, Johnson says, to within a matter of days. (A slow slip that occurred in August 2019 wasn’t included in the study.)

For de Hoop, the big takeaway is that “machine learning techniques have given us a corridor, an entry into searching in data to look for things that we have never identified or seen before.” But he cautions that there’s more work to be done. “An important step has been taken—an extremely important step. But it is like a tiny little step in the right direction.”

Sobering Truths

The goal of earthquake forecasting has never been to predict slow slips. Rather, it’s to predict sudden, catastrophic quakes that pose danger to life and limb. For the machine learning approach, this presents a seeming paradox: The biggest earthquakes, the ones that seismologists would most like to be able to foretell, are also the rarest. How will a machine learning algorithm ever get enough training data to predict them with confidence?

The Los Alamos group is betting that their algorithms won’t actually need to train on catastrophic earthquakes to predict them. Recent studies suggest that the seismic patterns before small earthquakes are statistically similar to those of their larger counterparts, and on any given day, dozens of small earthquakes may occur on a single fault. A computer trained on thousands of those small temblors might be versatile enough to predict the big ones. Machine learning algorithms might also be able to train on computer simulations of fast earthquakes that could one day serve as proxies for real data.

But even so, scientists will confront this sobering truth: Although the physical processes that drive a fault to the brink of an earthquake may be predictable, the actual triggering of a quake—the growth of a small seismic disturbance into full-blown fault rupture—is believed by most scientists to contain at least an element of randomness. Assuming that’s so, no matter how well machines are trained, they may never be able to predict earthquakes as well as scientists predict other natural disasters.

“We don’t know what forecasting in regards to timing means yet,” Johnson said. “Would it be like a hurricane? No, I don’t think so.”

In the best-case scenario, predictions of big earthquakes will probably have time bounds of weeks, months or years. Such forecasts probably couldn’t be used, say, to coordinate a mass evacuation on the eve of a temblor. But they could increase public preparedness, help public officials target their efforts to retrofit unsafe buildings, and otherwise mitigate hazards of catastrophic earthquakes.

Johnson sees that as a goal worth striving for. Ever the realist, however, he knows it will take time. “I’m not saying we’re going to predict earthquakes in my lifetime,” he said, “but … we’re going to make a hell of a lot of progress.”

See the full article here .

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

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

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.

Authorities

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
rdegroot@usgs.gov
626-583-7225

Learn more about EEW Research

ShakeAlert Fact Sheet

ShakeAlert Implementation Plan

five-ways-keep-your-child-safe-school-shootings

Please help promote STEM in your local schools.

Stem Education Coalition

Los Alamos National Laboratory’s mission is to solve national security challenges through scientific excellence.

Los Alamos National Laboratory, a multidisciplinary research institution engaged in strategic science on behalf of national security, is operated by Los Alamos National Security, LLC, a team composed of Bechtel National, the University of California, The Babcock & Wilcox Company, and URS for the Department of Energy’s National Nuclear Security Administration.

From University or Oregon via EarthSky: “A big earthquake in the US Pacific Northwest?”

From University or Oregon

via

EarthSky

August 5, 2019
Miles Bodmer, University of Oregon
Doug Toomey, University of Oregon

Most people don’t associate the US Pacific Northwest with earthquakes, but maybe they should. It’s home to the 600-mile (1,000-km) Cascadia megathrust fault, stretching from northern California to Canada’s Vancouver Island.

Data derived from NaturalEarthData.com, 10m datasets. Projected into NAD83 UTM 9N. Alicia.iverson

This is the USGS’ scenario ShakeMap for a M9 shock on the Casdadia Subduction Zone. This is not a real event.
23 December 2016
Source Earthquakes Shakemap usCasc9.0_se
Author United States Geological Survey

The Pacific Northwest is known for many things – its beer, its music, its mythical large-footed creatures. Most people don’t associate it with earthquakes, but they should. It’s home to the Cascadia megathrust fault that runs 600 miles (966 km) from Northern California up to Vancouver Island in Canada, spanning several major metropolitan areas including Seattle and Portland, Oregon.

This geologic fault has been relatively quiet in recent memory. There haven’t been many widely felt quakes along the Cascadia megathrust, certainly nothing that would rival a catastrophic event like the 1989 Loma Prieta earthquake along the active San Andreas in California. That doesn’t mean it will stay quiet, though. Scientists know it has the potential for large earthquakes – as big as magnitude 9.

Geophysicists have known for over a decade that not all portions of the Cascadia megathrust fault behave the same. The northern and southern sections are much more seismically active than the central section – with frequent small earthquakes and ground deformations that residents don’t often notice. But why do these variations exist and what gives rise to them?

Our research tries to answer these questions by constructing images of what’s happening deep within the Earth [Geophysical Research Letters Research], more than 90 miles (144 km) below the fault. We’ve identified regions that are rising up beneath these active sections which we think are leading to the observable differences along the Cascadia fault.

Cascadia and the ‘Really Big One’

The Cascadia subduction zone is a region where two tectonic plates are colliding. The Juan de Fuca, a small oceanic plate, is being driven under the North American plate, atop which the continental U.S. sits.

The Juan de Fuca plate meets the North American plate beneath the Cascadia fault. Image via USGS.

Subduction systems – where one tectonic plate slides over another – are capable of producing the world’s largest known earthquakes. A prime example is the 2011 Tohoku earthquake that rocked Japan.

Cascadia is seismically very quiet compared to other subduction zones – but it’s not completely inactive. Research indicates the fault ruptured in a magnitude 9.0 event in 1700. That’s roughly 30 times more powerful than the largest predicted San Andreas earthquake. Researchers suggest that we are within the roughly 300- to 500-year window during which another large Cascadia event may occur.

Many smaller undamaging and unfelt events take place in northern and southern Cascadia every year. However, in central Cascadia, underlying most of Oregon, there is very little seismicity. Why would the same fault behave differently in different regions?

Over the last decade, scientists have made several additional observations that highlight variations along the fault.

One has to do with plate locking, which tells us where stress is accumulating along the fault. If the tectonic plates are locked – that is, really stuck together and unable to move past each other – stress builds. Eventually that stress can be released rapidly as an earthquake, with the magnitude depending on how large the patch of fault that ruptures is.

A GPS geosensor in Washington. Image via Bdelisle.

Geologists have recently been able to deploy hundreds of GPS monitors across Cascadia to record the subtle ground deformations that result from the plates’ inability to slide past each other. Just like historic seismicity, plate locking is more common in the northern and southern parts of Cascadia.

Geologists are also now able to observe difficult-to-detect seismic rumblings known as tremor. These events occur over the time span of several minutes up to weeks, taking much longer than a typical earthquake. They don’t cause large ground motions even though they can release significant amounts of energy. Researchers have only discovered these signals in the last 15 years, but permanent seismic stations have helped build a robust catalog of events. Tremor, too, seems to be more concentrated along the northern and southern parts of the fault.

What would cause this situation, with the area beneath Oregon relatively less active by all these measures? To explain we had to look deep, over 100 kilometers (60 miles) below the surface, into the Earth’s mantle.

Green dots and blue triangles show locations of seismic monitoring stations. Image via Bodmer et al., 2018, Geophysical Research Letters.

Imaging the Earth using distant quakes

Physicians use electromagnetic waves to “see” internal structures like bones without needing to open up a human patient to view them directly. Geologists image the Earth in much the same way. Instead of X-rays, we use seismic energy radiating out from distant magnitude 6.0-plus earthquakes to help us “see” features we physically just can’t get to. This energy travels like sound waves through the structures of the Earth. When rock is hotter or partially molten by even a tiny amount, seismic waves slow down. By measuring the arrival times of seismic waves, we create 3-D images showing how fast or slow the seismic waves travel through specific parts of the Earth.

Ocean bottom seismometers waiting to be deployed during the Cascadia Initiative. Image via Emilie Hooft.

To see these signals, we need records from seismic monitoring stations. More sensors provide better resolution and a clearer image – but gathering more data can be problematic when half the area you’re interested in is underwater. To address this challenge, we were part of a team of scientists that deployed hundreds of seismometers on the ocean floor off the western U.S. over the span of four years, starting in 2011. This experiment, the Cascadia Initiative, was the first ever to cover an entire tectonic plate with instruments at a spacing of roughly 30 miles (50 km).

What we found are two anomalous regions beneath the fault where seismic waves travel slower than expected. These anomalies are large, about 90 miles (150 km) in diameter, and show up beneath the northern and southern sections of the fault. Remember, that’s where researchers have already observed increased activity: the seismicity. Interestingly, the anomalies are not present beneath the central part of the fault, under Oregon, where we see a decrease in activity.

Regions where seismic waves moved more slowly, on average, are redder, while the areas where they moved more quickly are bluer. The slower anomalous areas 90 miles (150 km) beneath the Earth’s surface corresponded to where the colliding plates are more locked and where tremor is more common. Image via Bodmer et al., 2018, Geophysical Research Letters.

So what exactly are these anomalies?

The tectonic plates float on the Earth’s rocky mantle layer. Where the mantle is slowly rising over millions of years, the rock decompresses. Since it’s at such high temperatures, nearly 1500 degrees Celsius (2700 F) at 100 km (60 mi) depth, it can melt ever so slightly.

These physical changes cause the anomalous regions to be more buoyant – melted hot rock is less dense than solid cooler rock. It’s this buoyancy that we believe is affecting how the fault above behaves. The hot, partially molten region pushes upwards on what’s above, similar to how a helium balloon might rise up against a sheet draped over it. We believe this increases the forces between the two plates, causing them to be more strongly coupled and thus more fully locked.

A general prediction for where, but not when

Our results provide new insights into how this subduction zone, and possibly others, behaves over geologic time frames of millions of years. Unfortunately our results can’t predict when the next large Cascadia megathrust earthquake will occur. This will require more research and dense active monitoring of the subduction zone, both onshore and offshore, using seismic and GPS-like stations to capture short-term phenomena.

Our work does suggest that a large event is more likely to start in either the northern or southern sections of the fault, where the plates are more fully locked, and gives a possible reason for why that may be the case.

It remains important for the public and policymakers to stay informed about the potential risk involved in cohabiting with a subduction zone fault and to support programs such as Earthquake Early Warning that seek to expand our monitoring capabilities and mitigate loss in the event of a large rupture.

See the full article here .

Earthquake Alert

Earthquake Alert

Earthquake Network projectEarthquake 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

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

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.

Authorities

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
rdegroot@usgs.gov
626-583-7225

Learn more about EEW Research

ShakeAlert Fact Sheet

ShakeAlert Implementation Plan

five-ways-keep-your-child-safe-school-shootings

Please help promote STEM in your local schools.

Stem Education Coalition

The University of Oregon (also referred to as UO, U of O or Oregon) is a public flagship research university in Eugene, Oregon. Founded in 1876, the institution’s 295-acre campus is along the Willamette River. Since July 2014, UO has been governed by the Board of Trustees of the University of Oregon. The university has a Carnegie Classification of “highest research activity” and has 19 research centers and institutes. UO was admitted to the Association of American Universities in 1969.

The University of Oregon is organized into five colleges (Arts and Sciences, Business, Design, Education, and Honors) and seven professional schools (Accounting, Architecture and Environment, Art and Design, Journalism and Communication, Law, Music and Dance, and Planning, Public Policy and Management) and a graduate school. Furthermore, UO offers 316 undergraduate and graduate degree programs. Most academic programs follow the 10 week Quarter System.

UO student-athletes compete as the Ducks and are part of the Pac-12 Conference in the National Collegiate Athletic Association (NCAA). With eighteen varsity teams, the Oregon Ducks are best known for their football team and track and field program.

From Caltech: Women in STEM “What is it Like to be a Caltech Seismologist During a Big Quake?” Dr. Jennifer Andrews

From Caltech

July 18, 2019
Robert Perkins
(626) 395‑1862
rperkins@caltech.edu

When an earthquake strikes, seismologists at Caltech’s Seismological Laboratory spring into action.

Dr. Jennifer Andrews

An arm of Caltech’s Division of Geological and Planetary Sciences (GPS), the Seismo Lab is home to dozens of seismologists who collaborate with the United States Geological Survey (USGS) to operate one of the largest seismic networks in the nation.Together, they analyze data to provide the public with information about where the quake occurred and how big it was. That information not only helps first responders, but feeds into the scientific understanding on earthquakes and when and where the next big quicks are likely to strike.

After the two largest Ridgecrest earthquakes on July 4 and 5 (Magnitude 6.4 and 7.1, respectively), Caltech staff seismologist Jen Andrews was part of the Seismo Lab team that rushed to respond. Recently, she described that experience.

Where were you when the earthquakes hit?

For Thursday’s quake, I was at home in my shower. I didn’t even realize at the time that it was a quake. But when I got out and looked at my computer, I saw the report. Then the phone rang, and it was Egill [Hauksson, research professor of geophysics at Caltech], saying it was time to go to work. It was all hands on deck.

For Friday’s quake, I was at the ballet at the Dorothy Chandler Pavilion in Downtown Los Angeles. They’d just finished act 1 and were in intermission, so fortunately no dancers were on stage to be knocked off their feet. I was in the balcony, so the movement I felt was probably amplified by the height (and also the soft sediment beneath Downtown). The chandeliers were swaying, but no one panicked. As soon as I felt it shake, I started counting. We felt it as a roll, so I knew the epicenter wasn’t right beneath us. Once I reached 20 seconds, I knew this was a big earthquake, even bigger than the first one. I immediately got in a taxi and headed straight to campus.

What did you do next?

Here at the Seismo Lab, it’s our responsibility to verify that all of the info we’re putting out about earthquakes—the locations and magnitudes, for example—are correct. We’re responsible for getting info about the origin out within two minutes of the shaking, so we have fully automated systems that send updates to the National Earthquake Information Center right away. All of that happens without anyone touching anything, before we can even get to our desks. But once we get there, we look at the waveforms and make sure that we’re correctly identifying the P and S waves. [During an earthquake, several types of seismic waves radiate out from the quake’s epicenter, including compressional waves (or P-waves), transverse waves (or S-waves), and surface waves.] We also know the speed at which seismic waves should travel, so we can use that to make sure that we’re correctly identifying where the quake originated. It turns out that the automatic systems did a brilliant job of getting most of the information correct.

What is it like to be in the Seismo Lab after a big earthquake?

It’s very busy. There’s a lot of people: seismologists, news reporters, even curious students and people who are on campus who just want to know what’s going on. Meanwhile, we have a lot of issues to deal with: we have seismologists on the phone with state representatives and others speaking to members of the press, while still others are trying to process data coming in from seismometers. Within a few hours of a quake, the USGS tries to figure out who’s going out to the location of the earthquake, and what equipment they’ll be taking. For the Ridgecrest quakes, they did flyovers in a helicopter looking for ruptures, and then sent people on the ground to measure the rupture. They then deployed additional seismometers so that we could get an even clearer picture of any aftershocks.

How long after the earthquake will things stay busy for you?

The media attention relaxes after a few hours or days, but I’m going to be looking at the data we gathered from these quakes for a long time. I was here every day over the holiday weekend and the following week working on it. It could take months or even years for our group to process all the data.

Do you learn more from big earthquakes like these than you do from little ones?

You learn different things. The data will be incorporated into earthquake hazard models, though likely will not make big changes. But these quakes in particular were interesting, as two perpendicular faults were involved. We can study the rupture dynamics, which you can’t resolve in smaller quakes. Also, having two strong quakes caused variations in fault slip and ground motion that will be important to study and understand.

See the full article here .

Earthquake Alert

Earthquake Alert

Earthquake Network projectEarthquake 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

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

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.

Authorities

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
rdegroot@usgs.gov
626-583-7225

Learn more about EEW Research

ShakeAlert Fact Sheet

ShakeAlert Implementation Plan

five-ways-keep-your-child-safe-school-shootings
Please help promote STEM in your local schools.

Stem Education Coalition

The California Institute of Technology (commonly referred to as Caltech) is a private research university located in Pasadena, California, United States. Caltech has six academic divisions with strong emphases on science and engineering. Its 124-acre (50 ha) primary campus is located approximately 11 mi (18 km) northeast of downtown Los Angeles. “The mission of the California Institute of Technology is to expand human knowledge and benefit society through research integrated with education. We investigate the most challenging, fundamental problems in science and technology in a singularly collegial, interdisciplinary atmosphere, while educating outstanding students to become creative members of society.”

Caltech campus

From temblor: “The Ridgecrest earthquakes: Torn ground, nested foreshocks, Garlock shocks, and Temblor’s forecast”

From temblor

July 9, 2019
Chris Rollins, Ph.D.; Michigan State University

By Chris Rollins, Ph.D., Michigan State University; Ross S. Stein, Ph.D., Temblor; Guoqing Lin, Ph.D., Professor of Geophysics, University of Miami; and Deborah Kilb, Ph.D., Project Scientist, Scripps Institution of Oceanography, University of California San Diego

A new image of the ground deformation, a rich and enigmatic foreshock sequence, aftershock trends we can explain, and others that are more elusive. This is also the time see how Temblor app’s hazard forecast for Ridgecrest fared.

Citation: Chris Rollins, Ross S. Stein, Guoqing Lin, and Deborah Kilb (2019), The Ridgecrest earthquakes: Torn ground, nested foreshocks, Garlock shocks, and Temblor’s forecast, Temblor, http://doi.org/10.32858/temblor.039

Ground Deformation from Space

The Advanced Rapid Imaging and Analysis (ARIA) team at NASA JPL and Caltech just released this Interferometric Synthetic Aperture Radar (InSAR) image that shows how the fault slip in the 4 July M 6.4 and 5 July M 7.1 earthquakes warped the earth’s surface. We have annotated the map to highlight its remarkable features: knife-edge faulting in the south, and a widely distributed band of secondary faults and shear in the north. That broad pattern of deformation may explain why geologists had missed the fault in the first place: it masquerades as hundreds of small, discontinuous tears at the surface. By using this image and others like it that will come in as more radar satellites pass over the Ridgecrest area, we can study how the slip in these earthquakes was distributed at depth, why the fault may have slipped that way, and what that might mean for how earthquakes occur in general.

The interferogram is derived from the ALOS-2 satellite, operated by the Japan Aerospace Exploration Agency (JAXA), with images taken before (16 April 2018) and after (8 July 2019) the earthquakes. Each color cycle represents 11.45 cm (4.5 inches) of ground displacement in the radar line-of-sight (28° from vertical and roughly east).

JAXA ALOS-2 satellite aka DAICH-2

Foreshocks of foreshocks

When we look how the earthquake sequence unfolded in time, we see what we might call ‘nested foreshocks.’ First, a M 4.0 struck 30 min before the M 6.4 mainshock in virtually the same location. Rare, but not unprecedented. About 18 hours into the M 6.4 aftershock sequence, the largest aftershock, a M 5.3 event struck. Then, about 16 hours later, the M 7.1 ruptured less than 3 km from the site of the M 5.3. That’s also rare. But while fascinating, we don’t see much that marks those little shocks for future greatness.

Here are the quakes in time. This plot is preliminary, as the locations will ultimately be improved, and many of the small quakes that struck soon after the mainshocks will be recovered. Thinking about this sequence was inspired by Derek Watkins from the New York Times.

Aftershocks in the Coso Volcanic Field and on the Garlock Fault: Cause for concern?

The Coso Volcanic Field, an area northwest of the earthquake with a history of seismic swarms, has lit up in earthquakes since the 7.1 quake. Over the past 48 hours, aftershocks have also begun to show up along parts of the Garlock Fault to the southwest. Can we explain these observations?

One can see 8-10 small shocks on the Garlock Fault (lower left), and a large cluster at Coso Volcanic Field (upper left).

When an earthquake ruptures a fault, it warps the surrounding earth (as captured by the satellite image above) and therefore changes the state of stress in the earth around it, including along nearby faults. These stress changes can push some faults closer to failure and pull others further from it, depending on where they are with respect to the earthquake. In the plot below, we calculated what the M 7.1 shock might have done to the major mapped faults in the region and others oriented like them. All else being equal, we would expect aftershocks to be more numerous around faults brought closer to failure by the stress changes in the M 7.1 shock (the red zones below), and less prevalent along faults inhibited from failure (the blue ‘stress shadows’).

Faults in the red lobes are calculated to be brought closer to failure; those in the blue ‘stress shadows’ are inhibited from failure. The calculation estimates what the dominant fault orientations are around the earthquakes by interpolating between major mapped faults (shown in red lines). So, we would expect strong stressing in the Coso Volcanic Field to the north (where the aftershocks lie), and along the Garlock Fault to the south (but not where most of them lie).

We see that the the 7.1 quake likely brought faults in the Coso Volcanic Field closer to failure, consistent with the abundant aftershocks there. But although the quake also strongly increased the Coulomb stress on a 30-km (20-mile) stretch of the Garlock, most of the aftershocks along the Garlock have in fact appeared in a blue zone to the southwest. Satellite radar imagery spanning several years before these quakes suggests the Garlock may be slowly creeping in the blue zone [Tong et al., 2013], which if real could play into seismicity there, but that signal is within the noise level of the dataset. Satellite radar imagery and other geodetic (surface deformation) data and field observations will help piece together what has been going on, not only near the Garlock but everywhere in and around the Ridgecrest sequence.

This calculation differs from the one above in that the stress changes are calculated on faults that are perfectly oriented for failure under the regional stress direction, which is north-south compression and east-west extension.

It is also possible that some of those aftershocks to the southwest didn’t actually occur on the Garlock, but instead on smaller nearby faults that are more optimally oriented for failure under the current tectonic stressing that drives the Eastern California Shear Zone. (The Garlock, for its part, has been rotated severely out of alignment with the regional stress direction, so exactly how much and how often it still slips is a topic of ongoing research.) The above plot shows that faults with this more optimal orientation would have in fact been slightly promoted for failure by the Ridgecrest quake down around where those aftershocks are occurring. We see that faults oriented like this in the Coso region would also have been in

Time history at Coso shows a mystery: The M 6.4 shock had no effect, but the M 7.1 produced abundant shocks.

A closer look at Coso shows that, intriguingly, it was quiet after the M 6.4 4th of July earthquake, but began to light up in earthquakes as soon as the M 7.1 hit on July 5. That might be because the 7.1 was a much larger earthquake and induced larger Coulomb stress changes there; it might alternatively (or also) be because the throughgoing seismic waves from the 7.1 shook Coso harder. We note that a M 7.5 earthquake in Ecuador earlier this year may have also been correlated with a temporary uptick in seismicity in Coso, but two other large remote earthquakes don’t look like they were. This effect, called remote triggering, has been observed in various parts of the world following several large earthquakes in the past 25 years, but studies differ on whether it is characteristic of the Coso region [Castro et al., 2017; Zhang et al., 2017]. Nevertheless, with more in-depth research, we can use the Ridgecrest sequence and Coso aftershocks as a natural experiment that helps shed light on what controls earthquake behavior there – and therefore what may control it in general.

How useful was Temblor in offering guidance to Ridgecrest residents?

Temblor gives three condensed forecasts in one screen. Here it is, slightly annotated:

Temblor app screen for Ridgecrest, California (app.temblor.net/)

– Earthquake Score is 40, which is based on the most current ‘probabilistic’ USGS model. A score of 100 means probable damage of 20% of the replacement cost of a home in 30 years. The score factors in all quakes large and small, near and far, and the amplification of shaking in basins. For comparison, the score is 65 in downtown Los Angeles, and 95 in San Bernardino.

– Lifetime quake is M 6.4. This is the earthquake magnitude that has a 1% chance per year of occurring within 60 mi (100 km); that’s a 60% chance of occurring if you live to 90. It was certainly exceeded, and this tells us that a M 7.1 here is rare. The lifetime quake is M 6.7 for L.A., and M 6.8 for San Bernardino.

– Possible quake is M 6.9. Temblor finds the USGS ‘scenario’ earthquake that produces the strongest shaking at your location and reports its magnitude, fault, and the shaking. Temblor then estimates the cost of repairing the damage to your home in this quake, based on your home’s characteristics. For L.A., it is M 7.0, and for San Bernardino, it is M 7.7. Although the shaking estimate is for a nearby fault with a lower magnitude, it turns out to be spot on: The forecast peak shaking was 55% g (55% of the force of gravity) and the observed was 57%.

Why do we give you two quake magnitudes? (in this case, M 6.4 and M 6.9). The first is the quake size you will more likely than not experience in your lifetime, the second is the largest that the USGS considers possible at your location. On July 5, both were exceeded, but the forecasted shaking nevertheless turned out to be prescient.

In short, while earthquakes will continue to surprise us, their shaking doesn’t have to. Take this opportunity and understand your risk.

References

Castro, R. R., Clayton, R., Hauksson, E., & Stock, J. (2017). Observations of remotely triggered seismicity in Salton Sea and Coso geothermal regions, Southern California, USA, after big (MW> 7.8) teleseismic earthquakes. Geofísica internacional, 56(3), 269-286.

Tong, X., Sandwell, D. T., & Smith‐Konter, B. (2013). High‐resolution interseismic velocity data along the San Andreas fault from GPS and InSAR. Journal of Geophysical Research: Solid Earth, 118(1), 369-389

Zhang, Q., Lin, G., Zhan, Z., Chen, X., Qin, Y., and Wdowinski, S. (2017). Absence of remote earthquake triggering within the Coso and Salton Sea geothermal production fields. Geophys. Res. Lett., doi:10.1002/2016GL071964.

See the full article here .

five-ways-keep-your-child-safe-school-shootings

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

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

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.

Authorities

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
rdegroot@usgs.gov
626-583-7225

Learn more about EEW Research

ShakeAlert Fact Sheet

ShakeAlert Implementation Plan

From temblor: “Large earthquake on Japan’s west coast points to a profound shortcoming in the national seismic hazard model”

From temblor

June 24, 2019
Sara E. Pratt, M.A., M.S.
@Geosciencesara

On Tuesday, June 18, 2019, a magnitude-6.4 quake struck the west coast of Honshu along the eastern Sea of Japan. The quake was shallow — 12 kilometers (7.5 miles) deep — and only 6 kilometers (3.7 kilometers) offshore, according to the U.S. Geological Survey. Its proximity to the cities of Tsuruoka and Sakata, both of which have populations of about 100,000, meant many were exposed to shaking. No one was killed, 21 people were injured, and despite the shallow depth, infrastructure damage was minimal. But the quake was a reminder that this region has experienced several large inland quakes over the last 15 years, and could again. In fact, two magnitude-6.8 earthquakes struck near the hypocenter of this week’s quake in Niigata in 2004 and 2007. The 2004 Niigata-Chuetsu quake killed 40 people, injured 3,000 and damaged more than 6,000 homes, and the 2007 Niigata quake killed seven people, injured more than 830 and destroyed 500 houses.

In the hours that followed the June 18 Tsuruoka quake, aftershocks ranging from magnitude-2.7 to magnitude-4.1 were recorded around Yamagata and Niigata. Credit: HI-Net/NIED

“The tectonic situation, epicenter offshore near the coast, and the size of the quakes are quite similar,” says Prof. Shinji Toda, a geophysicist at the International Research Institute of Disaster Science at Tohoku University who studies inland quakes.

Crucially, the hazard of large earthquakes striking off the coasts of Yamagata and Niigata prefectures is being underestimated by Japan’s national earthquake hazard models, according to some seismologists.

“The government is underestimating the probability of magnitude-7.5 to -7.8 events along the eastern Sea of Japan,” says Prof. Toda. “It misleads the general public [that] we will not have any large events near the coast of Yamagata and Niigata.”

The June 18 thrust fault rupture (where the crust is being compressed horizontally) occurred on the eastern margin of the Sea of Japan in a seismic zone where numerous active faults accommodate the strain of east-west crustal shortening transmitted from the subduction of the Pacific Plate, says Prof. Toda.

During the past 5-25 million years (the Miocene epoch), this region underwent ‘backarc’ extension (stretching), opening what is now the eastern Sea of Japan. Those tensional faults have now been reactivated, with their sense of slip reversed, as thrust faults. Thus, “the hazard of inland large quakes is always high,” Prof. Toda says.

Although the country’s east coast, where the Pacific Plate subducts beneath the North American and Eurasian plates in the Japan Trench, is more prone to large thrust quakes like the March 2011 magnitude-9 Tohoku megathrust quake, the west coast of Japan also is quite seismically active, a fact that is not being adequately accounted for in Japan’s earthquake hazard model, says geophysicist and Temblor CEO Ross Stein.

When compared to Japan’s national earthquake model, the GEAR model indicates a higher rate of earthquake activity on the eastern margin of the Sea of Japan, with a significant lifetime likelihood of experiencing a magnitude-7 or -7.5 quake.

Japan’s earthquake hazard models are released by the Japan Seismic Hazard Information Station (J-SHIS). The J-SHIS model uses inputs based on known faults, historical quakes and assumes fairly regular recurrence intervals. It has been criticized for underestimating the hazard of future the Tohoku quake, whose tsunami killed more than 18,000 people.

Scientists and officials in “Japan have done their very best to create a model that they think reflects future earthquake occurrence based on the expectation of regularity in the size and recurrence behavior of earthquakes. They have also built in the expectation that the longer it’s been since the last large earthquake, the more likely the next one is,” Stein says.

The J-SHIS model thus anticipates a strong likelihood that the next megaquake will occur in the Nankai Trough, off the southeast coast of Honshu, where two deadly magnitude-8.1 quakes struck in the 1940s. The 1944 Tōnankai and the 1946 Nankaidō quakes both triggered tsunamis and killed more than 1,200 and 1,400 people, respectively. “The Japanese model is putting all of its weight on this area, southeast of Tokyo and Nagoya,” Stein says.

Another model, the Global Earthquake Activity Rate (GEAR) forecast, that was developed by a team from UCLA, University of Nevada Reno, and Temblor, and is used in the Temblor app, indicates that quakes on the west coast of Honshu could likely reach magnitude-7 or magnitude-7.5 in the typical resident’s lifetime.

Unlike traditional earthquake hazard models, GEAR does not include active faults or historical earthquakes, which are not uniformly available around the globe. Instead, GEAR takes a global approach that uses only two factors: the stress that drives quakes (measured by GPS) and the events that release that stress, represented in the model by a complete global record of all quakes greater than magnitude-5.7 that have occurred over the past 40 years (from the Global CMT catalog).

“What the GEAR model says is that the Tohoku coast is a lot more likely to produce a large earthquake than the Japan Sea side, but the Japan Sea side is still quite active,” Stein says. “It should produce large earthquakes and has.”

Significant historical earthquakes in the shear zone along the eastern Sea of Japan include the 1964 magnitude-7.5 Niigata earthquake, the 1983 magnitude-7.7 Nihonkai-Chubu earthquake and the 1993 magnitude-7.8 Hokkaido-Nansei-Oki earthquake.

References

USGS Event Pages – https://earthquake.usgs.gov/earthquakes/eventpage/us600042fx/executive

https://earthquake.usgs.gov/earthquakes/eventpage/us600042fx/pager

Bird, P., D. D. Jackson, Y. Y. Kagan, C. Kreemer, and R. S. Stein (2015). GEAR1: A global earthquake activity rate model constructed from geodetic strain rates and smoothed seismicity, Bull. Seismol. Soc. Am. 105, no. 5, 2538–2554.

Toda and Enescu, (2011). Rate/state Coulomb stress transfer model for the CSEP Japan seismicity forecast. Earth, Planetary and Science, 63: 2. https://doi.org/10.5047/eps.2011.01.004 https://link.springer.com/article/10.5047/eps.2011.01.004

See the full article here .

five-ways-keep-your-child-safe-school-shootings

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

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

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.

Authorities

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
rdegroot@usgs.gov
626-583-7225

Learn more about EEW Research

ShakeAlert Fact Sheet

ShakeAlert Implementation Plan

From Eos: “Monitoring Haiti’s Quakes with Raspberry Shake”

From AGU

From Eos

17 May 2019
By Eric Calais, Dominique Boisson, Steeve Symithe, Roberte Momplaisir, Claude Prépetit, Sophia Ulysse, Guy Philippe Etienne, Françoise Courboulex, Anne Deschamps, Tony Monfret, Jean-Paul Ampuero, Bernard Mercier de Lépinay, Valérie Clouard, Rémy Bossu, Laure Fallou, and Etienne Bertrand

A woman displays a Raspberry Shake seismometer. Poor-quality construction, typical of many neighborhoods in Haiti, is visible in the background. A pilot project to create a network of these personal seismometers across Haiti aims not only to provide earthquake data but also to involve citizens in earthquake awareness and hazard mitigation efforts. Credit: E. Calais

On 12 January 2010, a devastating earthquake put Haiti on the map for many of us who were unaware of the recurrent difficulties that the country has endured over the past decades. The earthquake claimed more than 200,000 lives, and the damage amounted to about $11 billion, close to 100% of the country’s gross domestic product.

Before the earthquake, Haiti had no seismic network, no in-country seismologist, no active fault map, no seismic hazard map, no microzonation, and no building code. The national seismic network that has emerged since then currently consists of 10 broadband stations (Figure 1) [Seismological Research Letters ], operated and maintained by Haiti’s Bureau of Mines and Energy (BME). Although this network was a significant step in the right direction, it has not proved to be a panacea.

Fig. 1. Seismic stations in Haiti (symbols) and seismic activity as reported by the U.S. Geological Survey (white circles) from August 1946 to 14 January 2019. Natural Resources Canada (NRCan) broadband station PAPH (red circle), based in Port-au-Prince, is usually operational. The nine Raspberry Shake stations shown on this map (with their code names) were installed in January 2019 and were operational as of 15 February. The yellow star east of Port-au-Prince indicates the location of the M3.1 earthquake shown in Figure 3. Stations RE7D0, RE87E, and R2ABA, which use Wi-Fi to connect to the Internet, are not observing the radio frequency interference noted by some RS hosts elsewhere who also use Wi-Fi to connect to the Internet. BME is Haiti’s Bureau of Mines and Energy, which operates seismic instruments from two manufacturing companies.

On 6 October 2018, a magnitude 5.9 earthquake struck northwestern Haiti, causing 17 fatalities and significant damage in the larger cities of the epicentral area. Only one seismic station was operating at the time, a situation that has persisted for several years now. In spite of its continued efforts, it is difficult for the BME to overcome the chronic lack of resources—financial and human—necessary to maintain such a high-technology system.

This is where Raspberry Shake (RS) comes into play [Anthony et al., 2018 (Seismological Research Letters)]. This organization, founded using a Kickstarter campaign in 2016, provides affordable “personal seismometers” powered by small Raspberry Pi computers. The low cost of an RS station and the ease of installation and maintenance make it possible to imagine a situation in which perhaps as many as 100 citizens, businesses, or schools throughout Haiti would host an RS station.

To do more than just imagine, we began a pilot project last January, purchasing and deploying nine one-component vertical velocimeters (RS1D) throughout Haiti (Figure 1), four of them additionally equipped with 3-D accelerometers (RS4D). Except for one station located at the BME, all RS hosts are private homes or hotels. We selected these hosts from people whom we knew had quasi-continuous Internet access and electricity, the latter being a major issue in Haiti. This initiative is similar to the Quake Catcher Network [see below] [Cochran et al., 2009 (Seismological Research Letters)], although the latter uses only accelerometers.

Overcoming Limited Resources

As a result of resource limitations, seismologists in Haiti are able to provide only limited information to the public or to decision-makers when earthquakes are felt. This reinforces the ill-founded perception that seismic monitoring is of little value, and it keeps the population in the dark about seismic hazard. As a result, citizens and businesses do little to protect themselves from future large events. The lack of reliable information also provides ground for fake seismonews, including the notion that earthquake prediction has already been around for years so that earthquake monitoring is irrelevant.

Interestingly, however, the public demands reliable information about earthquakes and tsunamis and their associated risks. They ask questions, want to be informed, and want to know how to prepare. Some would even like to be able to help improve earthquake knowledge in Haiti.

A citizen’s network of small, affordable seismic stations could be a starting place for providing this information. Even though RS instruments would most likely be concentrated in major cities, their redundancy would alleviate inevitable maintenance issues at any single station. Such a network would improve the ability of the Haiti seismic network to detect small-magnitude earthquakes on a continuous basis, resulting in a better understanding of earthquake distribution and fault behavior. In addition, installing seismometers in people’s homes may be a way to initiate a conversation with the population to promote a culture of earthquake safety.

Setting Up the Network

Raspberry Shake setup at station R897D in Jacmel (see Figure 1) uses an RS1D instrument located on the first floor of a public notary’s office, under “made-on-the-spot” wooden protection. The RS station is connected to secure power and to the Internet through an Ethernet cable to the router visible on the windowsill. From left to right are Berthony (technician from the Haiti Bureau of Mines and Energy); Mrs. Beaulieu, who hosts the station; and authors Eric Calais and Steeve Symithe. Credit: E. Calais

We set about creating our RS network by simply laying an RS instrument on the floor of the quietest first-story room we could find at each location. We connected them to power and Internet utilities, in six cases directly to the router via an Ethernet cable and in three cases via Wi-Fi. We made it clear to the hosts that the RS stations would use very little power and Internet bandwidth but that they should contact us if they suspected any issue. We also told them that they were free to disconnect the RS in case of a problem.

Several hosts asked whether their RS could serve to predict earthquakes or whether they would sound an alarm if seismic waves were coming. We made it very clear that this was not the case and explained that we were mostly interested in the smaller earthquakes: the ones they never feel but that occur every day.

“What? There are earthquakes every day in Haiti?” was a common reaction. Yes, indeed, we told our hosts, and knowing where and how big the small quakes are tells us a lot about the future large ones. Many hosts asked how they could see the information. We showed them how to view the helicorder (which records data from the seismometer) from their smartphone or computer on their local network, but often, they were not impressed with the displays. Helicorder output is indeed difficult to read because most squiggles are not earthquakes. Clearly, we need to do more work on how to provide relevant and useful information to RS station hosts.

First Observations

Three weeks after the installation of the first RS, we could already make a few observations that will be useful for the next phase of our project and, we hope, for other similar projects elsewhere.

We have detected many events that occurred less than 100 kilometers from this first RS station. The first one (Figure 2), recorded on 13 January 2019, was later located by the seismological network of the Dominican Republic, which quoted its magnitude as 3.1. We also recorded a sequence of four events in northwestern Haiti the day after we installed another station; these events were not reported by any regional seismic network. Regional events show up very well too, for example, the M5.3 earthquake that struck the Dominican Republic on 4 February 2019. Even the P wave and S wave arrivals of teleseismic (distant) events are recorded, including an M5.6 earthquake that occurred in Colombia on 26 January 2019.

Fig. 2. Station R30E2, located in downtown Pétion-Ville, produced Haiti’s first Raspberry Shake station recording of a local earthquake on 13 January 2019. This event was not reported by Haiti’s national seismic network, but it was later reported by the Dominican Republic seismic network as an M3.1 event (yellow star in Figure 1) along the Enriquillo–Presqu’île du Sud fault close to the border between Haiti and the Dominican Republic.

Noise levels are, of course, very different from station to station, unless tight seismological prescriptions are enforced. However, that is not the point of using low-cost RS stations at individual homes, businesses, or schools. Our hope is that the redundancy of RS stations within a small footprint—a city—will suffice to ensure the availability of enough reliable data. This remains to be investigated in a quantitative manner as more stations come online.

We noticed that reliability and continuity of service are an issue, even though we tried our best to place the RS instruments at locations with continuous power and reliable Internet. One RS station host wanted to negotiate communication costs and, after a few days, apparently disconnected his station. Another station, located in a power-secure part of Port-au-Prince that had not previously needed power backup, is now experiencing regular blackouts. This underscores the importance of observation redundancy, with many stations at short distances from each other, because one never knows which one will have an issue and stop operating when an interesting earthquake shows up.

A Work in Progress

We were positively impressed by the response of civil society members and the private sector to this initiative. However, to gain the support of civil society, it is clear that we need to provide RS hosts with personalized information, such as “your RS instrument detected an earthquake of magnitude 2.5 located 50 kilometers away, in the area of….” A smartphone application would be a great way to provide this information in quasi-real time and keep station hosts engaged. It could also serve to broadcast information on earthquake preparedness and hence use the (fortunately long!) time intervals between large earthquakes to educate and promote earthquake safety.

With the lessons learned during this pilot experiment, our goal now is to push forward and engage the civil society and the private sectors—at least those entities that can afford continuous power and Internet—to be a bigger part of this project. Expanding the project would provide more RS stations and thus redundancy and continuity of service. It would also engage RS hosts in a project that puts them at the center of the information chain. RS hosts will become information providers to scientists rather than passive listeners to scarce and unintelligible information.

It is our hope that as RS hosts and others become more aware of the earthquake issue, they will share information they will be privy to. We hope that they will become advocates for seismic monitoring, but more important, we hope that they will act to reduce seismic risk for themselves and their community.

Acknowledgments

This pilot activity is funded by the Interreg Caraibes/European Regional Development Fund (FEDER) program through the PREST (vers la Plateforme Régionale de Surveillance Tellurique du Futur) project, the Centre National de la Recherche Scientifique/French Institute for Research and Development (IRD) Risques Naturels program, and the Jeune Equipe Associée of the IRD. All data from the RS stations installed in Haiti are openly available via the Raspberry Shake International Federation of Digital Seismograph Networks (FDSN) web services. We thank Maurice Lamontagne and two anonymous reviewers for their constructive comments.

References

Anthony, R. E., et al. (2018), Do low‐cost seismographs perform well enough for your network? An overview of laboratory tests and field observations of the OSOP Raspberry Shake 4D, Seismol. Res. Lett., 90(1), 219–228, https://doi.org/10.1785/0220180251.

Bent, A. L., et al. (2018), Real‐time seismic monitoring in Haiti and some applications, Seismol. Res. Lett., 89(2A), 407–415, https://doi.org/10.1785/0220170176.

Cochran, E. S., et al. (2009), The Quake-Catcher Network: Citizen science expanding seismic horizons, Seismol. Res. Lett., 80(1), 26–30, https://doi.org/10.1785/gssrl.80.1.26.

See the full article here .

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Please help promote STEM in your local schools.

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Eos is the leading source for trustworthy news and perspectives about the Earth and space sciences and their impact. Its namesake is Eos, the Greek goddess of the dawn, who represents the light shed on understanding our planet and its environment in space by the Earth and space sciences.

Earthquake Alert

Earthquake Alert

Earthquake Network projectEarthquake 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

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

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.

Authorities

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
rdegroot@usgs.gov
626-583-7225

Learn more about EEW Research

ShakeAlert Fact Sheet

ShakeAlert Implementation Plan

From temblor: “Did the Moon trigger Saturday’s M=6.1 earthquake in Colombia?”

From temblor

March 27, 2019
Aron Mirwald, M.Sc., Temblor, Inc.

A magnitude 6.1 earthquake occurred on 23 March 2019 at 2:14 pm in Colombia. A recent scientific paper reports that the tide might be responsible for 16% of the earthquakes in Colombia. But did the Moon trigger this earthquake? Possibly, but there are important limitations.

Colombia’s hyperactive Cauca Cluster and Bucaramanga Nest

The M=6.1 quake, which was widely felt in Bogota, Cali, and Medellin, was located in the well-known ‘Cauca cluster’ in Colombia, where M≥3 earthquakes occur frequently (~24 per year). Together with the ‘Bucaramanga nest’ (~550 per year), the two clusters account for over half of all Colombian earthquakes (Geological Service Colombia). Most of the earthquakes in the two clusters strike at depths between 70-180 km (43 -111 mi). How earthquakes can be produced at these great depths is itself an enigma, and a matter of ongoing research (read this and this for an introduction).

But, as for many geoscience problems, there is more to it: Researchers from the Medellin University have found that earthquakes in Colombia correlate with the tide. They show in their recent publication that the relation between earthquakes and tide is especially strong for earthquakes within the two earthquake clusters (Monaco et. al., 2019).

Each dot represents an earthquake. The colored dots are corresponding to earthquakes in seismic clusters. The upper two are the Cauca cluster and Bucaramanga nest, where over half of the earthquakes in Colombia occur.

The Moon and the Sun cause the Earth to deform

Maybe you have heard that we are slightly lighter when the moon is above us (only one millionth of our weight). But, to be exact, this is also true if the moon is directly below us, at the opposite side. The reason for this is that the gravitational force is not the only force at play. The earth is moved by the moon circling around it, and we experience a centrifugal force because of this (here is a webpage with a great animation of this). The net force is upwards both at the side that faces the moon and at the opposite one.

Both Moon and Earth move in ellipses due to the force they exert on each other. The white arrows represent the net force, i.e. the sum of the centrifugal force and the gravitational force.
Image from http://beltoforion.de (interactive animation)

The moon is not the only one who influences the earth. The sun does it in a similar way, although the force it generates is about half as large. The combined effect of the Sun and the Moon is called ‘tide’. The tide has two effects on the earth. First, it moves large quantities of water, also known as ocean tide. Second, it deforms the solid earth: The tidal forces, that pull on both sides, elongate the planet, making it around 40 cm longer. This generates shear and unclamping stresses in the earth that can promote earthquakes (Heaton, 1975).

The magnitudes of the stresses generated by the tide are much smaller than stresses due to the movement of the tectonic plates. This means that tides themselves are not responsible for earthquakes. Perhaps, however, if an earthquake is about to trigger, the tide can nudge it to fail. Therefore, we would expect seismicity to be higher when the tidal stresses and the tectonic stresses point in the same direction, and lower when the opposite is true.

Searching for periodicity: can we prove tidal triggering?

There are two key tidal cycles: The first one is 27.5 days long, which is the time the moon needs to circle around the earth. The second one is 24 hours long, which is the time the earth takes to turn around its own axis. If an increase in the rate of earthquakes correlates with these periods, then that increase could be tidally triggered. The next step would then be to actually compute the stresses involved.

Could the tides permit earthquake forecasts?

Since 1980 seismologists have searched for such a link, with mixed results. Recent studies, which have found a relation, are limited to certain regions or circumstances (Ide et. al., 2016). For example, it was found that the number of earthquakes in the region of the 2011 Tohoku earthquake in Japan was correlated with the tide before the earthquake occurred. After the magnitude 9 earthquake, on the other hand, no correlation was found (Tanaka et. al., 2012). Studies like this speculate that it might be possible to evaluate if a large rupture is about to come in certain areas, but this has yet to be proven.

The recent event was probably facilitated by the tide

In their research, Dr. Gloria Moncayo and her colleagues evaluated earthquakes in Colombia between 1993 and 2017. They found that the rate of earthquakes indeed had a periodic component, with a period of 27.5 days. About one-sixth (or 16%) more earthquakes occur when the moon is closest, i.e. at a full moon. This correlation between earthquakes and tides was strongest for the events within the Cauca cluster and the Bucaramanga nest.

The recent earthquake occurred just three days after the last full moon (20 March). In the figure below, this corresponds to a phase of 34°, and thus in an area where more earthquakes are expected due to the tide. We contacted the authors of the research in order to learn more.

Dr. Moncayo told us that the position and the timing of the event indicated tidal triggering. Her colleague, Dr. Jorge I. Zuluaga, added that they calculated the tidal stress for this event and found that its direction was such that the earthquake would be facilitated. ‘If I could bet a dollar, I would bet that it was tidally triggered. Regretfully, we cannot falsify this assertion’, he wrote.

Here, you see the number of earthquakes in relation to the 27.5-day period of the moon. A phase of 0 and 360 degrees corresponds to a full moon, and 180 degrees to a new moon. You can see that only a small fraction of the total number of earthquakes varies with time.
Image from Moncayo et. al. (2019)

Putting it into perspective: A tidal nudge, but not an earthquake prediction

For last Saturday’s event, we know that the tidal stress favored the triggering. Before we jump into hasty conclusions, we should be aware that there are limitations to the result of the study of Dr. Moncayo and her colleagues. An important one is that the seismological network has expanded in the time they evaluated. This could introduce error in the detection of periodicity (Ader and Avouac, 2013). Even if the periodicity that the authors found was true, still most of the earthquakes are independent of the tide. Only a fraction (less than 16%) of the seismicity could be attributed to it. Finally, we need to know the actual tidal stresses and not only the periodicity to make statements of the causality.

References

Ader, T. J., & Avouac, J. P. (2013). Detecting periodicities and declustering in earthquake catalogs using the Schuster spectrum, application to Himalayan seismicity. Earth and Planetary Science Letters, 377, 97-105.

Heaton, T. H. (1975). Tidal triggering of earthquakes. Geophysical Journal International, 43(2), 307-326.

Ide, S., Yabe, S., & Tanaka, Y. (2016). Earthquake potential revealed by tidal influence on earthquake size–frequency statistics. Nature Geoscience, 9(11), 834.

Moncayo, G. A., Zuluaga, J. I., & Monsalve, G. (2019). Correlation between tides and seismicity in Northwestern South America: the case of Colombia. Journal of South American Earth Sciences, 89, 227-245.

Tanaka, S. (2012). Tidal triggering of earthquakes prior to the 2011 Tohoku‐Oki earthquake (Mw 9.1). Geophysical research letters, 39(7).

https://www2.sgc.gov.co/sismos/sismos/ultimos-sismos.html

http://beltoforion.de/article.php?a=tides_explained&hl=en&p=tides_applet&s=idPageTop#idPageTop

http://temblor.net/earthquake-insights/the-riddle-of-the-19-september-2017-mexican-earthquake-8481/

http://news.mit.edu/2013/study-faults-a-runaway-mechanism-in-intermediate-depth-earthquakes-1223

See the full article here .

five-ways-keep-your-child-safe-school-shootings

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

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

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.

Authorities

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
rdegroot@usgs.gov
626-583-7225

Learn more about EEW Research

ShakeAlert Fact Sheet

ShakeAlert Implementation Plan

From École Polytechnique Fédérale de Lausanne: “How fluid viscosity affects earthquake intensity”

From École Polytechnique Fédérale de Lausanne

3.22.19
Sarah Perrin

A young researcher at EPFL has demonstrated that the viscosity of fluids present in faults has a direct effect on the force of earthquakes.

Fault zones play a key role in shaping the deformation of the Earth’s crust. All of these zones contain fluids, which heavily influence how earthquakes propagate. In an article recently published in Nature Communications, Chiara Cornelio, a PhD student at EPFL’s Laboratory of Experimental Rock Mechanics (LEMR), shows how the viscosity of these fluids directly affects an earthquake’s intensity. After running a series of laboratory tests and simulations, Cornelio developed a physical model to accurately calculate variables such as how much energy an earthquake needs to propagate—and, therefore, its strength—according to the viscosity of subsurface fluids.

The study formed part of wider research into geothermal energy projects which, like other underground activities, can trigger earthquakes – a process known as induced seismicity, as opposed to natural seismicity, where earthquakes occur without human intervention.

“Subsurface exploration projects such as geothermal power, injection wells and mining all involve injecting pressurized fluids into fractures in the rock,” explains Cornelio. “Studies like this show how a better understanding of the properties and effects of fluids is vital to preventing or attenuating induced earthquakes. Companies should factor these properties into their thinking, rather than focusing solely on volume and pressure considerations.”

Like soap

Cornelio ran 36 experiments, simulating earthquakes of varying intensity, and propagating at different speeds, in granite or marble, with fluids of four different viscosities. Her findings demonstrated a clear correlation between fluid viscosity and earthquake intensity.

“Imagine these fluids working like soap, reducing the friction between your hands when you wash them, or like the oil you spray on mechanical parts to get them moving again,” explains Marie Violay, an assistant professor and the head of the LEMR. “Moreover, naturally occurring earthquakes produce heat when the two plates rub together. That heat melts the rock, creating a lubricating film that causes the fault to slip even further. Our study also gives us a clearer picture of how that natural process works.”

See the full article here .

Earthquake Alert

Earthquake Alert

Earthquake Network projectEarthquake 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

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

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.

Authorities

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
rdegroot@usgs.gov
626-583-7225

Learn more about EEW Research

ShakeAlert Fact Sheet

ShakeAlert Implementation Plan

five-ways-keep-your-child-safe-school-shootings

Please help promote STEM in your local schools.

Stem Education Coalition

EPFL campus

EPFL is Europe’s most cosmopolitan technical university. It receives students, professors and staff from over 120 nationalities. With both a Swiss and international calling, it is therefore guided by a constant wish to open up; its missions of teaching, research and partnership impact various circles: universities and engineering schools, developing and emerging countries, secondary schools and gymnasiums, industry and economy, political circles and the general public.

From University of Tokyo: “Sensing shakes”

From University of Tokyo

March 11, 2019

A new way to sense earthquakes could help improve early warning systems.

Earthquake Research Institute

Contour maps depict changes in gravity gradient immediately before the earthquake hits. The epicenter of the 2011 Tohoku earthquake is marked by (✩). ©2019 Kimura Masaya.

Every year earthquakes worldwide claim hundreds or even thousands of lives. Forewarning allows people to head for safety and a matter of seconds could spell the difference between life and death. UTokyo researchers demonstrate a new earthquake detection method — their technique exploits subtle telltale gravitational signals traveling ahead of the tremors. Future research could boost early warning systems.

The shock of the 2011 Tohoku earthquake in eastern Japan still resonates for many. It caused unimaginable devastation, but also generated vast amounts of seismic and other kinds of data. Years later researchers still mine this data to improve models and find novel ways to use it, which could help people in the future. A team of researchers from the University of Tokyo’s Earthquake Research Institute (ERI) found something in this data which could help the field of research and might someday even save lives.

It all started when ERI Associate Professor Shingo Watada read an interesting physics paper on an unrelated topic by J. Harms from Istituto Nazionale di Fisica Nucleare in Italy. The paper suggests gravimeters — sensors which measure the strength of local gravity — could theoretically detect earthquakes.

“This got me thinking,” said Watada. “If we have enough seismic and gravitational data from the time and place a big earthquake hit, we could learn to detect earthquakes with gravimeters as well as seismometers. This could be an important tool for future research of seismic phenomena.”

The idea works like this. Earthquakes occur when a point along the edge of a tectonic plate comprising the earth’s surface makes a sudden movement. This generates seismic waves which radiate from that point at 6-8 kilometers per second. These waves transmit energy through the earth and rapidly alter the density of the subsurface material they pass through. Dense material imparts a slightly greater gravitational attraction than less dense material. As gravity propagates at light speed, sensitive gravimeters can pick up these changes in density ahead of the seismic waves’ arrival.

A map of Japan showing locations for the epicenter of the 2011 Tohoku earthquake (✩),Kamioka (K), Matsushiro (M) and seismic survey instruments used (△ and ●). ©2019 Kimura Masaya.

“This is the first time anyone has shown definitive earthquake signals with such a method. Others have investigated the idea, yet not found reliable signals,” elaborated ERI postgraduate Masaya Kimura. “Our approach is unique as we examined a broader range of sensors active during the 2011 earthquake. And we used special processing methods to isolate quiet gravitational signals from the noisy data.”

Japan is famously very seismically active so it’s no surprise there are extensive networks of seismic instruments on land and at sea in the region. The researchers used a range of seismic data from these and also superconducting gravimeters (SGs) in Kamioka, Gifu Prefecture, and Matsushiro, Nagano Prefecture, in central Japan.

The signal analysis they performed was extremely reliable scoring what scientists term a 7-sigma accuracy, meaning there is only a one-in-a-trillion chance a result is incorrect. This fact greatly helps to prove the concept and will be useful in calibration of future instruments built specifically to help detect earthquakes. Associate Professor Masaki Ando from the Department of Physics invented a novel kind of gravimeter — the torsion bar antenna (TOBA) — which aims to be the first of such instruments.

A TOBA with door open to reveal cryogenically cooled sensor platform inside. ©2019 Ando Masaki.

“SGs and seismometers are not ideal as the sensors within them move together with the instrument, which almost cancels subtle signals from earthquakes,” explained ERI Associate Professor Nobuki Kame. “This is known as an Einstein’s elevator, or the equivalence principle. However, the TOBA will overcome this problem. It senses changes in gravity gradient despite motion. It was originally designed to detect gravitational waves from the big bang, like earthquakes in space, but our purpose is more down-to-earth.”

The team dreams of a network of TOBA distributed around seismically active regions, an early warning system that could alert people 10 seconds before the first ground shaking waves arrive from an epicenter 100 km away. Many earthquake deaths occur as people are caught off-guard inside buildings that collapse on them. Imagine the difference 10 seconds could make. This will take time but the researchers continually refine models to improve accuracy of the method for eventual use in the field.

Science paper:
“Earthquake-induced prompt gravity signals identified in dense array data in Japan,” Masaya Kimura; Nobuki Kame; Shingo Watada; Makiko Ohtani; Akito Araya; Yuichi Imanishi; Masaki Ando; Takashi Kunugi
Earth, Planets and Space

See the full article here .

Earthquake Alert

Earthquake Alert

Earthquake Network projectEarthquake 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

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

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.

Authorities

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
rdegroot@usgs.gov
626-583-7225

Learn more about EEW Research

ShakeAlert Fact Sheet

ShakeAlert Implementation Plan

five-ways-keep-your-child-safe-school-shootings

Please help promote STEM in your local schools.

Stem Education Coalition

The University of Tokyo aims to be a world-class platform for research and education, contributing to human knowledge in partnership with other leading global universities. The University of Tokyo aims to nurture global leaders with a strong sense of public responsibility and a pioneering spirit, possessing both deep specialism and broad knowledge. The University of Tokyo aims to expand the boundaries of human knowledge in partnership with society. Details about how the University is carrying out this mission can be found in the University of Tokyo Charter and the Action Plans.