From temblor: “Ancient rock structures guided rupture pathway in Australian quake”

From temblor

July 16, 2020
Helen Santoro, freelance science journalist, (@helenwsantoro)

Early one May morning in 2016, a magnitude-6.0 earthquake ripped through central Australia, causing a 13-mile (21-kilometer) stretch of land to shift upwards by up to three feet (approximately one meter). Typically, an earthquake of this magnitude results in far larger ground displacements and jagged ruptures — but this rupture was long and smooth, puzzling scientists at the University of Melbourne.

The magnitude-6.0 quake produced a remarkably linear surface rupture. Credit: Dan Clark, Commonwealth of Australia (Geoscience Australia).

Generally, ruptures that break the surface are rough and curved, says Januka Attanayake, a seismologist at the university and lead author on the study. “This one was different.”

A history of larger ground displacements

Although Australia is located in the middle of the Indo-Australian tectonic plate, far from a plate boundary where large quakes typically occur, the continent still has a history of destructive earthquakes. A magnitude-5.6 earthquake in 1989, for example, hit the harbor city of Newcastle and caused 13 deaths and $4 billion in damage — making it one of Australia’s worst natural disasters. Luckily, most earthquakes of this magnitude happen in remote areas far away from cities and towns.

The majority of these moderate earthquakes also occur on faults that don’t generate clear surface ruptures. If an earthquake generates a surface offset, or “fault scarp,” researchers get a chance to make direct observations of the fault surface and can better understand the processes behind the rupture. Any fault scarp needs to be documented immediately following an earthquake, before the forces of nature — wind, water, animal, etc. — work to erase any clues that could give scientists valuable insight into the rupture process.

Uncovering the foundation of the smooth rupture

As luck may have it, the 2016 earthquake created a clear surface rupture — providing a perfect opportunity for scientists from the University of Melbourne to study the tremor. The earthquake originated near the Petermann Ranges, a mountain range that extends almost 200 miles (320 kilometers) across central Australia that was formed around 550 million years ago.

After the earthquake, the team trekked out into the field to create a detailed map of the fault scarp. They used satellite-based global positioning system (GPS) data to map the feature from above and found a relatively smooth and straight 13-mile (21-kilometer) scarp. To see the fault underground, the group used data from seismometers — instruments that record ground motion — to detect and locate aftershocks. These smaller quakes result from the redistribution of stress following a larger shock and tend to cluster along the fault surface that ruptured in the main quake. They therefore can be used to map the extent of the fault below the surface.

Attanyake and his team discovered that the pattern of aftershocks followed along a known subsurface rock structure, suggesting that the surface that ruptured during the quake was related to this feature. In fact, the orientation of the structure seemed to control the path of the rupture.

Old rocks dictate modern earthquakes

Around 550 million years ago India slammed into Western Australia, causing the Petermann mountains to form. The grinding together of these land masses at extreme pressure and temperature deep within the Earth’s crust caused weak zones of rock to form. Over time, as Earth’s surface was slowly eroded away, these zones made their way closer to the surface.

Weak zones within old rocks in the Petermann Ranges are a path of least resistance for stress to concentrate in the crust. Here the orientation of these weak rock units is shown with the dotted line and arrow. Credit: Fabian Prideaux

Stress that builds in the crust through time causes rocks to break through the path of least resistance — in the case of the 2016 earthquake, one of these weak zones.

“We don’t know why this particular weak layer ruptured, but that layer is what caused the long, straight line,” Attanayake explained. “The weak mechanics of the rocks allowed it to easily react to the earthquake,” meaning that earthquake essentially took advantage of the presence of this weak layer.

Earthquakes like this that occur far from plate boundaries are rare, says John Paul Platt, a professor of geology at the University of Southern California. But he adds, they “can be particularly dangerous because they affect areas where buildings are not constructed to withstand earthquakes.” Understanding where these types of ruptures may occur could be vital for disaster preparation. This latest study suggests that in some cases, the rocks at the surface and at depth could give scientists clues about where a future quake could occur.

Further Reading

Attanayake, J., T. R. King, M. C. Quigley, G. Gibson, D. Clark, A. Jones, S. L. Brennand, and M. Sandiford (2020). Rupture Characteristics and Bedrock Structural Control of the 2016 Mw 6.0 Intraplate Earthquake in the Petermann Ranges, Australia, Bull. Seismol. Soc. Am. 110, 1037–1045, doi: 10.1785/ 0120190266

Salleh, Anna (2009). Mystery mountain range explained. Retrieved July 1, 2020, from https://www.abc.net.au/science/articles/2009/12/10/2765285.htm

Verdouw, E. (2018, September 02). On this day: Newcastle earthquake strikes. Retrieved June 19, 2020, from https://www.australiangeographic.com.au/blogs/on-this-day/2013/11/on-this-day-newcastle-earthquake-strikes/

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: “Hydrated oceanic crust supports benign plate movement at subduction zones”

From temblor

July 23, 2020
Melanie Chan, @mellojellochan

This SEM image shows hydrated oceanic crust that was deformed at about 370 degrees Celsius with 6 kilobars of pressure in a plate interface shear zone. Credit: Tulley et al., Science Advances (2020).

At approximately 14:46 JST, on Friday, March 11, 2011, the Japanese communities living in the region of Tohoku were informed by the nation’s Early Earthquake Warning system that they would soon experience notably strong shaking. What the people did not know at the time was that this extreme shaking was a result of a megathrust earthquake, measuring at 9.0-9.1 in magnitude. They did not know of the death and destruction that would await them, stemming from the earthquake and its resulting tsunami, claiming tens of thousands of lives and laying waste to the Pacific Coast of northeast Japan.

Not all earthquakes reach such a high magnitude nor create such catastrophes in their wake. Understanding the circumstances that lead to either benign geological events or catastrophic ones is undoubtedly an important question in geological research. A recent study [ Science Advances ] explores the conditions near Kyushu, Japan, that dictate whether tectonic plates in a subduction zone will creep benignly past one another or get stuck and unleash any pent-up stress as a potentially disastrous megathrust earthquake. Specifically, the research team investigates whether water can sufficiently hydrate and weaken the oceanic plate to accommodate slow slip of plates past each other.

How plates slide

Tectonic plates move at rates of centimeters per year above the uppermost layer of the Earth’s mantle. In a subduction zone, oceanic plates composed of dense basalt slide below younger, more-buoyant oceanic plates or less-dense continental plates. Sediments coating the ocean floor often hitch a ride down into the Earth, and because they deform much more easily than basaltic oceanic crust, they “form a lubricating layer between the oceanic crust and overlying [tectonic] plate,” says Chris Tulley, a doctoral student at Cardiff University and lead author of the new study, published in Science Advances.

Geologists commonly assume that this lubricating layer of sediment lets the plates slide past each other without producing earthquakes in a process called aseismic creep. However, Tulley says, at “plate boundaries where there is relatively thin sediment cover and where rough basaltic seamounts stick out above the sediments, [one] might expect more earthquakes” because the lubricating layer — the oceanic sediment — is simply too thin. Yet, even here, some plates creep past one another without producing major earthquakes, indicating that ocean sediment may not be the only substance that allows for aseismic creep.

Sampling deformed crust

Researchers from Cardiff and Tsukuba University in Japan tackled this problem by sampling deformed oceanic crust from three sites on Kyushu. These three sites exposed rocks that deformed in a Late Cretaceous subduction zone, thought to have had similar characteristics to the modern subduction zone offshore of southwest Japan.

Researchers collected samples of deformed oceanic crust from three locations along the coast of Kyushu, Japan, (Nagasaki-bana pictured here). Credit: BirdsEyeLV, CC BY-SA 3.0

Using energy-dispersive spectroscopy and electron-backscatter diffraction to analyze samples of hydrated oceanic crust in the scanning electron microscope, the researchers were able to understand the mechanical and chemical processes responsible for controlling how hydrated oceanic crust deformed. The researchers concluded “that if water is added to basaltic oceanic crust, then two [processes occur]: One, water allows weak [clay] minerals to form; and two, water facilitates the process of dissolving and precipitating minerals in response to stress — a mechanism allowing deformation at low stresses,” Tulley says. In other words, the hard basalt experienced significant mechanical weakening with the addition of water. Their results showed that as water weakens the top basaltic layer of the subducting slab, the slab can deform more easily through creep — instead of the interfacing plates locking together to potentially create a megathrust earthquake.

In this figure from the Science Advances paper, you can see the deformed rocks that the researchers sampled. In (A), metabasalts are exposed as foliated layers with red mudstone filling the space in between. In (B), the remnants of easily dissolvable minerals with the metamorphic rocks reveal a lack of foliation. In (C), you can see a reduction in silicon concentration within solution seams, caused by the dissolution of albite. In (D), you can see very fine grains of chlorite, prehnite and magnetite. And in (E), asymmetric stress shadows around titanite indicate noncoaxial shear within dissolved minerals. Photo credit (A): Å. Fagereng, Cardiff University; Rest – Tulley et al., Science Advances (2020).

More research needed

This study will “stimulate people to take a closer look at margins that are sediment-starved” and force researchers to grapple with the idea that “metabasalts can be as weak as sedimentary rocks at certain temperatures,” says Michael Brown, a professor specializing in metamorphic geology at the University of Maryland. However, whether hydrated oceanic basalts are the main components that dictate whether a subduction zone moves via catastrophic earthquake or slow creep is still up for debate, Brown says.

This research, Tulley says, highlights the need to better understand the specific geological environment and processes that are responsible for a wide spectrum of slip events (namely creep versus earthquakes). There’s more work to be done though, he notes, such as observing locations “with shear zones of metasediment, dry, strong oceanic crust, and hydrated crust in combination” and what roles such combinations in varying conditions play in complex plate slip behavior.

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 EarthSky: “A powerful 7.8-magnitude quake struck Alaska last night”

From EarthSky

July 22, 2020
Deborah Byrd

The quake happened around 10:15 p.m. Tuesday night 7.21.20, according to clocks in Alaska. A tsunami warning along coastal Alaska – which was later rescinded – sent some residents to higher ground.

The July 21, 2020, 7.8-magnitude earthquake struck off the coast of the Alaskan Peninsula, about 17 miles (27 km) deep. Image via USGS.

According to Alaska Public Media, residents across coastal Alaska – from Homer to Unalaska – woke to the sounds of sirens and phone alerts last night, warning them of a possible tsunami. Many quickly left home, moving to higher ground. The warnings followed a 7.8-magnitude earthquake – a very powerful earthquake – that struck off coastal Alaska at around 10:15 p.m., local time, on Tuesday, July 21, 2020. The earthquake was centered offshore, 60 miles (98 km) south-southeast of Perryville, Alaska, according to the U.S. Geological Survey (USGS). All tsunami warnings and advisories were canceled early Wednesday morning, according to the National Weather Service.

The Associated Press reported:

“Hundreds wore masks against the spread of the coronavirus as they gathered in shelters.”

Kodiak Police Sgt. Mike Sorter told the Associated Press early Wednesday morning:

“No reports of any damage. No injuries were reported. Everything is nominal.”

There have been multiple, smaller aftershocks since the main quake.

__________________________________

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

See the full article here .

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

Stem Education Coalition

Deborah Byrd created the EarthSky radio series in 1991 and founded EarthSky.org in 1994. Today, she serves as Editor-in-Chief of this website. She has won a galaxy of awards from the broadcasting and science communities, including having an asteroid named 3505 Byrd in her honor. A science communicator and educator since 1976, Byrd believes in science as a force for good in the world and a vital tool for the 21st century. “Being an EarthSky editor is like hosting a big global party for cool nature-lovers,” she says.

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

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

Please help promote STEM in your local schools.

Stem Education Coalition

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 .

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

Please help promote STEM in your local schools.

Stem Education Coalition

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