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

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 .

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Please help promote STEM in your local schools.

Stem Education Coalition

Earthquake Alert

Earthquake Network project

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

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

Get the app in the Google Play store.

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

Meet The Quake-Catcher Network

QCN bloc

Quake-Catcher Network

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

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

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

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

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

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

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

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

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

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

Below, the QCN Quake Catcher Network map

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

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: “Past meets present to help future seismic hazard forecasts in San Diego, CA”

From temblor

January 13, 2020
Alka Tripathy-Lang
@DrAlkaTrip

Urbanization obscures a complex fault zone on which downtown San Diego sits, but decades-old geotechnical studies reveal the faults.

Urbanization in downtown San Diego. Credit: Tony Webster CC-BY-2.0.

Fault studies often rely on surface expressions of the ground’s movement. In densely populated urban areas, such as San Diego, this evidence is concealed beneath the cityscape. Now, though, a team has used historical reports to trace faults through downtown San Diego in unprecedented detail, establishing a template that other fault-prone cities can follow to illuminate otherwise hidden hazards.

Urbanization obscures geology

Downtown San Diego, popular for its beaches and parks, also hosts the active Rose Canyon Fault Zone, a complex hazard that underlies the city from northwest of La Jolla through downtown, before curving into San Diego Bay.

Rose Canyon Fault. https://www.nbcsandiego.com/

Like the nearby San Andreas, the Rose Canyon Fault is right-lateral, meaning if you were to stand on one side, the opposite side would appear to move to your right. But it plods along at a rate of 1-2 millimeters per year, unlike its speedy neighbor, which indicates a comparatively lower seismic risk.

“We haven’t had a major rupture” on the Rose Canyon Fault since people have been living atop it, says Jillian Maloney, a geophysicist at San Diego State University and co-author of the new study. So it’s hard to say what kind of damage would be caused, she says. “But, a magnitude-6.9 [of which this fault is capable] is big.”

Because of urbanization, though, “there haven’t been any comprehensive geologic investigations” of the faults underlying downtown San Diego, Maloney says. This presents a problem because detailed knowledge of active and inactive fault locations, especially in a complicated area where the fault zone bends, is key for successful seismic hazard assessments, she says. The state and federal government maintain fault maps and databases, but their accuracy at the small scale was unknown.

Map of the Rose Canyon Fault near San Diego, California, USA. USGS

Faded pages

A solution to the lack of detailed fault mapping in downtown San Diego resided in decades of old geotechnical reports. These individual studies the size of a city block or smaller are required by the city for any proposed development near active faults, as mapped by the state. Although the data are public once the reports are filed with the city, the reports had not been integrated into a comprehensive or digital resource, and the city does not maintain a list of such reports.

This bird’s-eye view of downtown San Diego was drawn by Eli Glover in 1876. Prior to the development of downtown San Diego, the Rose Canyon Fault Zone was expressed on the surface and could be seen laterally offsetting topographic features. Credit: Library of Congress, Geography and Map Division.

According to Luke Weidman, lead author of this study, which was his master’s project, the first challenge was determining how many reports were even available. Weidman, currently a geologist at geotech firm Geocon, went straight to the source: He asked several of San Diego’s large geotechnical firms for their old publicly available reports in exchange for digitizing them.  

Weidman scrutinized more than 400 reports he received, dating from 1979 to 2016. Many were uninterpretable because of faded or illegible pages. He assembled the 268 most legible ones into a fault map and database of downtown San Diego. Because reports lacked geographical coordinates, Weidman resorted to property boundaries, building locations, park benches and even trees to locate the reports on a modern map, says Maloney, one of his master’s advisors. Weidman, Maloney and geologist Tom Rockwell also of San Diego State published the findings from their comprehensive interactive digital map last month in Geosphere, along with an analysis of the Rose Canyon Fault Zone in downtown San Diego.

Below from https://pubs.geoscienceworld.org/

Map of the Rose Canyon fault zone (RCFZ) through San Diego (SD), California (USA) and across the San Diego Bay pull-apart basin. Black box shows the extent of Figure 3. Grid shows population count per grid cell (∼1 km2) (source: LandScan 2017, Oak Ridge National Laboratory, UT-Battelle, LLC, https://landscan.ornl.gov/). DF—Descanso fault; SBF—Spanish Bight fault; CF—Coronado fault; SSF—Silver Strand fault; LNFZ—La Nacion fault zone.

Street map of greater downtown San Diego region showing Alquist-Priolo (AP) zones and faults from the U.S. Geological Survey (USGS) fault database (USGS-CGS, 2006). Black box shows the extent of Figures 6, 7, and 8. Background imagery: ESRI, HERE (https://www.here.com/strategic-partners/esri), Garmin, OpenStreetMap contributors, and the GIS community.

Fault findings

The team found that downtown San Diego’s active faults—defined in their paper as having ruptured within the past 11,500 years—largely track the state’s active fault maps. However, at the scale of the one-block investigations, they found several faults mapped in the wrong location, and cases of no fault where one was expected. Further, the team uncovered three active faults that were not included in the state or federal maps. At the scale at which geotechnical firms, government, owners and developers need to know active fault locations, the use of this type of data is important, says Diane Murbach, an engineering geologist at Murbach Geotech who was not involved in this study.

This map of downtown San Diego, Calif., shows fault locations as mapped by the U.S. Geological Survey (USGS), and faults as located by the individual geotechnical reports compiled in the new study. Green, light orange, dark orange and red boxes indicate whether individual geotechnical studies found no hazard (green), active faults (red) or potential fault hazards (dark or light orange). Note that the Rose Canyon Fault Zone as mapped by USGS occasionally intersects green boxes, indicating the fault may be mislocated. Where the fault is active, mismatches exist as well. Note the arrow pointing to the ‘USGS-Geotech fault difference,’ highlighting a significant discrepancy in where the fault was previously mapped, versus where it lies. Credit: Weidman et al., [2019].

Maloney says they also found other faults that haven’t ruptured in the last 11,500 years. This is important, she says, because “you could have a scenario where an active zone ruptures and propagates to [one] that was previously considered inactive.”

This research “is the first of its kind that I know of that takes all these different reports from different scales with no set format, and fits them into one [usable] database,” says Nicolas Barth, a geologist at the University of California, Riverside who was not part of this study. Many cities have been built on active faults, obscuring hints of past seismicity, he notes. “This is a nice template for others to use,” he says, “not just in California, but globally.”

References
Weidman, L., Maloney, J.M., and Rockwell, T.K. (2019). Geotechnical data synthesis for GIS-based analysis of fault zone geometry and hazard in an urban environment. Geosphere, v.15, 1999-2017. doi:10.1130/GES02098.1

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 Network project

Get the app in the Google Play store.

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

Meet The Quake-Catcher Network

QCN bloc

Quake-Catcher Network

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

Below, the QCN Quake Catcher Network map

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

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

The primary project partners include:

The Earthquake Threat

Part of the Solution

System Goal

Current Status

Authorities

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: “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 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.

Get the app in the Google Play store.

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

Meet The Quake-Catcher Network

QCN bloc

Quake-Catcher Network

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

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.

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richardmitnick Related 2 Comments September 27, 2019September 27, 2019 8 Minutes

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

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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.

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richardmitnick Related Leave a comment September 22, 2019September 22, 2019 17 Minutes

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.

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richardmitnick Related Leave a comment August 10, 2019August 10, 2019 13 Minutes

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 .

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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

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richardmitnick Related Leave a comment July 10, 2019July 10, 2019 13 Minutes

From temblor: “Southern California M 6.4 earthquake stressed by two large historic ruptures”

From temblor

July 4, 2019
Ross S. Stein, Ph.D., and Volkan Sevilgen, M.Sc., Temblor, Inc.

The site of the 4th of July shock was stressed by the great 1872 Owens Valley quake and the 1992 Landers quake. Their overlapping stress lobes may have raised the stakes for this region.

Citation: Stein, R. S., and Sevilgen, V., (2019), Southern California M 6.4 earthquake stressed by two large historic ruptures, Temblor, http://doi.org/10.32858/temblor.034

A Magnitude 6.4 earthquake struck the remote southern California high desert today, a region which has been the site of several moderate earthquakes over the past 30 years (Hauksson and Unruh, 2007), and tends to exhibit swarm-like behavior. Based on its aftershocks, the quake appears to have ruptured two perpendicular faults, one right-lateral (whichever side you are on, the other moves to the right), and the other left lateral, as shown below.

Temblor app map of the mainshock and its first two hours of aftershock suggests that two orthogonal faults have ruptured together. The inferred sense of slip is represented by the half arrows.

The Eastern California Shear Zone lights up

The quake lies west of Searles Valley and east of Ridgecrest, near the Naval Air Warfare Center on China Lake. This is a region of diffuse shear and extension, as indicated by the myriad of small distributed faults, and is part of the so-called ‘Eastern California Shear Zone.’ It also lies close to a geothermally active region that heats and locally thins the crust. While the San Andreas is the major fault system that accommodates the Pacific-North America plate motion, the Eastern California Shear Zone plays a secondary role, and so, in fact, the plate boundary spans the entire girth of California.

The ‘Eastern California Shear Zone,’ within which the 4th July shock struck, rivals the San Andreas for great quakes, producing an M~7.6 shock in 1872, an M=7.3 shock in 1992, and an M=7.1 shock in 1999.

Two quakes gang up in Ridgecrest

We calculate that two large earthquakes, the 26 March 1872 M~7.6 Owens Valley shock, and the 29 June 1992 M=7.3 Landers shock, permanently imparted stress to the site of today’s shock, perhaps increasing the likelihood of earthquakes in this region over others.

The site of the July 4th shock was likely brought closer to failure in the 1872 M~7.6 shock. Notice that the (red) stress trigger zones of the this 148-year-old quake are all seismically active today, whereas the (blue) stress shadows are generally devoid of shocks.

The more recent 1992 M 7.3 Landers shock was followed by the Ridgecrest earthquakes of M 5.4 in August 1995, and an M 5.8 in September 1995 (Hauksson et al., 1995). These earthquakes perhaps indicate that stress imparted by the Landers earthquake immediately brought this area closer to failure, and so the 1995 events might be regarded as remote aftershocks.

The 4th July earthquake lies at the northern edge of a stress trigger lobe of the 1992 Landers shock. Together, the 1872 and 1992 earthquakes increased the stress at the 4th July epicenter by about 0.25 bars, a small but significant amount.

In 2005, Shinji Toda and his colleagues used the 1992 Landers stress changes and the pattern of seismicity to make a retrospective forecast of seismicity, below. The forecast is in red, the observed quakes that struck are in blue. Because of its voluminous background seismicity and the imparted stress, one can see that the site of the 4th July shock was indeed forecast for a high quake rate.

The 4th July quake struck where the background rate of shocks is high, and where stress was transferred by the 1992 earthquake.

What’s Next?

Our preliminary calculation, below, suggests that parts of the Garlock, Black Mountain, and Panamint Valley Faults were brought closer to failure by the 4th July quake. Fortunately, all of these are in remote, lightly populated regions.

Coulomb 3.3 calculation of stress transferred by the 4th July shock to the surrounding region and major faults. Here we use a simple source based on the moment tensor (geometry, sense of slip, and size) of the earthquake, as determined by the USGS.

Citation: Stein, R. S., and Sevilgen, V., (2019), Southern California M 6.4 earthquake stressed by two large historic ruptures, Temblor, http://doi.org/10.32858/temblor.034

References

Egill Hauksson, Kate Hutton, Hiroo Kanamori, Lucile Jones, James Mori, Susan Hough, and Glenn Roquemore (1995), Preliminary Report on the 1995 Ridgecrest Earthquake Sequence in Eastern California, Seismological Research Letters, 66 (6), 54-60, doi.org/10.1785/gssrl.66.6.54

Hauksson, E., and J. Unruh (2007), Regional tectonics of the Coso geothermal area along the intracontinental plate boundary in central eastern California: Three-dimensional Vp and Vp /Vs models, spatial-temporal seismicity patterns, and seismogenic deformation, J. Geophys. Res., 112, B06309, doi:10.1029/2006JB004721.

Stein, R.S., Earthquake Conversations, Scientific American, vol. 288, 72-79, January issue, 2003. Republished in: Our Ever Changing Earth, Scientific American, Special Edition, v. 15 (2), 82-89, 2005.

Toda, S., Stein, R. S., Richards-Dinger, K. & Bozkurt, S. Forecasting the evolution of seismicity in southern California: Animations built on earthquake stress transfer. J. Geophys. Res. 110, B05S16 (2005) https://doi.org/10.1029/2004JB003415

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

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richardmitnick Related Leave a comment July 5, 2019July 5, 2019 9 Minutes

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

sciencesprings
Email
More
Twitter
Like Loading...

richardmitnick Related Leave a comment June 25, 2019June 25, 2019 10 Minutes

From temblor: “El Salvador Earthquake: A Moderate Event in An Area of Extreme Seismic Risk”

From temblor

Posted on June 1, 2019 by Tiegan Hobbs
Tiegan Hobbs, Ph.D., Postdoctoral Hazard Scientist (@THobbsGeo), and Ross S. Stein, Ph.D., Temblor, Inc.

Because of its offshore location and moderate depth, Thursday’s shock did little damage. But many indications suggest that El Salvador will not stay so lucky for long. This event also highlights the increasing number of large extensional earthquakes: a global trend with important hazard implications.

A photo by Twitter user Daniel (@dfvegacom) showing the calm after the earthquake in El Salvador.

At 03:03 am local time on Thursday morning, a strong earthquake ruptured off the west coast of El Salvador on the Pacific side of Central America. It was felt in southern Mexico, Guatemala, Honduras, Nicaragua, and Costa Rica, with a maximum reported intensity of about Level VI (strong shaking). The quake awakened many residents of the nearby city of La Libertad, less than an hour’s drive south of the capital city of San Salvador. But fortunately, the shaking is likely to damage only poorly built structures. Because of its moderate depth and offshore location, no tsunami was produced and little liquefaction or land-sliding is expected.

Thursday’s M 6.6 earthquake just off the coast of El Salvador was felt in surrounding countries: Mexico, Guatemala, Nicaragua, and Costa Rica.

Waiting For El Salvador’s ‘Big One’ in the Red Zone

While this event has no reported damage or injuries so far, El Salvador has among the highest seismic risks in the world. What does that mean, exactly? Hazard refers to the probability of earthquakes occurring, but risk refers to the likelihood of suffering losses from that hazardous event. Both El Salvador and Guatemala are recognized by the Global Earthquake Model Foundation as having a very high potential for losses due to a high likelihood of earthquakes occurring compounded by buildings and population centers that are highly susceptible to damage. So, this week’s earthquake was a gentle reminder of what could be in store for this small country.

The Global Earthquake Model Foundation assesses seismic risk around the world. El Salvador and Guatemala are both ominously high. (Silva et al., 2018)

Two Deep Tensional Earthquakes in One Week

As with the M=8.0 Peru earthquake from earlier this week, Thursday’s M=6.6 El Salvador earthquake was also a relatively deep tensional rupture. That means it occurs within the subducting slab, rather than on the interface between the slab and the over-riding continental plate. In this part of Central America, tensional events occur relatively frequently at this depth range (Correa-Mora et al., 2009). This includes a M=7.3 in 1982 and M=7.7 in 2001, which, combined, killed almost 2,000 people.

Conflicting views of seismic hazard in Central America

Although the GEM model and the Global Earthquake Activity Rate model (Bird et al., 2015), used by Temblor and shown in the first figure, both suggest high risk for El Salvador and Guatemala, Correa-Mora et al., (2009) argue that the subduction zone in this region may be too ‘weak’ (slippery) to generate large megathrust earthquakes. These are the kinds of events that are usually associated with great damage, and which can generate tsunami if they occur near the ocean floor. Correa-Mora and coauthors suggested that although there is a great deal of energy being released through earthquakes in the subduction zone region here, they are probably mostly from these tensional events. Nevertheless, earthquakes can be deadly regardless of their mechanism. The 1556 Huaxian earthquake in China occurred in an extensional rift environment, and yet it is the single deadliest earthquake on record, claiming 830,000 lives (Liu et al., 2011).

Is the Rate of Large Global Tensional Earthquakes Growing?

In addition to this week’s two major extensional (also called ‘normal’ or tensional) earthquakes, the last couple of years have seen other strong tensional events: the September 2017 M=7.1 Puebla earthquake in Mexico City, the November 2018 M=7.1 Anchorage earthquake in Alaska, and the February 2019 M=7.5 Ecuador earthquake. But is the apparent increase in extensional events real?

A map of tensional earthquakes with magnitude 7 and above, since 2005. They are distributed mainly in the ‘Ring of Fire, around the Pacific Ocean. Mapped using GeoMapApp.

Generally speaking, we detect more earthquakes with time because networks, detection algorithms, and computing power are all improving. However, the number of large extensional events appears to increase with time at a greater rate than either thrust events or combined thrust and strike-slip events. The rate of increase is 0.01 magnitude units per year when normalized to all non-extensional earthquakes, and 0.02 when compared to only thrust events. This means that (1) there are more large tensional earthquakes than there were before, and (2) the occurrence of thrust events is actually decreasing slightly.

The proportion of normal events is increasing with time. The ratio of extensional events to all other types of events (top) and to only thrust events (bottom), inclusive from 1976-2018 (Global CMT Project). Only M>7 earthquakes considered. The lines show a linear regression (fitting), with the corresponding equations and regression coefficients in the top left. A clear upward trend is observed, although a larger increase is occurring relative to thrust events. This means that the rate of large thrust events is actually decreasing with time.

It’s possible that, because extensional earthquakes are sometimes quite deep, this apparent increased frequency of extensional events is just due to improved seismic networks. Additional work will be required to determine how compelling this result is. However, if it is real then it is astounding! These events occur because the subducting slab is being pulled apart as it is dragged into the mantle by suction. Is that suction force increasing with time, or does it oscillate? We know that great megathrust earthquakes (Ben-Naim et al., 2013) and strike-slip events (Pollitz et al., 2012) can tend to be clustered in time – perhaps the same is true for extensional intraslab events?

Aftershocks in Unexpected Places

The initial aftershocks of the M=6.6 event lie 30-40 km southwest of the mainshock.

Although Thursday’s M=6.6 earthquake off El Salvador was too far away to have been caused by Sunday’s M=8.0 event in Peru, the El Salvador event did produce its own remarkable aftershock sequence. Early aftershocks are concentrated to the southwest of the mainshock, roughly 30 km away, at a depth of about 35 km. Usually, aftershocks are distributed around the edge of the region that slipped during the mainshock, rather than being clustered in only one direction. This may be due to the rupture propagating (unzipping) towards the southwest, concentrating seismic energy in that direction, or possibly related to a tear or bump in the subducting slab that makes this region more susceptible. By studying cases like this one, scientists can better understand where and when aftershocks will strike in the aftermath of much larger earthquakes.

References

Ben‐Naim, E., Daub, E. G., & Johnson, P. A. (2013). Recurrence statistics of great earthquakes. Geophysical Research Letters, 40(12), 3021-3025.

Bird, P., Jackson, D. D., Kagan, Y. Y., Kreemer, C. & Stein, R. S. (2015). GEAR1: A Global Earthquake Activity Rate Model Constructed from Geodetic Strain Rates and Smoothed Seismicity. Bull Seis. Soc. Am.105(5), 2538-2554.

Correa-Mora, F., DeMets, C., Alvarado, D., Turner, H. L., Mattioli, G., Hernandez, D., … & Tenorio, C. (2009). GPS-derived coupling estimates for the Central America subduction zone and volcanic arc faults: El Salvador, Honduras and Nicaragua. Geophysical Journal International, 179(3), 1279-1291.

Liu, M., Stein, S., & Wang, H. (2011). 2000 years of migrating earthquakes in North China: How earthquakes in midcontinents differ from those at plate boundaries. Lithosphere, 3(2), 128-132.

Pollitz, F. F., Stein, R. S., Sevilgen, V., & Bürgmann, R. (2012). The 11 April 2012 east Indian Ocean earthquake triggered large aftershocks worldwide. Nature, 490(7419), 250.

V. Silva, D. Amo-Oduro, A. Calderon, J. Dabbeek, V. Despotaki, L. Martins, A. Rao, M. Simionato, D. Viganò, C. Yepes, A. Acevedo, N. Horspool, H. Crowley, K. Jaiswal, M. Journeay, M. Pittore (2018). Global Earthquake Model (GEM) Seismic Risk Map (version 2018.1). DOI: 10.13117/GEM-GLOBAL-SEISMIC-RISK-MAP-2018.1, https://maps.openquake.org/map/global-seismic-risk-map/

GEM Profile for El Salvador: https://downloads.openquake.org/countryprofiles/SLV.pdf

USGS Event Pages

https://earthquake.usgs.gov/earthquakes/eventpage/us70003t2n

https://earthquake.usgs.gov/earthquakes/eventpage/us2000ar20/

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

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Twitter
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richardmitnick Related Leave a comment June 3, 2019June 3, 2019 12 Minutes

From temblor: “Deep earthquake in Peru is felt along the length of South America: More to follow?”

From temblor

May 28, 2019
Tiegan Hobbs, Ph.D., Postdoctoral Seismic Risk Scientist (@THobbsGeo)

A magnitude-8.0 quake shook deep below the Amazon Rainforest in Peru, causing extensive liquefaction and shaking from Colombia to Chile.

A powerful Mw 8.0 earthquake shook Peru at 2:41 a.m. local time on Sunday, May 26, 2019, from an epicenter within the Reserva Nacional Pacaya-Samiria of the Amazon Rainforest. Although it was felt from Colombia to Chile, this deep event (about 110 kilometers) did not generate a tsunami and only two casualties have been reported (AP). At least 26 people are injured in Peru and Ecuador. Casualties were limited due to the remote location of the epicenter and the depth of the quake.

The 26 May 2019 M=8.0 event was slightly larger and about 440 kilometers to the southeast of a M=7.5 earthquake that occurred in Ecuador on 22 Feb 2019.

Damage and liquefaction expected in the Amazon.

This map, produced by the United States Geological Survey, shows estimated Mercalli shaking intensity (colored contour lines from maximum of orange level VIII) and liquefaction probability (colored contours with maximum dark purple representing a greater than 20% chance of liquefaction).

The United States Geological Survey (USGS) now routinely produces maps of probable landslide and liquefaction. According to the shaking and topography of the area, this event is predicted to cause widespread and/or severe liquefaction affecting approximately 74,000 people. It is not predicted to cause an extensive landslide, though aerial surveys showed at least one landslide in the jungle.

Road damage in the Cajamarca Region from Twitter (@Crisanris).

Peru resident Cristina Andrade (@crisanris) reported road damage due to ground displacements from this event and aerial photography shows a landslide in the lush jungles of this region (Reuters). Little information has emerged about the extent of the destruction, despite incoming footage from the firefighters of Peru (@BomberosPE) showing rubble lining the streets of Yurimaguas, the town nearest the epicenter, in Alto Amazonas. Emergency teams and politicians have been converging on the affected areas to lead the response.

Landslide as a result of Sunday’s earthquake, as reported to Reuters (@Univ_inenglish).

Not the first deep earthquake in this area

Events like this one, which occur deep within Earth’s crust and rupture under extensional forces, are different than usual subduction zone earthquakes. This earthquake occurred entirely within the subducting Nazca Plate, which is being pulled apart as it is sucked deeper into Earth’s mantle. We call this type of earthquake an “intraplate event: occurring within the plate. More often, subduction zone earthquakes are “interplate” events, in which earthquakes occur on the boundary between two plates. These events, like the 2016 M=7.8 earthquake in Pedernales, Ecuador (http://temblor.net/earthquake-insights/ecuador-earthquakes-what-happened-and-what-is-next-986/), tend to be shallower and therefore are closer to population centers and the ocean floor. They’re thus more likely to cause tsunamis and significant damage.

This figure, modified from Leyton et al., 2009, shows the difference between interplate events, which occur between two plates, and intraplate events, like Sunday’s Mw 8.0 event in Peru.

Questions may arise as to whether Sunday’s Mw 8.0 earthquake in Peru was related to a February Mw 7.5 event in Ecuador. That event was also a deep, extensional intraplate quake. While these two earthquakes were very similar and happened within a few months of one another, they were upwards of 400 kilometers apart. Therefore, the static stress change from the February event was too small to have triggered Sunday’s event.

Sunday’s quake, like most deep earthquakes, is likely to be relatively depleted in aftershocks [e.g. Wiens & McGuire, 1995]. So far, no events with magnitude greater than 2.5 have been reported by the USGS for that area.

References

pic.twitter.com/miV5ak8Gf6

pic.twitter.com/3bFW9JqfE9

USGS Event Pages

https://earthquake.usgs.gov/earthquakes/eventpage/us60003sc0/executive

(https://earthquake.usgs.gov/earthquakes/eventpage/us60003sc0/ground-failure/summary

https://earthquake.usgs.gov/earthquakes/eventpage/us2000jlfv/executive

Leyton, F., Ruiz, J., Campos, J., & Kausel, E. (2009). Intraplate and interplate earthquakes in Chilean subduction zone: A theoretical and observational comparison. Physics of the Earth and Planetary interiors, 175(1-2), 37-46.

Wiens, D. A., & McGuire, J. J. (1995). The 1994 Bolivia and Tonga events: Fundamentally different types of deep earthquakes?. Geophysical research letters, 22(16), 2245-2248.

Other News Sources

https://www.eluniversal.com.mx/english/magnitude-8-earthquake-hits-peru (Reuters)

https://www.apnews.com/3b12f5abea604f19a5ad36d700d090b1 (AP)

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

sciencesprings
Email
More
Twitter
Like Loading...

richardmitnick Related Leave a comment May 29, 2019May 29, 2019 9 Minutes

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