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  • richardmitnick 9:34 pm on December 30, 2019 Permalink | Reply
    Tags: "Largest Colombian crustal earthquake in 20 years strikes on Christmas Eve", , , , , , Shake Alert System,   

    From temblor: “Largest Colombian crustal earthquake in 20 years strikes on Christmas Eve” 

    1

    From temblor

    December 28, 2019
    Albert Leonardo Aguilar Suarez, Ph.D. candidate, Stanford University
    Ross S. Stein, Ph.D., Temblor, Inc.

    Evacuations in Bogotá and the suspension of transportation systems followed a magnitude-6.2 earthquake, which struck on or near where the North Andean Block grinds against South American Plate. The mainshock was followed just 15 minutes later by a magnitude-5.7 aftershock. Further large aftershocks remain a possibility.

    1
    Bogotá, Colombia, the capital and largest city in the country, was shaken on Christmas Eve by a magnitude-6.2 temblor. Credit: Ian Barbour, CC BY-SA 2.0

    The Christmas Eve gift from the Earth to the people of Colombia was a reminder of Earth’s immense power and destructive potential. A magnitude-6.2 earthquake struck near the town of Mesetas, Meta just after 2 pm local time on December 24. This event was followed 15 minutes later by a magnitude-5.7 aftershock. Both were widely felt in Bogotá, Villavicencio, Cali and other big cities in the country. The shaking caused evacuations in Bogotá and the suspension of transportation systems. Fortunately, no injuries have been reported, but many buildings were damaged near the epicentral region. Damages in Mesetas include cracking of the school, the police station and many houses.

    3
    The magnitude-6.2 and magnitude-5.7 earthquakes struck at the junction of several faults, in a location where strong shaking is expected over a person’s lifetime. In this map, sediment-filled basins would be expected to experience more intense shaking than the highlands. The expected shaking is from Temblor’s PUSH (Probabilistic Uniform Seismic Hazards) model, which is available worldwide.

    4
    Ground motion recorded at the seismic station Tumaco, nearly 600 km away. The magnitude-6.2 shock struck 15 minutes before the magnitude-5.7 shock. Data provided by National Seismological Network at the Colombian Geological Survey (RSNC) and stored on IRIS DMC.

    More to come

    Following a large earthquake, many smaller earthquakes, called aftershocks, occur because of stress changes caused by the mainshock. In the 48 hours following the magnitude-6.2 earthquake, the National Seismological Network of Colombia (RSNC for its initials in Spanish) reported more than 300 aftershocks.

    5
    Aftershocks reported by the National Seismological Network at the Colombian Geological Survey (RSNC).

    In a typical aftershock sequence, earthquakes will become less frequent with time. That is observed here, with the aftershock sequence including several earthquakes greater than magnitude-4.5. These aftershocks will continue for weeks to years, but most will be too small to be felt or cause damage, although we cannot rule out the possibility of a larger event.

    6
    Evolution of aftershocks, with time on the x-axis and magnitude on the y-axis. The size of the circles scale with magnitude to emphasize the y-axis. Notice the decrease in earthquake frequency with time. The vertical dashed line marks the origin time of the magnitude-6.2 event.

    Unsurprising, naturally occurring earthquakes

    The magnitude-6.2 is the largest crustal earthquake that has occurred in Colombia in the last 20 years, but its size and location are not surprising for earthquake scientists. The epicenter is located on the eastern side of the Eastern Cordillera of Colombia, where the Algeciras fault system acts as the boundary between the South American plate and the North Andean Block [Velandia et al., 2005; Veloza et al., 2012]. The Algeciras fault system is as a right-lateral strike slip fault, meaning that whichever side of the fault you’re on, the opposite side moves to the right (see the green arrows on the map below). The Algeciras fault system was also responsible for the largest historical crustal earthquake in Colombia—the 1967 magnitude-7.0 Huila earthquake [Dimaté et al.,2005].

    6
    Large historical and recent earthquakes in the Eastern Cordillera near Bogotá. The green arrows indicate the right-lateral sense of motion of the Algeciras fault system. On the left is the Colombia-Huila seismic sequence (2016-2017-2018). In the middle, highlighted by red boxes are the Christmas earthquakes. The inset shows the tectonic setting of Colombia. CP stands for Caribbean Plate, NP for Nazca Plate, NAB for North Andean Block and SAP for South American Plate.

    The eastern cordillera of Colombia and the faults that run through it are responsible for more than half of the shallow seismicity (i.e. depth < 30 km) reported by RSNC. Small earthquakes happen every day, but for the most part, their shaking is too small to be felt. However, more than two years ago, a magnitude-4.7 earthquake took place ~20 km NE of the epicenter of the magnitude-6.2 Christmas earthquake, which is why the location of the Christmas quake is no surprise at all.

    In recent years, seismic activity surged near the town of Colombia (a town with the same name as the country). Three earthquakes greater than magnitude-5.0 struck the town in October 2016, February 2017 and July 2018, and were felt in major cities. These earthquakes also had a rich sequence of aftershocks, as shown by Aguilar & Prieto [2019]. There, the Altamira and Nazareth faults were responsible for the sequence, which occurred near the intersection of the two. At the time, these three quakes were the largest to occur close to Bogotá, after the 2008 magnitude-5.9 Quetame earthquake.

    This seismicity is naturally occurring, a consequence of the interactions of the geological faults that are building the Eastern Cordillera. They are unrelated to industrial oil and gas activities as many people have falsely claimed on social media. Furthermore, there is no relation between these earthquakes and the so-called ‘activation of the Pacific ring of fire’, which is a headline that goes viral after any notable earthquake near the edge of the Pacific Ocean.

    An opportunity for advancement

    The RSNC recently deployed additional seismometers, including two new stations close to the recent earthquakes—station URMC in Uribe, Meta, installed in March 2018, and station CLBC in Colombia, Huila that started recording on February 2019. These additional seismometers will allow a higher resolution image of seismicity, especially for small quakes that are hidden in the shadow of bigger ones.

    Aguilar & Prieto [2018] and Aguilar et al. [2019] revisited the data recorded by RSNC near Colombia-Huila. Through a systematic search for small earthquakes, they tripled the number of events in the catalog for the years 2016, 2017 and 2018. They also clarified the geometry of these faults via precise relocations. The work in the following weeks and months will be pivotal for gaining further insights into the geometry of the faults and the mechanisms of these earthquakes, as well as the seismic hazard near Bogotá, the largest city in Colombia.

    7
    These are waveforms of the M 6.2 aftershocks, with time pointing upwards. We took the liberty of ‘dressing the tree’ with the red bulbs.

    References
    INGEOMINAS – Servicio Geologico Colombiano (SGC Colombia) (1993): Red Sismologica Nacional de Colombia. International Federation of Digital Seismograph Networks. Dataset/Seismic Network. doi:10.7914/SN/CM

    Dimaté, C., Rivera, L., and Cisternas, A. (2005), Re-visiting large historical earthquakes in the Colombian Eastern Cordillera, Journal of Seismology, 9, 1–22, doi:10.1007/s10950-005-1413-2

    Aguilar, A. and Prieto, G. (2018), Spatial and temporal evolution of source properties in the Colombia-Huila seismic sequence. Seismology of the Americas. Available at: https://www.seismosoc.org/wp-content/uploads/2018/06/poster_AA.pdf

    Aguilar, A. and Prieto, G. (2019), Spatial and temporal evolution of source properties in the Colombia-Huila seismic sequence. Thesis submitted to the National University of Colombia.

    Veloza, G., Styron R., Taylor M., and Morg, A. (2012), Open-source archive of active faults for northwest South America, GSA Today, 22, 4–10. doi:10.1130/GSAT-G156A.1

    Mora-Páez, H., Mencin, D.J., Molnar, P., Diederix, H., Cardona-Piedrahita, L., Peláez-Gaviria, J.-R., and Corchuelo- Cuervo, Y. (2016), GPS velocities and the construction of the Eastern Cordillera of the Colombian Andes, Geophys. Res. Lett., 43, 8407–8416, doi:10.1002/ 2016GL069795.

    Aguilar, A., Prieto, G., Pedraza, P., Pulido, N. and Beroza, G. (2019), The recent seismicity of the Eastern Cordillera of Colombia. American Geophysical Union Fall Meeting.

    Velandia, F., Acosta, J., Terraza, R. and Villegas, H. (2005), The current tectonic motion of the Northern Andes along the Algeciras Fault System in SW Colombia, Tectonophysics, doi:10.1016/j.tecto.2004.12.028.

    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

    1

    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.

    3
    Smartphone network spatial distribution (green and red dots) on December 4, 2015

    Meet The Quake-Catcher Network

    QCN bloc

    Quake-Catcher Network

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

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

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

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

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

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

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

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

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

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

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

    ShakeAlert: An Earthquake Early Warning System for the West Coast of the United States
    1

    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

     
  • richardmitnick 2:16 pm on December 21, 2019 Permalink | Reply
    Tags: "Scientists Identify Almost 2 Million Previously "Hidden" Earthquakes", , , , , , , Shake Alert System   

    From Caltech: “Scientists Identify Almost 2 Million Previously “Hidden” Earthquakes” 

    Caltech Logo

    From Caltech

    April 18, 2019 [Just found this is a search]
    Robert Perkins
    (626) 395‑1862
    rperkins@caltech.edu

    A closer look at seismic data from 2008–17 expands Southern California’s earthquake catalog by a factor of 10.

    1
    Seismic activity associated with the Cahuilla earthquake swarm in Southern California’s Anza Valley. Filling out the earthquake catalogue using template matching shows the swarm in greater detail. The color of each seismic event records its depth, and so the rainbow-like appearance of the swarm indicates the shallow-to-deep slant of the fault, not previously visible from earlier data.

    Pouring through 10 years’ worth of Southern California seismic data with the scientific equivalent of a fine-tooth comb, Caltech seismologists have identified nearly two million previously unidentified tiny earthquakes that occurred between 2008 and 2017.

    Their efforts, published online by the journal Science on April 18, expand the earthquake catalog for that region and period of time by a factor of 10—growing it from about 180,000 recorded earthquakes to more than 1.81 million. The new data reveal that there are about 495 earthquakes daily across Southern California occurring at an average of roughly three minutes apart. Previous earthquake cataloging had suggested that approximately 30 minutes would elapse between seismic events.

    This 10-fold increase in the number of recorded earthquakes represents the cataloging of tiny temblors, between negative magnitude 2.0 (-2.0) and 1.7, made possible by the broad application of a labor-intensive identification technique that is typically only employed on small scales. These quakes are so small that they can be difficult to spot amid the background noise that appears in seismic data, such as shaking from automobile traffic or building construction.

    “It’s not that we didn’t know these small earthquakes were occurring. The problem is that they can be very difficult to spot amid all of the noise,” says Zachary Ross, lead author of the study and postdoctoral scholar in geophysics, who will join the Caltech faculty in June as an assistant professor of geophysics. Ross collaborated with Egill Hauksson, research professor of geophysics at Caltech, as well as Daniel Trugman of Los Alamos National Laboratory and Peter Shearer of Scripps Institution of Oceanography at UC San Diego.

    To overcome the low signal-to-noise ratio, the team turned to a technique known as “template matching,” in which slightly larger and more easily identifiable earthquakes are used as templates to illustrate what an earthquake’s signal at a given location should, in general, look like. When a likely candidate with the matching waveform was identified, the researchers then scanned records from nearby seismometers to see whether the earthquake’s signal had been recorded elsewhere and could be independently verified.


    Using powerful computers and a technique called template matching, scientists at Caltech have identified millions of previously unidentified tiny earthquakes. The new data reveal that there are about 495 earthquakes daily across Southern California, occurring at an average of roughly three minutes apart. This graphic shows the earthquakes recorded near Cahuilla, California from 2016-2017.

    Template matching works best in regions with closely spaced seismometers, since events generally only cross-correlate well with other earthquakes within a radius of about 1 to 2 miles, according to the researchers. In addition, because the process is computationally intensive, it has been limited to much smaller data sets in the past. For the present work, the researchers relied on an array of 200 powerful graphics processing units (GPUs) that worked for weeks on end to scan the catalog, detect new earthquakes, and verify their findings.

    However, the findings were worth the effort, Hauksson says. “Seismicity along one fault affects faults and quakes around it, and this newly fleshed-out picture of seismicity in Southern California will give us new insights into how that works,” he says. The expanded earthquake catalog reveals previously undetected foreshocks that precede major earthquakes as well as the evolution of swarms of earthquakes. The richer data set will allow scientists to gain a clearer picture of how seismic events affect and move through the region, Ross says.

    “The advance Zach Ross and colleagues has made fundamentally changes the way we detect earthquakes within a dense seismic network like the one Caltech operates with the USGS. Zach has opened a new window allowing us to see millions of previously unseen earthquakes and this changes our ability to characterize what happens before and after large earthquakes,” said Michael Gurnis, Director of the Seismological Laboratory and John E. and Hazel S. Smits Professor of Geophysics

    See the full article here .

    Earthquake Alert

    1

    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.

    3
    Smartphone network spatial distribution (green and red dots) on December 4, 2015

    Meet The Quake-Catcher Network

    QCN bloc

    Quake-Catcher Network

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

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

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

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

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

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

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

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

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

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

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

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

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

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

    The primary project partners include:

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

    The Earthquake Threat

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

    Part of the Solution

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

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

    System Goal

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

    Current Status

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

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

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

    Authorities

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

    For More Information

    Robert de Groot, ShakeAlert National Coordinator for Communication, Education, and Outreach
    rdegroot@usgs.gov
    626-583-7225

    Learn more about EEW Research

    ShakeAlert Fact Sheet

    ShakeAlert Implementation Plan


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


    Stem Education Coalition

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

    Caltech campus

     
  • richardmitnick 9:30 am on September 27, 2019 Permalink | Reply
    Tags: "Distant Quake Triggered Slow Slip on Southern San Andreas", , , , , Shake Alert System   

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

    From AGU
    Eos news bloc

    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.

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    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.

    4
    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

    1

    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.

    3
    Smartphone network spatial distribution (green and red dots) on December 4, 2015

    Meet The Quake-Catcher Network

    QCN bloc

    Quake-Catcher Network

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

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

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

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

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

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

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

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

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

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

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

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

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

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

    The primary project partners include:

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

    The Earthquake Threat

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

    Part of the Solution

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

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

    System Goal

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

    Current Status

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

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

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

    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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    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.

     
    • Skyscapes for the Soul 2:40 pm on September 27, 2019 Permalink | Reply

      Very interesting that there is slow aseismic slip on my local part of the San Andreas. Explains why that fault hardly ever pops like the Borrego fault does.

      Like

  • richardmitnick 11:04 am on September 22, 2019 Permalink | Reply
    Tags: , , , , , Shake Alert System,   

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

    LANL bloc

    Los Alamos National Laboratory

    via

    Wired logo

    From WIRED

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

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    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.

    2
    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.

    3
    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

    1

    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.

    3
    Smartphone network spatial distribution (green and red dots) on December 4, 2015

    Meet The Quake-Catcher Network

    QCN bloc

    Quake-Catcher Network

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

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

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

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

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

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

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

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

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

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

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

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

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

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

    The primary project partners include:

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

    The Earthquake Threat

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

    Part of the Solution

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

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

    System Goal

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

    Current Status

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

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

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

    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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    Please help promote STEM in your local schools.

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

    LANL campus

    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.

     
  • richardmitnick 8:55 am on August 23, 2019 Permalink | Reply
    Tags: , , , , Shake Alert System   

    From University of Washington: “USGS awards $10.4M to ShakeAlert earthquake early warning system in the Pacific Northwest “ 

    U Washington

    From University of Washington

    August 19, 2019

    The U.S. Geological Survey today announced $10.4 million in funding to the Pacific Northwest Seismic Network, based at University of Washington, to support the ShakeAlert earthquake early warning system. Some $7.3 million of the funding will go to the UW.

    The PNSN is responsible for monitoring earthquakes and volcanoes in Washington and Oregon. It is a partnership between the University of Washington, the University of Oregon and the USGS. The support for the PNSN is among the new ShakeAlert cooperative agreements announced today by the USGS.

    The first year’s funding of $5.4 million to the PNSN begins this month. The UW will receive about $3.75 million in direct support of its PNSN activities and $1.66 million will support the PNSN team at the University of Oregon. The second-year funding, of an additional $5 million, is contingent on approval by Congress and will be similarly shared.

    1
    Karl Hagel and Pat McChesney, field engineers with the Pacific Northwest Seismic Network team at the University of Washington, install earthquake monitoring equipment on the slopes of Mount St. Helens, with Mount Hood in the distance.Marc Biundo/University of Washington.

    “This investment in the PNSN represents a major increase in federal support for earthquake monitoring in the Cascadia region,” said Harold Tobin, director of the PNSN and professor in the UW’s Department of Earth and Space Sciences. “At the end of the two years of funding we anticipate having essentially doubled the number of seismic stations across our whole region that contribute to real-time earthquake early warning. This would allow for full public alerts of any potentially damaging earthquakes, across our entire region of Washington and Oregon, by the end of the two-year period.”

    This new award will allow for installation of 104 new seismic stations in Washington state and 44 in Oregon, during the two-year period. It will also support improved, more-sophisticated detection of earthquakes as they begin, and new efforts to engage potential users of the warnings.

    ShakeAlert’s network of instruments detect the first, less damaging waves from a major earthquake close to where the earthquake begins. The system then issues alerts for the estimated size and location of the earthquake, providing seconds or minutes of warning before the more damaging ground shaking begins – enough for someone to pull off the road, stop a surgery, or find a safe place to take shelter.

    2
    A sample warning, with a countdown of the number of seconds until the strong shaking reaches the user.Pacific Northwest Seismic Network

    In the Pacific Northwest’s pilot phase of the system, early adopters in the region have developed pilot projects with guidance and support from the PNSN and USGS, and have received ShakeAlert warning messages for the past two years. These warnings are currently used to trigger loss-reduction measures at critical facilities — such as turning off water valves in public utility districts — before dangerous shaking would arrive.

    The additional funding will support the development of new pilot projects in schools, businesses, communities and critical infrastructure facilities in preparation for the eventual goal of open alerts to the general public, as launched recently in the Los Angeles region. The improvements to PNSN’s network supported by this funding will meet the USGS’ recommended station-density standard for public alerting in almost all areas of Washington and Oregon.

    “It will enable us to rapidly build out our network to produce faster and more accurate alerts for Cascadia Region earthquakes,” Tobin said.

    3
    Existing Pacific Northwest Seismic Network ShakeAlert stations, as of spring 2019. The new funding will roughly double the number of stations in Washington and Oregon.

    The funding will also support ongoing research to integrate GPS data into ShakeAlert, which will allow quicker estimates of the magnitude of offshore Cascadia Subduction Zone earthquakes as they unfold. The UW is sharing its research in this area with the National Oceanic and Atmospheric Administration and NASA in the hope of improving tsunami-warning capabilities. The UW is working with Central Washington University, also supported by USGS, to receive near-real-time GPS data from across Washington and Oregon that will be integrated into future releases of ShakeAlert.

    The regional ShakeAlert effort began in 2011, when the UW joined the University of California, Berkeley and California Institute of Technology as a primary ShakeAlert center in the developing a West Coast warning system. The Gordon and Betty Moore Foundation awarded $2 million to each university to kick-start ShakeAlert from a research project to an operational system. With support from Congress, the USGS ramped up support for ShakeAlert as the foundation’s seed funding expired.

    Additional support for PNSN operations comes from the U.S. Department of Energy and the states Oregon and Washington. The Washington legislature, in its current biennium budget, allocated $1.24 million over two years for additional enhancements to the ShakeAlert network.

    See the full article here .


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    Please help promote STEM in your local schools.

    Stem Education Coalition

    u-washington-campus
    The University of Washington is one of the world’s preeminent public universities. Our impact on individuals, on our region, and on the world is profound — whether we are launching young people into a boundless future or confronting the grand challenges of our time through undaunted research and scholarship. Ranked number 10 in the world in Shanghai Jiao Tong University rankings and educating more than 54,000 students annually, our students and faculty work together to turn ideas into impact and in the process transform lives and our world. For more about our impact on the world, every day.
    So what defines us —the students, faculty and community members at the University of Washington? Above all, it’s our belief in possibility and our unshakable optimism. It’s a connection to others, both near and far. It’s a hunger that pushes us to tackle challenges and pursue progress. It’s the conviction that together we can create a world of good. Join us on the journey.

     
  • richardmitnick 10:25 am on August 10, 2019 Permalink | Reply
    Tags: "A big earthquake in the US Pacific Northwest?", Cascadia megathrust fault, , , , , Shake Alert System   

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

    From University or Oregon

    via

    1

    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.

    1
    Data derived from NaturalEarthData.com, 10m datasets. Projected into NAD83 UTM 9N. Alicia.iverson

    3
    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.

    4
    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.

    4
    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.

    5
    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.

    6
    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.

    7
    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

    1

    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.

    3
    Smartphone network spatial distribution (green and red dots) on December 4, 2015

    Meet The Quake-Catcher Network

    QCN bloc

    Quake-Catcher Network

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

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

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

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

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

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

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

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

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

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

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

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

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

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

    The primary project partners include:

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

    The Earthquake Threat

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

    Part of the Solution

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

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

    System Goal

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

    Current Status

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

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

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

    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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    Please help promote STEM in your local schools.

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    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.

     
  • richardmitnick 11:33 am on July 19, 2019 Permalink | Reply
    Tags: , Dr. Jennifer Andrews, , , , Shake Alert System, The Seismo Lab at Caltech,   

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

    Caltech Logo

    From Caltech

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

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

    2

    1
    Dr. Jennifer Andrews

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

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

    Where were you when the earthquakes hit?

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

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

    What did you do next?

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

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

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

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

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

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

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

    See the full article here .

    Earthquake Alert

    1

    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.

    3
    Smartphone network spatial distribution (green and red dots) on December 4, 2015

    Meet The Quake-Catcher Network

    QCN bloc

    Quake-Catcher Network

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

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

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

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

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

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

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

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

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

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

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

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

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

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

    The primary project partners include:

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

    The Earthquake Threat

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

    Part of the Solution

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

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

    System Goal

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

    Current Status

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

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

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

    Authorities

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

    For More Information

    Robert de Groot, ShakeAlert National Coordinator for Communication, Education, and Outreach
    rdegroot@usgs.gov
    626-583-7225

    Learn more about EEW Research

    ShakeAlert Fact Sheet

    ShakeAlert Implementation Plan


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


    Stem Education Coalition

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

    Caltech campus

     
  • richardmitnick 10:45 am on July 10, 2019 Permalink | Reply
    Tags: "The Ridgecrest earthquakes: Torn ground; nested foreshocks; Garlock shocks; and Temblor’s forecast", , , Shake Alert System,   

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

    1

    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.

    2
    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.

    3
    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?

    3
    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’).

    5
    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.

    6
    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

    7
    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:

    8
    Temblor app screen for Ridgecrest, California (app.temblor.net/)

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

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

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

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

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

    References

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

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

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

    See the full article here .


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

    Please help promote STEM in your local schools.

    Stem Education Coalition

    Earthquake Alert

    1

    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.

    3
    Smartphone network spatial distribution (green and red dots) on December 4, 2015

    Meet The Quake-Catcher Network

    QCN bloc

    Quake-Catcher Network

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

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

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

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

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

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

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

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

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

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

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

    ShakeAlert: An Earthquake Early Warning System for the West Coast of the United States
    1

    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

     
  • richardmitnick 11:21 am on July 5, 2019 Permalink | Reply
    Tags: "Southern California M 6.4 earthquake stressed by two large historic ruptures", , , Shake Alert System,   

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

    1

    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.

    1
    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.

    2
    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.

    3
    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.

    4
    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.

    5
    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.

    6
    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

    1

    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.

    3
    Smartphone network spatial distribution (green and red dots) on December 4, 2015

    Meet The Quake-Catcher Network

    QCN bloc

    Quake-Catcher Network

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

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

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

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

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

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

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

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

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

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

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

    ShakeAlert: An Earthquake Early Warning System for the West Coast of the United States
    1

    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

     
  • richardmitnick 1:38 pm on June 25, 2019 Permalink | Reply
    Tags: "Large earthquake on Japan’s west coast points to a profound shortcoming in the national seismic hazard model", , , Shake Alert System,   

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

    1

    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.

    1
    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.

    2
    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

    1

    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.

    3
    Smartphone network spatial distribution (green and red dots) on December 4, 2015

    Meet The Quake-Catcher Network

    QCN bloc

    Quake-Catcher Network

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

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

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

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

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

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

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

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

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

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

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

    ShakeAlert: An Earthquake Early Warning System for the West Coast of the United States
    1

    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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