From Eos: “Seismic Sensors in Orbit”

From AGU

From Eos

26 December 2019
Timothy I. Melbourne
Diego Melgar
Brendan W. Crowell
Walter M. Szeliga

A continuously telemetered GNSS station located on the Olympic Peninsula of Washington state. Determining the real-time positions of hundreds of stations like this one to accuracies of a few centimeters within a global reference frame opens a new pipeline of analysis tools to monitor and mitigate risk from the seismic and tsunami hazards of the Cascadia Subduction Zone and other fault systems around the globe. Credit: Central Washington University

Imagine it’s 3:00 a.m. along the Pacific Northwest coast—it’s dark outside and most people are asleep indoors rather than alert and going about their day. Suddenly, multiple seismometers along the coast of Washington state are triggered as seismic waves emanate from a seconds-old earthquake. These initial detections are followed rapidly by subsequent triggering of a dozen more instruments spread out both to the north, toward Seattle, and to the south, toward Portland, Ore. Across the region, as the ground begins to shake and windows rattle or objects fall from shelves, many people wake from sleep—while others are slower to sense the potential danger.

Within a few seconds of the seismometers being triggered, computers running long-practiced seismic location and magnitude algorithms estimate the source of the shaking: a magnitude 7.0 earthquake 60 kilometers off the Washington coast at a depth roughly consistent with the Cascadia Subduction Zone (CSZ) interface, along which one tectonic plate scrapes—and occasionally lurches—past another as it descends toward Earth’s interior. The CSZ is a well-studied fault known in the past to have produced both magnitude 9 earthquakes and large tsunamis—the last one in 1700.

Cascadia subduction zone

The initial information provided by seismometers is important in alerting not only scientists but also emergency response personnel and the public to the potentially hazardous seismic activity. But whether these early incoming seismic waves truly represent a magnitude 7 event, whose causative fault ruptured for 15–20 seconds, or whether instead they reflect ongoing fault slip that could last minutes and spread hundreds of kilometers along the fault—representing a magnitude 8 or even 9 earthquake—is very difficult to discern in real time using only local seismometers.

It’s a vital distinction: Although a magnitude 7 quake on the CSZ could certainly cause damage, a magnitude 8 or 9 quake—potentially releasing hundreds of times more energy—would shake a vastly larger region and could produce devastating tsunamis that would inundate long stretches of coastline.

The USGS produced a scenario ShakeMap for a modeled M 9.0 CSZ earthquake for planning purposes. This ShakeMap page provides information about probable shaking levels at different frequencies but is not very useful for site specific estimates nor does it provide much information about potential impacts.

The 1999 24 page Crew Publication, Cascadia Subduction Zone Earthquakes: A Magniude 9 Earthquake Scenario, takes USGS-model ground motions and NOAA tsunami estimates and paints a generalized picture of the likely damages to regional infrastructure. The scenario then identifes challenges that will be faced in responding and recovering from such an event.

In 2007 CREW produced a publication that summarized potential impacts and lessons learned in three tabletop exercises based on the Cascadia earthquake scenario.

Oregon Department of Transportation examined potential damage to bridges during a scenario M8.3 earthquake on the CSZ.

Some communities must evacuate for miles to get out of the potential inundation zone, meaning that every second counts. The ability to characterize earthquake slip and location accurately within a minute or two of a fault rupturing controls how effective early warnings are and could thus mean the difference between life and death for tens of thousands of people living today along the Pacific Northwest coast.

Enter GPS or, more generally, Global Navigation Satellite Systems (GNSS). These systems comprise constellations of Earth-orbiting satellites whose signals are recorded by receivers on the ground and used to determine the receivers’ precise locations through time. GPS is the U.S. system, but several countries, or groups of countries, also operate independent GNSS constellations, including Russia’s GLONASS and the European Union’s Galileo system, among others. Prominently used for navigational purposes, GNSS ground receivers, which in recent years have proliferated by the thousands around the world, now offer useful tools for rapidly and accurately characterizing large earthquakes—supplementing traditional seismic detection networks—as well as many other natural hazards.

An Initial Demonstration

Fig. 1. Examples of GNSS three-dimensional displacement recorded roughly 100 kilometers from the hypocenters of the 2011 magnitude 9.1 Tohoku earthquake in Japan, the 2010 magnitude 8.8 Maule earthquake in Chile, the 2014 magnitude 8.1 Iquique earthquake in Chile, and the 2010 magnitude 7.2 El Mayor-Cucapah earthquake in Mexico. Static displacements accrue over timescales that mimic the evolution of faulting and become discernible as dynamic displacements dissipate. Note the dramatic increase in permanent offsets for the largest events, increasing from about 5 centimeters for El Mayor to over 4 meters for Tohoku. The data are freely available from Ruhl et al. [2019].

Large earthquakes both strongly shake and deform the region around the source fault to extents that GNSS can easily resolve (Figure 1). With the expansion of GNSS networks and continuous telemetry, seismic monitoring based on GNSS measurements has come online over the past few years, using continuously gathered position data from more than a thousand ground stations, a number that is steadily growing. Station positions are computed in a global reference frame at an accuracy of a few centimeters within 1–2 seconds of data acquisition in the field. In the United States, these data are fed into U.S. Geological Survey (USGS) and National Oceanic and Atmospheric Administration (NOAA) centers charged with generating and issuing earthquake and tsunami early warnings.

In the scenario above, GNSS-based monitoring would provide an immediate discriminant of earthquake size based on the amount of displacement along the coast of Washington state. Were it a magnitude 7, a dozen or so GNSS stations spread along a roughly 30-kilometer span of the coast might reasonably move a few tens of centimeters within half a minute, whereas a magnitude 8 event—or a magnitude 9 “full rip” along the entire subduction zone, from California to British Columbia—would move hundreds of Cascadia GNSS stations many meters. Ground offset at some might exceed 10 meters, depending on location, but the timing of the offsets along the coast determined with GNSS would track the rupture itself.

The July 2019 strike-slip earthquake sequence in the Eastern California Shear Zone near Ridgecrest in the eastern Mojave Desert provided the first real-world demonstration of the capability of GNSS-based seismic monitoring. The newly developed GNSS monitoring systems included a dozen GNSS stations from the National Science Foundation–supported Network of the Americas (NOTA) located near the fault rupture. Data from these stations indicated that the magnitude 7.1 main shock on 5 July caused coseismic offsets of up to 70 centimeters in under 30 seconds of the initiation of fault slip.

The magnitude 7.1 strike-slip earthquake that occurred in the Mojave Desert near Ridgecrest, Calif., on 5 July 2019 caused the ground surface to rupture. Nearby Global Navigation Satellite Systems (GNSS) stations recorded up to 70 centimeters of offset within 30 seconds of the fault rupture. Credit: U.S. Geological Survey

Further analysis of the data showed that those 30 seconds encompassed the fault rupture duration itself (roughly 10 seconds), another 10 or so seconds as seismic waves and displacements propagated from the fault rupture to nearby GNSS stations, and another few seconds for surface waves and other crustal reverberations to dissipate sufficiently such that coseismic offsets could be cleanly estimated. Latency between the time of data acquisition in the Mojave Desert to their arrival and processing for position at Central Washington University was less than 1.5 seconds, a fraction of the fault rupture time itself. Comparison of the coseismic ground deformation estimated within 30 seconds of the event with that determined several days later, using improved GNSS orbital estimates and a longer data window, shows that the real-time offsets were accurate to within 10% of the postprocessed “true” offsets estimated from daily positions [Melgar et al., 2019]. Much of the discrepancy may be attributable to rapid fault creep in the hours after the earthquake.

A Vital Addition for Hazards Monitoring

This new ability to accurately gauge the position of GNSS receivers within 1–2 seconds from anywhere on Earth has opened a new analysis pipeline that remedies known challenges for our existing arsenal of monitoring tools. Receiver position data streams, coupled to existing geophysical algorithms, allow earthquake magnitudes to be quickly ascertained via simple displacement scaling relationships [Crowell et al., 2013 Geophysical Research Letters]. Detailed information about fault orientation and slip extent and distribution can also be mapped nearly in real time as a fault ruptures [Minson et al., 2014 JGR Solid Earth]. These capabilities may prove particularly useful for earthquake early warning systems: GNSS can be incorporated into these systems to rapidly constrain earthquake magnitude, which determines the areal extent over which warnings are issued for a given shaking intensity [Ruhl et al., 2017 Geophysical Research Letters].

GNSS will never replace seismometers for immediate earthquake identifications because of its vastly lower sensitivity to small ground displacements. But for large earthquakes, GNSS will likely guide the issuance of rapid-fire revised warnings as a rupture continues to grow throughout and beyond the timing of initial, seismometer-based characterization [Murray et al., 2019 Seismological Research Letters].

Deformation measured using GNSS is also useful in characterizing tsunamis produced by earthquakes, 80% of which in the past century were excited either by direct seismic uplift or subsidence of the ocean floor along thrust and extensional faults [Kong et al., 2015 UNESCO UNESDOC Digital Library] or by undersea landslides, such as in the 2018 Palu, Indonesia, earthquake (A. Williamson et al., Coseismic or landslide? The source of the 2018 Palu tsunami, EarthArXiv, https://doi.org/10.31223/osf.io/fnz9j). Rough estimates of tsunami height may be computed nearly simultaneously with fault slip by combining equations describing known hydrodynamic behavior with seafloor uplift determined from GNSS offsets [Melgar et al., 2016 Geophysical Research Letters]. Although GNSS won’t capture landslides or other offshore processes for which on-land GNSS has little resolution, the rapidity of the method in characterizing tsunami excitation, compared with the 10–20 minutes required by global tide gauge and seismic networks and by NOAA’s tsunami-specific Deep-Ocean Assessment and Reporting of Tsunamis (DART) buoy system, offers a dramatic potential improvement in response time for local tsunamis that can inundate coastlines within 5–15 minutes of an earthquake.

Natural hazards monitoring using GNSS isn’t limited to just solid Earth processes. Other measurable quantities, such as tropospheric water content, are estimated in real time with GNSS and are now being used to constrain short-term weather forecasts. Likewise, real-time estimates of ionospheric electron content from GNSS can help identify ionospheric storms (space weather) and in mapping tsunami-excited gravity waves in the ionosphere to provide a more direct measurement of the propagating tsunami as it crosses oceanic basins.

A Future of Unimaginable Potential

Many resources beyond the rapid proliferation of GNSS networks themselves have contributed to making global GNSS hazards monitoring a reality. Unlike seismic sensors that measure ground accelerations or velocities directly, GNSS positioning relies on high-accuracy corrections to the orbits and clocks broadcast by satellites. These corrections are derived from continuous analyses of global networks of ground stations. Similarly, declining costs of continuous telemetry have facilitated multiconstellation GNSS processing, using the vast investments in international satellite constellations to further improve the precision and reliability of real-time GNSS measurements of ground displacements.

In the future, few large earthquakes in the western United States will escape nearly instantaneous measurement by real-time GNSS. Throughout the seismically active Americas, from Alaska to Patagonia, numerous GNSS networks in addition to NOTA now operate, leaving big earthquakes without many places to hide. Mexico operates several GNSS networks, as do Central and South American nations from Nicaragua to Chile. Around the Pacific Rim, Japan, New Zealand, Australia, and Indonesia all operate networks that together comprise thousands of ground stations.

In North America, nearly all GNSS networks have open data-sharing policies [Murray et al., 2018]. But a global system for hazard mitigation can be effective only if real-time data are shared among a wider set of networks and nations. The biggest remaining impediment to expanding a global system is increasing the networks whose data are available for monitoring. GNSS networks are expensive to deploy and maintain. Many networks are built in whole or in part for land surveying and operate in a cost-recovery mode that generates revenue by selling data or derived positioning corrections through subscriptions. At the current time, just under 3,000 stations are publicly available for hazards monitoring, but efforts are under way to create international data sharing agreements specifically for hazard reduction. The Sendai Framework for Disaster Risk Reduction, administered by the United Nations Office for Disaster Risk Reduction, promotes open data for hazard mitigation [International Union of Geodesy and Geophysics, 2015], while professional organizations, such as the International Union of Geodesy and Geophysics, promote their use for tsunami hazard mitigation [LaBrecque et al., 2019].

The future holds unimaginable potential. In addition to expanding GNSS networks, modern smartphones by the billions are ubiquitous sensing platforms with real-time telemetry that increasingly make many of the same GNSS measurements that dedicated GNSS receivers do. Crowdsourcing, while not yet widely implemented, is one path forward that could use tens of millions of phones, coupled to machine learning methods, to help fill in gaps in ground displacement measurements between traditional sensors.

The potential of GNSS as an important supplement to existing methods for real-time hazards monitoring has long been touted. However, a full real-world test and demonstration of this capability did not occur until the recent Ridgecrest earthquake sequence. Analyses are ongoing, but so far the conclusion is that the technique performed exactly as expected—which is to say, it worked exceedingly well. GNSS-based hazards monitoring has indeed arrived.

Acknowledgments

Development of global GNSS seismic analysis is supported by NASA-ESI grants NNX14AQ40G and 80NSSC19K0359 and USGS Cooperative Agreements G17AC00344 and G19AC00264 to Central Washington University. Data from the Network of the Americas are provided by the Geodetic Facility for the Advancement of Geoscience (GAGE), operated by UNAVCO Inc., with support from the National Science Foundation and NASA under NSF Cooperative Agreement EAR-1724794.

References

Crowell, B. W., et al. (2013), Earthquake magnitude scaling using seismogeodetic data, Geophys. Res. Lett., 40(23), 6,089–6,094, https://doi.org/10.1002/2013GL058391.

International Union of Geodesy and Geophysics (2015), Resolution 4: Real-time GNSS augmentation of the tsunami early warning system, iugg.org/resolutions/IUGGResolutions2015.pdf.

Kong, L. S. L., et al. (2015), Pacific Tsunami Warning System: A Half-Century of Protecting the Pacific 1965–2015, 188 pp., Int. Tsunami Inf. Cent., Honolulu, Hawaii, unesdoc.unesco.org/ark:/48223/pf0000233564.

LaBrecque, J., J. B. Rundle, and G. W. Bawden (2019), Global navigation satellite system enhancement for tsunami early warning systems, in Global Assessment Report on Disaster Risk Reduction, U.N. Off. for Disaster Risk Reduct., Geneva, Switzerland, unisdr.org/files/66779_flabrequeglobalnavigationsatellites.pdf.

Melgar, D., et al. (2016), Local tsunami warnings: Perspectives from recent large events, Geophys. Res. Lett., 43(3), 1,109–1,117, https://doi.org/10.1002/2015GL067100.

Melgar, D., et al. (2019), Real-time high-rate GNSS displacements: Performance demonstration during the 2019 Ridgecrest, CA earthquakes, Seismol. Res. Lett., in press.

Minson, S. E., et al. (2014), Real-time inversions for finite fault slip models and rupture geometry based on high-rate GPS data, J. Geophys. Res. Solid Earth, 119(4), 3,201–3,231, https://doi.org/10.1002/2013JB010622.

Murray, J. R., et al. (2018), Development of a geodetic component for the U.S. West Coast Earthquake Early Warning System, Seismol. Res. Lett., 89(6), 2,322–2,336, https://doi.org/10.1785/0220180162.

Murray, J. R., et al. (2019), Regional Global Navigation Satellite System networks for crustal deformation monitoring, Seismol. Res. Lett., https://doi.org/10.1785/0220190113.

Ruhl, C. J., et al. (2017), The value of real-time GNSS to earthquake early warning, Geophys. Res. Lett., 44(16), 8,311–8,319, https://doi.org/10.1002/2017GL074502.

Ruhl, C. J., et al. (2019), A global database of strong-motion displacement GNSS recordings and an example application to PGD scaling, Seismol. Res. Lett., 90(1), 271–279, https://doi.org/10.1785/0220180177.

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Earthquake Alert

Earthquake Alert

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

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

Get the app in the Google Play store.

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

Meet The Quake-Catcher Network

Quake-Catcher Network

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

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

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

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

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

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

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

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

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

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

Below, the QCN Quake Catcher Network map

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

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

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

The primary project partners include:

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

The Earthquake Threat

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

Part of the Solution

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

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

System Goal

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

Current Status

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

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

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

Authorities

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

For More Information

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

Learn more about EEW Research

ShakeAlert Fact Sheet

ShakeAlert Implementation Plan

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

From AGU GeoSpace Blog: “Forces from Earth’s spin may spark earthquakes and volcanic eruptions at Mount Etna”

From From AGU GeoSpace Blog

26 December 2019
Erin I. Garcia de Jesus

New research suggests forces pulling on Earth’s surface as the planet spins may trigger earthquakes and eruptions at volcanoes.

Seismic activity and bursts of magma near Italy’s Mount Etna increased when Earth’s rotational axis was furthest from its geographic axis, according to a new study comparing changes in Earth’s rotation to activity at the well-known Italian volcano.

Earth’s spin doesn’t always line up perfectly with its north and south poles. Instead, the geographic poles often twirl like a top around Earth’s rotational axis when viewed from space. Every 6.4 years, the axes line up and the wobble fades for a short time – until the geographic poles move away from the spin axis and begin to spiral once again.

Polar motion describes the motion of the Earth’s spin axis (shown in orange) with respect to the geographic north and south poles (shown in blue). Over time, the geographic poles appear to spin away from the spin axis when viewed from space and then back again. Viewed from the perspective of someone on Earth, the spin axis instead appears to spiral away from the geographic poles and then spiral back. The motion of the spin pole with respect to the geographic poles fixed to the Earth’s crust is called polar motion. Note: The size and speed of the spiral are greatly exaggerated for clarity. Video credit: NASA/GSFC Science Visualization Studio.

This phenomenon, called polar motion, is driven by changes in climate due to things like changing seasons, melting ice sheets or movement from tectonic plates. As polar motion fluctuates, forces pulling the planet away from the sun tug at Earth’s crust, much like tides due to the gravitational pull from the sun and moon. The tide from polar motion causes the crust to deform over the span of seasons or years. This distortion is strongest at 45 degrees latitude, where the crust moves by about 1 centimeter (0.4 inches) per year.

Now, a new study published in AGU’s journal Geophysical Research Letters suggests that polar motion and subsequent shifts in Earth’s crust may increase volcanic activity.

“I find it quite exciting to know that while climate drives Earth’s spin, its rotation can also drive volcanoes and seismicity,” said Sébastien Lambert, a geophysicist at Paris Observatory in France and lead author of the study.

The new findings, however, don’t allow scientists to forecast volcanic activity. Although the study suggests earthquakes might be more common or volcanic eruptions may eject more lava when the distance between Earth’s geographic and rotational axes is at its peak, the timescale is too large for meaningful short-term forecasts, according to the authors.

But the results point to an interesting concept. “It’s the first time we’ve found this relationship in this direction from Earth’s rotation to volcanoes,” Lambert said. “It’s a small excitation process, but if you accumulate a small excitation over a long time it can lead to measurable consequences.”

Shaking Earth

Previous work [not presented here] has shown the length of a day on Earth, which changes based on the speed of Earth’s spin, also deforms the crust and could affect volcanic behavior. In the new study, Lambert and his colleague, Gianluca Sottili, a volcanologist from Sapienza University of Rome in Italy, wanted to study the relationship between polar motion and volcanic activity.

They focused on Mount Etna because the volcano is well-studied, meaning there’s plenty of data, and it sits just south of 45 degrees latitude. There also weren’t any volcanic crises out of the ordinary at Mount Etna during the study period, which might otherwise mask the signal from polar motion.

An image of an eruption at Mount Etna on October 30, 2002 from the International Space Station. The eruption, triggered by a series of earthquakes, was one of the most vigorous in years. Ashfall was reported in Libya, more than 350 miles away. Credit: NASA

Lambert and Sottili used seismic records from 11,263 earthquakes that happened within 43 kilometers (26.7 miles) of Mount Etna’s summit between 1999 and 2019. The team also used records of how much magma erupted from the volcano since 1900. They included 62 eruptions in the analysis, based on the time span between events.

The pair then compared the distance between the geographic and rotational poles at the time each event occurred to determine whether volcanic activity was connected to Earth’s rotation.

Lambert and Sottili discovered there were more earthquakes when Earth’s rotational pole was furthest from the geographic axis – at the point in Earth’s top-like spin when it looks like it is about to fall over. Between 1999 and 2019, those peaks were in 2002 and 2009. An expected peak in 2015 never materialized because one of the oscillations contributing to polar motion has been slowing down.

The team also uncovered a link between the amount of magma ejected during an eruption. Polar motion appears to drive the largest eruptions from Mount Etna, although to a lesser extent than its seismic activity, according to the researchers.

Examining volcanoes in the Ring of Fire to see if Earth’s spin impacts their activity would surely be interesting, Sottili said, who was senior author of the study. Even expanding to other planets might open scientists’ view of how external forces impact volcanoes on the surface, he added.

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GeoSpace is a blog on Earth and space science, managed by AGU’s Public Information staff. The blog features posts by AGU writers and guest contributors on all sorts of relevant science topics, but with a focus on new research and geo and space sciences-related stories that are currently in the news.

Do you have ideas on topics we should be covering? Would you like to contribute a guest post to the blog? Contact Peter Weiss at pweiss@agu.org.

From Horizon The EU Research and Innovation Magazine: “The ‘slow earthquakes’ that we cannot feel may help protect against the devastating ones”

From Horizon The EU Research and Innovation Magazine

10 December 2019
Sandrine Ceurstemont

Unlike regular earthquakes, which can cause visible damage, slow earthquakes cannot be felt at the Earth’s surface. Image credit – Pixabay/ marcellomigliosi1956, licensed under pixabay license

Earthquakes are sudden and their shaking can be devastating. But about 20 years ago, a new type of earthquake was discovered. We cannot feel them, and geologists still know very little about them, such as how often they occur.

Regular earthquakes occur when rock underground breaks along a fault – a crack in the Earth’s crust that commonly forms a boundary between tectonic plates – and slips at a speed of about a metre per second.

The tectonic plates of the world were mapped in 1996, USGS.

Previously, it was thought that unless there’s an earthquake, faults move very slowly, at fingernail growth rate. Then, better earthquake-detection instruments revealed that there is a whole range of slip speeds in between. These are known as slow earthquakes and can last days, months or sometimes even years.

‘Earth movement accelerates but it doesn’t accelerate to the point where it makes an earthquake that can be felt on the surface,’ said Dr Ake Fagereng, a geologist at Cardiff University in the UK.

There are still many questions to be answered about slow earthquakes though. How they happen, for example, still isn’t clear, as well as what the repercussions might be.

Dr Fagereng and his colleagues are especially interested in slow earthquakes’ relationship to regular ones and the conditions that give rise to these events, which they are investigating as part of a project called MICA. ‘If we can figure that out, then we can hopefully also get at whether those conditions can change so that an earthquake speeds up,’ said Dr Fagereng.

In addition to drilling into an offshore area in New Zealand that experiences slow earthquakes, the team has been visiting regions in Japan, Namibia, Cyprus and the UK that would have experienced them in the past. Since they occur deep below the surface of the Earth, which is hard to study, the researchers have chosen areas that were once at the appropriate depths and conditions but have been brought to the surface over time due to erosion and uplift.

‘We are looking for structures that formed (as a result of slow earthquakes) and what they tell us about how the rocks accommodated that slip,’ said Dr Fagereng.

Exposed areas of rock on Kyushu Island, southern Japan, are among those being studied by researchers for evidence of past slow earthquakes. Image credit – Ake Fagareng

Creep

Their theory is that slow earthquakes occur when creep – tiny, continuous movements in a fault – accelerates throughout the fault zone, which can be several kilometres thick. Their field observations showed that a fault can be made up of different rock types of varying strength, such as solid basalt and granite and weaker clay-rich sediment. They suspected that stronger rocks start to fracture as creep speeds up due to weaker rocks moving around them but couldn’t explain exactly why.

Using information from their fieldwork, they’ve now developed a mathematical model to reproduce their theory and describe some of the physics behind it. A mixture of rocks with different deformation styles – such as breaking or bending – seems to be key. A proportion of creeping weak rock is required, as well as locally high enough pressure to cause some rock to rupture.

‘A possibility for these slow earthquakes is that you have a thick creeping zone with embedded stronger (rock) bits,’ said Dr Fagereng.

The team is planning to follow up with more field observations to refine their model. They still can’t explain why slow earthquakes occur at particular locations, for example, and why they are much more predictable than regular earthquakes, often occurring at set intervals.

Dr Fagereng thinks that findings from the project could help improve earthquake and tsunami forecasting. Last year, researchers found the first evidence of a slow earthquake preceding a regular earthquake in an area west of Fairbanks, Alaska, in the US. But the link between the two types of tremors isn’t well understood. In some cases, slow earthquakes could also alleviate stress that would otherwise build up and cause a larger earthquake.

‘We’re hoping to get somewhere on what the relation is between slow earthquakes and regular earthquakes,’ said Dr Fagereng. ‘And then that could potentially feed into models for what size earthquake you can get in different regions.’

Lab experiments could also shed light on the physics of slow earthquakes. Dr Nicolas Brantut from University College London in the UK and his colleagues are using bespoke machines that can deform rock samples at high pressures and temperatures to mimic conditions deep below the surface of the Earth.

Brittle-plastic transition

His team is particularly interested in the brittle-plastic transition, a region about 10 to 15 kilometres below the surface where the behaviour of rocks changes. Above this zone they are brittle, whereas beneath it they flow due to the high temperature and pressure which increase with depth. ‘The brittle part is where you have earthquakes,’ said Dr Brantut.

However, slow earthquakes seem to occur in the brittle-plastic zone, based on seismological observations. In many cases, they also take place at the same temperature and pressure conditions found in this region. But so far, slow slip events have typically been modelled based on the frictional forces at a fault without taking into account the peculiarities of the brittle-plastic transition zone where rocks start to flow.

‘The interactions between friction mechanisms and plastic flow mechanisms are not understood well enough to rule them out as mechanisms for slow earthquakes,’ said Dr Brantut.

As part of the RockDEaF project, Dr Brantut and his team are investigating the motion of rocks at the brittle-plastic transition. They are replicating the conditions in this region on pieces of rock centimetres long to see whether they fracture or flow. ‘We want to understand how these mechanisms compete with each other,’ said Dr Brantut.

Simulating

So far, the team has examined the brittle-plastic transition by simulating a fault in the Earth’s crust in a block of marble. They investigated the behaviour of the rock at different pressures and were expecting to find a sharp transition between brittle and plastic behaviour.

However, they were surprised to find that both behaviours occurred simultaneously under a wide range of pressure conditions. ‘This is something that I think nobody has realised before,’ said Dr Brantut. ‘The fact that we can have both friction and deformation in a continuum at the same time.’

Dr Brantut thinks that results from the project could help pin down where slow earthquakes could occur by determining the conditions and properties of rock that are required.

But they could also provide new clues about the depths at which regular earthquakes originate. Temperature below the surface of the Earth increases as a function of depth, which is typically an increase of 10°C to 40°C per kilometre in the crust. An earthquake’s lowest point of origin is thought to coincide with depths that reach 600°C, since rocks become supple when they surpass this temperature and therefore can’t fracture and generate an earthquake. However better understanding of the transition in rock behaviour should help determine if temperature is the deciding factor.

‘We should understand more about what really controls how deep we can expect earthquakes to propagate,’ said Dr Brantut.

See the full article here .

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From Eos: “A New Dimension to Plate Tectonics”

AGU

From Eos

10.28.19
Kate Wheeling

It’s easy to forget that plate tectonics is a relatively young theory. Researchers have known for only a little more than half a century that Earth’s lithosphere is essentially a jigsaw puzzle of rocky plates sitting on top of a viscous mantle. The plates violently collide, rip apart, or sideswipe each other, usually in excruciatingly slow motion.

Crucial to the theory of plate tectonics is subduction, the process in which a plate of dense oceanic crust collides with a plate of less dense crust and sinks into the mantle. Since the 1960s, scientists have shown that subduction zones are particularly important for driving processes like mountain building and seismic hazards like earthquakes, tsunamis, and volcanoes. But less well understood is how the three-dimensional structure of subduction zones can influence these phenomena.

Two main things have held scientists back from studying the structure of subduction zones, according to Gavin Hayes, a geophysicist at the U.S. Geological Survey (USGS): a lack of data on the 3-D geometry of subducting plates (also known as slabs) and a lack of computing power and software that would allow researchers to visualize these zones in three dimensions. But that’s all beginning to change.

Researchers now are benefiting from new tools to peek inside Earth’s interior, and massive leaps in computing power are allowing scientists to constrain and visualize the 3-D structure of slabs. These new 3-D models are providing critical insights into long-standing gaps in geology’s unifying theory of plate tectonics, including why some mountains arise and some earthquakes occur hundreds of kilometers away from plate boundaries.

“It’s quite an exciting time for this type of science,” Hayes said.

From 2-D to Reality

“Traditionally, seismologists and geodynamicists have been focused on a two-dimensional or cross-sectional viewpoint when studying subduction zones,” said Kirstie Haynie, a USGS Mendenhall Research Fellow.

Cross-sectional diagrams like this one are great starting points for understanding subduction zone dynamics. Credit: K. D. Schroeder, CC-BY-SA 4.0

Even school-age children are familiar with the two-dimensional cross sections of one plate diving beneath another and disappearing into the mantle. Such images are good approximations of subduction zone dynamics, according to experts, and useful for, say, describing the tectonic setting of a recent earthquake. But they can’t convey much about the three-dimensional geometry of the underlying slabs.

There has been an explosion of seismic data over the past 3 decades, as seismic recording stations have proliferated and new tools like seismic tomography [Physics of the Earth and Planetary Interiors] have emerged. These technologies have helped scientists like Hayes build databases like Slab2 [Science], which models the 3-D structure of slabs in subduction zones around the world.

“Seismic tomography is kind of like a CT [computerized tomography] scan of Earth’s interior,” Haynie said. The technique tracks the movement of seismic waves generated by earthquakes as they bounce off underground features, allowing researchers to reconstruct images of inner Earth. What all these new data show is that subduction zones are highly variable.

“What we’re seeing is that even in one subduction zone, the geometry of the downgoing plate varies—in its sense of curvature, in the inclination of the subduction zone, and also how deep the subducted plate goes,” said Margarete Jadamec, a geodynamicist and assistant professor at the University of Buffalo in New York.

Last year, Jadamec and colleagues [Earth and Space Science] fed data on slab morphologies into an open-source visualization software called the ShowEarthModel to create 3-D videos [Earth and Space Science] of every major subduction zone around the world.

“These virtual tours of the various subduction zones are a way for researchers to build a mental picture of what the subduction zone looks like in 3-D,” Jadamec said. “You realize with these movies that a 2-D representation is inadequate because we can actually see in three dimensions [that] the slab varies.”

The data points are tied to their geographic location on the virtual Earth, so viewers can see exactly where the slab geometries are changing. “It forces you to honor the data,” Jadamec said.

Armed with better data and more accurate renderings of what slabs and subduction zones look like, researchers can begin asking questions about how their geometry influences seismic hazards and processes like mantle flow. And evidence is mounting that the 3-D geometry of slabs has a significant impact on the geologic processes taking place at plate boundaries. This has helped Jadamec and others address some long-standing gaps in the original theory of plate tectonics.

A Mystery Solved

“Inherent in the theory of plate tectonics is that the plates are actually rigid, and the deformation is concentrated at the boundaries,” Jadamec said. But that’s not what we actually see on Earth. “What we find in many locations is that we have mountain building and earthquakes that occur far from the plate boundary, like 500 or 1,000 kilometers away,” she said.

Take Alaska, which sits atop the North American plate just where it meets the Pacific plate. The state has mountain ranges, volcanoes, and earthquakes in areas where the simple theory of plate tectonics wouldn’t have predicted them.

For instance, there are tall mountains near the Alaska-Aleutian subduction zone where the plates converge, but Denali, the tallest mountain peak in North America, is some 500 kilometers inland in the Central Alaska Range. Researchers long wondered why the deformation occurred so far from the plate boundary.

Alaska also has some unusual volcanoes. Volcanoes tend to form directly over subduction zones, but in some locations, including in Alaska, they pop up off to the side of subducting slabs.

Finally, Alaska is also the site of the second-largest earthquake ever recorded with modern seismometers, the magnitude 9.2 temblor known as the Great Alaska earthquake of 1964 or the Good Friday earthquake.

To better understand these anomalies, Jadamec created one of the first large-scale 3-D geodynamic simulations of the subduction zone in the region. This allowed her to study the area in southeastern Alaska where the slab comes to an end.

Until recently, researchers tended to ignore slab edges because it was too complex to numerically model the ways in which the mantle arcs around the slab edge, a process called toroidal flow that was first demonstrated in laboratory experiments.

In the first studies of 3-D flow dynamics, researchers used tanks filled with a gooey medium like honey to stand in for the mantle, pressed hard slabs into it, and tracked the flow of the viscous liquid around the edges. As computing resources advanced, researchers like Jadamec began using computational fluid dynamics simulations.

“One of the things that the 3-D slab models like the fluid dynamics experiments show is that in addition to toroidal flow, you get vertical upwelling zones,” Jadamec said. “These upwelling zones seem to spatially correlate with where we observe those anomalous volcanoes on Earth’s surface.”

Building on this work, Jadamec and Haynie went looking for an explanation for Denali in the slab geometry data and found one. “In south central Alaska, there’s a segment of the slab that’s horizontal or flat beneath the overriding plate,” Haynie said. “We think it’s coupled strongly to the overriding plate and that the flat slab is kind of pulling that overriding plate along the path of subduction.”

When Jadamec’s numerical model accounted for both the flat slab and the activity of a nearby strike-slip fault known as the Denali fault, it was able to accurately predict uplift exactly where Denali is located.

That coupling might also explain why the region is prone to such large earthquakes, according to Haynie, but she cautions that there are other factors at play in subduction zones besides the dip angle that could contribute to seismogenesis. Several other studies that look at slab geometries and earthquakes suggest that flat slabs have a role in generating large quakes, including a 2016 paper in Science that found that the biggest historic quakes tended to correlate with areas where 3-D subduction geometry models show that the subducting slab is broad and flat.

“I still think it’s an open question exactly what role subducting geometry plays in big earthquakes,” Hayes said. “But we’re beginning to build the data sets that allow us to better address these questions.”

From Earth to the Cloud

The major challenge now is that our understanding of the 3-D geometries of these underground slabs is “incomplete and constantly changing,” said Haynie, who is building a cloud-based version of the USGS Slab database that can be constantly updated, so that researchers working with them will always have the most up-to-date information feeding their models. “Every earthquake is a new data point.”

The USGS is focused on mitigating hazards. “We’re trying to use these geometries to inform things like our seismic hazard maps, and our understanding of seismic hazards more broadly, so that we can hopefully better mitigate [the damage from] these big earthquakes in the future,” Hayes said. But he notes that these 3-D geometries can also help answer questions about where volcanoes and mountain ranges form.

“These are questions that have been addressed before,” Hayes said, “but now that we’re getting these better data sets, it’s important that we revisit them and see [whether] some of the theories that we’ve thrown out in the past 50 years have held up.”

See the full article here .

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

From Lawrence Berkeley National Lab: “New Sensor Could Shake Up Earthquake Response Efforts”

From Lawrence Berkeley National Lab

July 11, 2019
Christina Procopiou

Berkeley Lab technology could reduce time needed to declare buildings affected by earthquakes safe and sound.

(Credit: iStockphoto)

Last week’s massive southern California earthquakes shut down Ridgecrest Regional Hospital throughout the July 4 holiday weekend while the tiny town of Ridgecrest assessed the damages. A new optical sensor developed at Lawrence Berkeley National Laboratory (Berkeley Lab) could speed up the time it takes to evaluate whether critical buildings like these are safe to occupy shortly after a major earthquake.

The technology – which autonomously captures and transmits data depicting the relative displacement between two adjacent stories of a shaking building – is able to provide reliable information about building damage immediately following an earthquake, and could expedite efforts to safely assess, repair, and reoccupy buildings post-quake.

Scientists and engineers at Berkeley Lab, Lawrence Livermore National Laboratory, and the University of Nevada-Reno began working to design an optical method of measuring interstory drift within buildings in 2015. After four years of extensive peer-reviewed research and simulative testing at the University of Nevada’s Earthquake Engineering Laboratory, the Discrete Diode Position Sensor (DDPS) will be deployed for the first time this summer in a multi-story building at Berkeley Lab – which sits adjacent to the Hayward Fault, considered one of the most dangerous faults in the United States.

“Until now, there’s been no way to accurately and directly measure drift between building stories, which is a key parameter forassessing earthquake demand in a building,” said David McCallen, a senior scientist in the Energy Geosciences Division at Berkeley Lab and faculty member at the University of Nevada, who leads the research collaboration.

The debut of DDPS comes as governments at every level make post-earthquake building inspection and reoccupation a central focus of response planning, and as the highly anticipated next generation of remote connectivity – 5G – becomes reality for rapid data transmission. “We are excited that this sensor technology is now ready for field trials, at a time when post-earthquake response strategies have evolved to prioritize safe, continued building functionality and re-occupancy in addition to ‘life safety,’” McCallen said.

DDPS is a small device that will be positioned between building stories to detect interstory drift and transmit data about building damages to response planners. Its debut comes as governments at every level make post-earthquake building inspection and reoccupation a central focus of response planning, and as the highly anticipated next generation of remote connectivity–5G–becomes reality. (Credit Diana Swantek/Berkeley Lab)

Optics makes a difference in monitoring seismic structural health

Measuring building interstory drift has been a factor in assessing buildings for post-earthquake damage for some time, yet finding a reliable method to do so has been fraught with challenges. Traditionally, engineers mounted strong motion earthquake accelerometers at select elevations to secure data on the back-and-forth and side-to-side force imposed on a shaking building. But processing the acceleration data from these instruments to obtain building drift displacements is very challenging due to the frequency limitations of the sensors, especially when buildings have sustained permanent displacements associated with damage. Even more difficult is receiving data quickly enough to inform decision-making on continuity of operations and occupant safety. In addition, because typical building accelerometer-based instrumentation can be quite costly, systems tend to be very sparse with accelerometers on relatively few buildings.

DDPS leverages a promising new alternative for directly measuring building interstory drift that combines laser beams with optical sensors. This technique centers around projecting laser light across a story height to sense the position at which the light strikes a detector located on the adjacent building floor to directly measure structural drift. The tool developed at Berkeley Lab relies on utilizing a laser source and position sensitive detector. Making use of a geometric array of small, inexpensive light-sensitive photodiodes, the sensor is able to instantly track the position of an impinging laser beam.

A new sensor developed at Lawrence Berkeley National Laboratory combines laser beams with a position sensitive detector to directly measure drift between building stories, an essential part of assessing earthquake damages in a building and deeming them safe to reoccupy. (Credit Diana Swantek/Berkeley Lab)

“Previous generations of DDPS were quite a bit larger than the system we are now able to deploy,” says McCallen. “Based on design advancements and lessons learned, the sensor is a quarter of the size of our original sensor design, but features 92 diodes staggered in a rectangular array so that the laser beam is always on one or more diodes.”

So far, DDPS has held up to three rounds of rigorous experimental shake table testing.

“The rigorous testing the DDPS has undergone indicates how the drift displacements measured on the three testbeds compared to representative drifts that could be achieved on an actual full-scale building undergoing strong shaking from an earthquake,” McCallen said.

Why DDPS is smart for cities

The most populous town affected by the earthquakes in southern California earlier this month was Ridgecrest itself, a city of 29,000 which sits at the epicenter of a magnitude 7.1 earthquake which took place on July 5. Even though this is a small population center, the building damage estimates are still in the $100-million range.

If an earthquake of that magnitude were to hit Los Angeles 150 miles to the south of tiny Ridgecrest, or San Francisco, nearly 400 miles north, literally hundreds to thousands of buildings would be at stake for damage. In that scenario, the ability to measure and display key interstory drift information immediately after an earthquake would provide critical new data for making informed decisions on building occupancy – giving first responders information to help guide their efforts to evacuate a building, and municipalities the potential to maintain functional use of important facilities such as hospitals.

In addition, understanding a building’s drift profile would allow a quick determination of building damage potential, letting building inspectors know where to look for potential damage. This will be an important capability in moving beyond time-consuming and challenging manual inspections of hundreds of buildings after the next major urban earthquake.

McCallen noted, “The major earthquakes that struck in southern California this past week serve as a reminder of the risks associated with seismic activity across many regions of the United States. These events put an exclamation point on the need for continued societal focus on earthquake readiness and resilience, including an ability to provide the sensors and data analysis that can rapidly measure infrastructure health and inform the most effective response after the next major quake.”

This research was funded by the U.S. Department of Energy’s (DOE) Nuclear Safety Research and Development (NSR&D) Program managed by the Office of Nuclear Safety within the DOE Office of Environment, Health, Safety and Security. An objective of the NSR&D program is to establish an enduring Departmental commitment and capability to utilize NSR&D in preventing and/or reducing high consequence-low probability hazards and risks posed by DOE and NNSA nuclear facilities, operations, nuclear explosives, and environmental restoration activities.

See the full article here .

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Bringing Science Solutions to the World

In the world of science, Lawrence Berkeley National Laboratory (Berkeley Lab) is synonymous with “excellence.” Thirteen Nobel prizes are associated with Berkeley Lab. Seventy Lab scientists are members of the National Academy of Sciences (NAS), one of the highest honors for a scientist in the United States. Thirteen of our scientists have won the National Medal of Science, our nation’s highest award for lifetime achievement in fields of scientific research. Eighteen of our engineers have been elected to the National Academy of Engineering, and three of our scientists have been elected into the Institute of Medicine. In addition, Berkeley Lab has trained thousands of university science and engineering students who are advancing technological innovations across the nation and around the world.

Berkeley Lab is a member of the national laboratory system supported by the U.S. Department of Energy through its Office of Science. It is managed by the University of California (UC) and is charged with conducting unclassified research across a wide range of scientific disciplines. Located on a 202-acre site in the hills above the UC Berkeley campus that offers spectacular views of the San Francisco Bay, Berkeley Lab employs approximately 3,232 scientists, engineers and support staff. The Lab’s total costs for FY 2014 were $785 million. A recent study estimates the Laboratory’s overall economic impact through direct, indirect and induced spending on the nine counties that make up the San Francisco Bay Area to be nearly $700 million annually. The Lab was also responsible for creating 5,600 jobs locally and 12,000 nationally. The overall economic impact on the national economy is estimated at $1.6 billion a year. Technologies developed at Berkeley Lab have generated billions of dollars in revenues, and thousands of jobs. Savings as a result of Berkeley Lab developments in lighting and windows, and other energy-efficient technologies, have also been in the billions of dollars.

Berkeley Lab was founded in 1931 by Ernest Orlando Lawrence, a UC Berkeley physicist who won the 1939 Nobel Prize in physics for his invention of the cyclotron, a circular particle accelerator that opened the door to high-energy physics. It was Lawrence’s belief that scientific research is best done through teams of individuals with different fields of expertise, working together. His teamwork concept is a Berkeley Lab legacy that continues today.

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From Caltech: “Lessons from the 1994 Northridge Quake”

From Caltech

01/17/2014 [Just now in social media]

Written by Cynthia Eller
Contact:
Deborah Williams-Hedges
(626) 395-3227
debwms@caltech.edu

A portion of the Golden State Freeway in Gavin Canyon that collapsed during the 1994 Northridge earthquake. Credit: FEMA

Current Earthquake Research at Caltech

Since the magnitude 6.7 Northridge earthquake 20 years ago (January 17, 1994), researchers at the California Institute of Technology (Caltech) have learned much more about where earthquakes are likely to happen, and how danger to human life and damage to property might be mitigated when they do occur.

“The Northridge quake really heralded the beginning of a new era in earthquake research, not only in southern California, but worldwide,” says Michael Gurnis, John E. and Hazel S. Smits Professor of Geophysics, and director of the Seismological Laboratory at Caltech.

In the years just prior to the Northridge earthquake, Caltech launched a program called TERRAscope supported by the Whittier foundations, which placed high-quality seismic sensors near where earthquakes occur. The Northridge earthquake was, in effect, the first test of TERRAscope in which Caltech scientists could infer the distribution of an earthquake rupture on subsurface faults and directly measure the associated motion of the ground with greater accuracy. “With a modern digital seismic network, the potential of measuring ground shaking in real time presented itself,” says Gurnis. “The real time view also gave first responders detailed maps of ground shaking so that they could respond to those in need immediately after a quake,” adds Egill Hauksson, senior research associate at Caltech.

To give us this new view of earthquakes, Caltech collaborated with the U.S. Geological Survey (USGS) and the California Geological Survey to form TriNet, through which a vastly expanded network of instrumentation was put in place across southern California. Concurrently, a new network of continuously operated GPS stations was permanently deployed by a group of geophysicists under the auspices of the Southern California Earthquake Center, funded by the USGS, NASA, NSF, and the Keck Foundation. GPS data are used to measure displacements as small as 1 millimeter per year between stations at any two locations, making it possible to track motions during, between, and after earthquakes. Similar and even larger networks of seismometers and GPS sensors have now been deployed across the United States, especially EarthScope, supported by the NSF, and in countries around the world by various respective national agencies like the networks deployed by the Japanese government.

Initially, says Gurnis, there were not many large earthquakes to track with the new dense network of broadband seismic instruments and GPS devices. That all changed in December 2004 with the magnitude 9.3 earthquake and resulting tsunami that struck the Indian Ocean off the west coast of Sumatra, Indonesia. Quite abruptly, Caltech scientists had an enormous amount of information coming in from the instrumentation in Indonesia previously deployed by the Caltech Techtonics Observatory with support from the Gordon and Betty Moore Foundation. By the time the magnitude 9.0 Tohoku-Oki earthquake hit northern Japan in 2011, the Seismological Laboratory at Caltech had developed greatly expanded computing power capable of ingesting massive amounts of seismic and geodetic data. Within weeks of the disaster, a team led by Caltech professor of geophysics Mark Simons using data from GPS systems installed by the Japanese had produced extensive measurements of ground motion, as well as earthquake models constrained by this data, that provided new insight into the mechanics of plate tectonics and fault ruptures.

The Tohoku-Oki earthquake was unprecedented: scientists estimate that over 50 meters of slip on the subsurface fault occurred during the devastating earthquake. Currently, scientists at Caltech and the Jet Propulsion Laboratory are prototyping new automated systems for exploiting the wealth of GPS and satellite imaging data to rapidly provide disaster assessment and situational awareness as events occur around the globe. “We are now at a juncture in time where new observational capabilities and available computational power will allow us to provide critical information with unprecedented speed and resolution,” says Simons.

Earthquakes are notable—and, for many, particularly upsetting—because they have always come without warning. Earthquakes do in fact happen quickly and unpredictably, but not so much so that early-warning systems are impossible. In a Moore Foundation-supported collaboration with UC Berkeley, the University of Washington, and the USGS, Caltech is developing a prototype early-warning system that may provide seconds to tens of seconds of warning to people in areas about to experience ground shaking, and minutes of warning to people potentially in the path of a tsunami. Japan invested heavily in an earthquake early-warning system after the magnitude 6.9 Kobe earthquake that occurred January 17, 1995, on the one-year anniversary of the Northridge earthquake, and the system performed well during the Tohoku-Oki earthquake. “It was a major scientific and technological accomplishment,” says Gurnis. “High-speed rail trains slowed and stopped as earthquake warnings came in, and there were no derailments as a result of the quake.”

Closer to home, Caltech professor of geophysics Robert Clayton has aided local earthquake detection by distributing wallet-sized seismometers to residents of the greater Pasadena area to keep in their homes. The seismometers are attached to a USB drive on each resident’s computer, which is to remain on at all times. The data from these seismometers serve two functions: they record seismic activity on a detailed block-by-block scale, and, in the event of a large earthquake, they can help identify areas that are hardest hit. One lesson learned in the Northridge earthquake was that serious damage can occur far from the epicenter of an earthquake. The presence of many seismometers could help first responders to find the worst-affected areas more quickly after an earthquake strikes.

Caltech scientists have also been playing a leading role in the large multi-institutional Salton Seismic Imaging Project. The project is mapping the San Andreas fault and discovering additional faults by setting off underground explosions and underwater bursts of compressed air and then measuring the transmission of the resulting sound waves and vibrations through sediment. According to Joann Stock, professor of geology and geophysics at Caltech, knowing the geometry of faults and the composition of nearby sediments informs our understanding of the types of earthquakes that will occur in the future, and the reaction of the local sediment to ground shaking.

In addition, Caltech scientists learned much through simulating—via both computer modeling and physical modeling techniques—how earthquakes occur and what they leave in their aftermath.

Computer simulations of how buildings respond during earthquakes recently allowed Caltech professors Thomas Heaton, professor of engineering seismology, and John Hall, professor of civil engineering, to estimate the decrease in building safety caused by the existence of defective welds in steel-frame structures, a problem identified after the Northridge earthquake. Researchers simulated the behavior of different 6- and 20-story building models in a variety of potential earthquake scenarios created by the Southern California Earthquake Center for the Los Angeles and San Francisco areas. The study showed that defective welds make a building significantly more susceptible to collapse and irreparable damage, and also found that stiffer, higher-strength buildings perform better than more flexible, lower-strength designs.

Caltech professor of mechanical engineering and geophysics Nadia Lapusta recently used computer simulations of numerous earthquakes to determine what role “creeping” fault slip might play in earthquake events. It has been known for some time that, in addition to the rapid displacements that trigger earthquakes, land also slips very slowly along fault lines, a process that was thought to stop incoming earthquake rupture. Instead, Lapusta’s models show that these “stable segments” may become seismically active in an earthquake, accelerating and even strengthening its motions. Lapusta hypothesizes that this was one factor behind the severity of the 2011 Tohoku-Oki earthquake. Taking advantage of advances in computer modeling, Lapusta and her colleague Jean-Philippe Avouac, Earle C. Anthony Professor of Geology at Caltech, have created a comprehensive model of a fault zone, including both its earthquake activity and its behavior in seismically quiet times.

Physical modeling of earthquakes is carried out at Caltech via collaborative efforts between the Divisions of Geological and Planetary Sciences and of Engineering and Applied Science. A series of experiments conducted by Ares Rosakis, the Theodore von Kármán Professor of Aeronautics and Mechanical Engineering, and collaborators including Lapusta and Hiroo Kanamori, the John E. and Hazel S. Smits Professor of Geophysics, Emeritus, used polymer plates to simulate land masses. Stresses were then created at various angles to the fault lines between the plates to set off earthquake-like activity. The motion in the polymer plates was measured by laser vibrometers while a high-speed camera recorded the movements in detail, yielding unprecedented data on the propagation of seismic waves. Researchers learned that strike-slip faults like the San Andreas may rupture in more than one direction (it was previously believed that these faults had a preferred direction), and that in addition to sliding along a fault, ruptures may occur in a “self-healing” pulselike manner in which a seismic wave “crawls” down a fault line. A third study drew conclusions about how faults will behave—in either a classic cracklike sliding rupture or in a pulselike rupture—depending on the angle at which compression forces strike the fault.

“Northridge was a devastating earthquake for Los Angeles, and there was a massive amount of damage,” Gurnis says, “But in some sense, we stepped up to the plate after Northridge to determine what we could do better. And as a result we have ushered in an era of dense, high-fidelity geophysical networks on top of hazardous faults. We’ve exploited these networks to better understand how earthquakes occur, and we’ve pushed the limits such that we are now at the dawn of a new era of earthquake early warning in the United States. That’s because of Northridge.”

See the full article here .

Earthquake Alert

Earthquake Alert

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

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

Get the app in the Google Play store.

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

Meet The Quake-Catcher Network

Quake-Catcher Network

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

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

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

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

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

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

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

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

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

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

Below, the QCN Quake Catcher Network map

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

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

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

The primary project partners include:

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

The Earthquake Threat

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

Part of the Solution

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

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

System Goal

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

Current Status

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

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

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

Authorities

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

For More Information

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

Learn more about EEW Research

ShakeAlert Fact Sheet

ShakeAlert Implementation Plan

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

Stem Education Coalition

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

Caltech campus

Caltech campus

From The New York Times: “A.I. Is Helping Scientists Predict When and Where the Next Big Earthquake Will Be”

From The New York Times

Oct. 26, 2018

Thomas Fuller
Cade Metz

Jean-Francois Podevin

Countless dollars and entire scientific careers have been dedicated to predicting where and when the next big earthquake will strike. But unlike weather forecasting, which has significantly improved with the use of better satellites and more powerful mathematical models, earthquake prediction has been marred by repeated failure.

Some of the world’s most destructive earthquakes — China in 2008, Haiti in 2010 and Japan in 2011, among them — occurred in areas that seismic hazard maps had deemed relatively safe. The last large earthquake to strike Los Angeles, Northridge in 1994, occurred on a fault that did not appear on seismic maps.

Now, with the help of artificial intelligence, a growing number of scientists say changes in the way they can analyze massive amounts of seismic data can help them better understand earthquakes, anticipate how they will behave, and provide quicker and more accurate early warnings.

“I am actually hopeful for the first time in my career that we will make progress on this problem,” said Paul Johnson, a fellow at the Los Alamos National Laboratory who is among those at the forefront of this research.

Well aware of past earthquake prediction failures, scientists are cautious when asked how much progress they have made using A.I. Some in the field refer to prediction as “the P word,” because they do not even want to imply it is possible. But one important goal, they say, is to be able to provide reliable forecasts.

The earthquake probabilities that are provided on seismic hazard maps, for example, have crucial consequences, most notably in instructing engineers how they should construct buildings. Critics say these maps are remarkably inexact.

A map of Los Angeles lists the probability of an earthquake producing strong shaking within a given period of time — usually 50 years. That is based on a complex formula that takes into account, among other things, the distance from a fault, how fast one side of a fault is moving past the other, and the recurrence of earthquakes in the area.

A study led by Katherine M. Scharer, a geologist with the United States Geological Survey, estimated dates for nine previous earthquakes along the Southern California portion of the San Andreas fault dating back to the eighth century. The last big earthquake on the San Andreas was in 1857.

Since the average interval between these big earthquakes was 135 years, a common interpretation is that Southern California is due for a big earthquake. Yet the intervals between earthquakes are so varied — ranging from 44 years to 305 years — that taking the average is not a very useful prediction tool. A big earthquake could come tomorrow, or it could come in a century and a half or more.

This is one of the criticisms of Philip Stark, an associate dean at the University of California, Berkeley, at the Division of Mathematical and Physical Sciences. Dr. Stark describes the overall system of earthquake probabilities as “somewhere between meaningless and misleading” and has called for it to be scrapped.

The new A.I.-related earthquake research is leaning on neural networks, the same technology that has accelerated the progress of everything from talking digital assistants to driverless cars. Loosely modeled on the web of neurons in the human brain, a neural network is a complex mathematical system that can learn tasks on its own.

Scientists say seismic data is remarkably similar to the audio data that companies like Google and Amazon use in training neural networks to recognize spoken commands on coffee-table digital assistants like Alexa. When studying earthquakes, it is the computer looking for patterns in mountains of data rather than relying on the weary eyes of a scientist.

“Rather than a sequence of words, we have a sequence of ground-motion measurements,” said Zachary Ross, a researcher in the California Institute of Technology’s Seismological Laboratory who is exploring these A.I. techniques. “We are looking for the same kinds of patterns in this data.”

Brendan Meade, a professor of earth and planetary sciences at Harvard, began exploring these techniques after spending a sabbatical at Google, a company at the forefront of A.I. research.

His first project showed that, at the very least, these machine-learning methods could significantly accelerate his experiments. He and his graduate students used a neural network to run an earthquake analysis 500 times faster than they could in the past. What once took days now took minutes.

Dr. Meade also found that these A.I. techniques could lead to new insights. In the fall, with other researchers from Google and Harvard, he published a paper showing how neural networks can forecast earthquake aftershocks. This kind of project, he believes, represents an enormous shift in the way earthquake science is done. Similar work is underway at places like Caltech and Stanford University.

“We are at a point where the technology can do as well as — or better than — human experts,” Dr. Ross said.

Driving that guarded optimism is the belief that as sensors get smaller and cheaper, scientists will be able to gather larger amounts of seismic data. With help from neural networks and similar A.I. techniques, they hope to glean new insights from all this data.

Dr. Ross and other Caltech researchers are using these techniques to build systems that can more accurately recognize earthquakes as they are happening and anticipate where the epicenter is and where the shaking will spread.

Japan and Mexico have early warning systems, and California just rolled out its own. But scientists say artificial intelligence could greatly improve their accuracy, helping predict the direction and intensity of a rupture in the earth’s crust and providing earlier warnings to hospitals and other institutions that could benefit from a few extra seconds of preparation.

“The more detail you have, the better your forecasts will be,” Dr. Ross said.

Scientists working on these projects said neural networks have their limits. Though they are good at finding familiar signals in data, they are not necessarily suited to finding new kinds of signals — like the sounds tectonic plates make as they grind together.

But at Los Alamos, Dr. Johnson and his colleagues have shown that a machine-learning technique called “random forests” can identify previously unknown signals in a simulated fault created inside a lab. In one case, their system showed that a particular sound made by the fault, which scientists previously thought was meaningless, was actually an indication of when an earthquake would arrive.

Some scientists, like Robert Geller, a seismologist at the University of Tokyo, are unconvinced that A.I. will improve earthquake forecasts. He questions the very premise that past earthquakes can predict future ones. And ultimately, he said, we would only know the effectiveness of A.I. forecasting when earthquakes can be predicted beyond random chance.

“There are no shortcuts,” Dr. Geller said. “If you cannot predict the future, then your hypothesis is wrong.”

See the full article here .

Earthquake Alert

Earthquake Alert

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

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

Get the app in the Google Play store.

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

Meet The Quake-Catcher Network

Quake-Catcher Network

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

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

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

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

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

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

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

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

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

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

Below, the QCN Quake Catcher Network map

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

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

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

The primary project partners include:

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

The Earthquake Threat

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

Part of the Solution

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

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

System Goal

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

Current Status

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

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

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

Authorities

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

For More Information

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

Learn more about EEW Research

ShakeAlert Fact Sheet

ShakeAlert Implementation Plan

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

Please help promote STEM in your local schools.

Stem Education Coalition

From UCLA Newsroom: “The evolution of earthquake science”

From UCLA Newsroom

October 11, 2018

Jonathan Stewart, a professor in the UCLA Department of Civil and Environmental Engineering, at a Los Angeles Department of Water and Power facility.

It’s a scene of post-mayhem disaster. In front of the Acacia residential building on the west end of the UCLA campus. Victims are everywhere, bleeding, confused, in and out of consciousness. A small boy in a baseball hat and shorts is laid out on a red tarp. “Very low pulse,” says one of the people who helped carry him over, before rushing back to the search and rescue. It’s hard to tell if anyone hears her, given the commotion. Nearby, a woman sits upright, a drop of blood rolling out of her ear and down her cheek, and another woman props her bloodied leg inside a makeshift cardboard splint.

A few dozen first responders move victims onto colorcoded tarps — green for the most stable, yellow for those in need of a medic and red for the most critical. One of the vested first responders kneels beside the boy to check his pulse, and quickly stands up again. “We have a dead over here,” she calls out. But there’s no time to stop.

This is the aftermath of a 6.8 magnitude earthquake centered on the Santa Monica Fault just south of campus. It’s the “big one” that Southern Californians had known could one day happen. That day is today.

Except it’s not. The “victims” are all actors, the injuries painted on and the small boy alive and well. The first responders are volunteers from the Community Emergency Response Team, running a drill to test emergency response procedures on campus.

While this 6.8 quake didn’t actually happen, through the work of researchers and scientists across UCLA, we know with certainty the probable impact of such a temblor, how to warn those who would feel its shaking, how to plan around its destructive power and even how to ensure that buildings like the Acacia dorms don’t fall. From the deepest motions of our planet’s structure to the foundations of our buildings to the crucial urban systems underpinning modern society, UCLA research is increasing our understanding of how the land beneath us moves and how to survive a major quake.

It’s estimated that up to 3,000 people died in San Francisco in 1906 as a result of the 7.9 magnitude quake, and more than 140,000 died in the 1923 Great Kanto earthquake in Japan. Fortunately, in more recent years, particularly in the United States, earthquake-caused deaths have been relatively rare. Unlike in the past, when buildings crumbled and crushed the people inside, we now know how to construct buildings that can withstand quakes.

We learned from buildings that fell. In 1994, a 6.7 magnitude earthquake that struck in the San Fernando Valley destroyed or significantly damaged an estimated 90,000 buildings. Of the approximately 60 people killed, 33 were in buildings that fell. The most common were small apartment buildings perched over space left largely empty for parking. With enough shaking, the apartments come crashing down on the mostly hollow space below.

Scott Brandenberg, a professor of civil and environmental engineering at the UCLA Henry Samueli School of Engineering and Applied Science, studies the impact of earthquakes on the built environment. He lives in a soft story building.“It’s hard to find buildings in the area I can afford,” he says. Soft story buildings were not designed to resist earthquake forces specified in the current building code and should be evaluated for retrofit. A number of these buildings collapsed during the 1994 Northridge earthquake.

Today, Brandenberg’s building, as well as thousands of others across the region, have been retrofitted through mandatory retrofit ordinances.

Learning from the past is key to UCLA’s earthquake research across multiple fields. Brandenberg, for example, is creating an international database on liquefaction, the phenomenon sometimes observed during earthquakes in which soil flows like a liquid, causing land to slide and foundations of buildings to slip away. He and his colleagues are collecting case studies globally that shed light on the consequences of liquefaction. “We’ve never really had a database that was available to the whole community,” says Brandenberg. He hopes broad access to the data will help standardize the science behind liquefaction.

Researchers can’t wait around for earthquakes to strike; the stakes are too high. Jonathan Stewart, a professor in the Department of Civil and Environmental Engineering, has been collecting global data on earthquake impacts on levees and their associated drinking water systems. His major area: a 1,100-mile network of levees in California that directs water into the State Water Project’s drinking and agricultural water conveyances and prevents salt water intrusion from the San Francisco Bay.

“A good 40 percent of the water in Southern California is coming through this system,” he says. “So the stability and viability of this system is really a big deal. For the system to work, the whole thing has to work. You can’t just analyze individual sections. So we’ve developed methods to do that.”

Based on previous seismic activity near levee systems in places like Japan, Stewart and his colleagues can determine the dynamic properties of the peat that makes up much of the structure of the foundation beneath the levees in the Delta, learning how much levees can settle, which can lead to overtopping and cause erosion. They also determine how much soil to keep in reserve to patch breaches that occur. Add in computer modeling, and they can predict worst-case scenarios for disruptions to the system and plan how to respond.

This type of systemic, model-based thinking is new for earthquake research, a field that has been largely based on observations of specific events. “[Research] was being done on a small-time basis: individual faculty and their grad students working on something, producing a paper, other people doing the same thing, and we get all these disparate documents out there,” Stewart explains. “And then somebody has to figure out what to do with it all. We’re trying to change the paradigm by which this research is done.”

Practitioners outside the university who are applying this information to the real world say UCLA’s work is making a difference. Ronald T. Eguchi is president and CEO of Long Beach-based ImageCat, which creates earthquake maps and hazard exposure models for buildings and infrastructure. The company serves clients like NASA and FEMA, as well as private insurance companies. Eguchi says the data coming out of UCLA has helped make these maps more accurate.

“Without [that UCLA] research, I don’t think we’d be able to come up with these quantitative assessments,” he says. “We use that information to [learn] what the extent of displacement or ground failure would be.”

Useful data can come from surprising sources. Engineering Professor Ertugrul Taciroglu, who studies earthquake effects on urban infrastructure — ports, bridges, power lines — has developed a way to use the abundant images available from Google to visually analyze infrastructures and develop predictive simulation models to quantify their seismic risks.

“My students and I developed computer codes that will locate each bridge and examine it through Google Street from multiple angles. Our algorithms extract key measurements, such as column heights and cross-sectional dimension. We use those measurements to create a structural analysis model. We intend to do that for all 25,000 bridges in California,” he says. These images are remarkably accurate. Taciroglu says he has checked his models using Google’s images against Caltrans’ original bridge blueprints, and the measurements match up at the sub-inch level.

Google Earth also has been a rich source of data for power lines and other lifeline transmission corridors that provide electricity across the state. “I can create structural analysis models of power distribution networks by going around with my preprogrammed robot inside Google Earth and extracting where the transmission towers are, the length of the cables, the sag of the cables,” Taciroglu adds. “Because I know where they are, I know what kind of an earthquake shaking we can expect in the future for each structure.”

Knowing how transmission lines may fail in a big earthquake can show, for example, what hospitals should be better equipped with backup power. Modeling which bridges could fail will help us understand how to prevent parts of cities from being cut off from essential services. Taciroglu says a dream project would be to integrate all this information into one massive model that encompasses the full complexity of an entire urban region and all its interrelated risks. Such a tool would be immensely valuable to government agencies, facility operators and insurance agencies.

This kind of metropolitan-wide thinking may not be far off. A task force of UCLA earthquake researchers is developing plans to better integrate systems thinking and earthquake consciousness into the operations of city and county entities, such as utilities. “Lifeline infrastructure can be impacted by big earthquakes,” says Ken Hudnut, a geophysicist for Risk Reduction at the U.S. Geological Survey and a lecturer in UCLA’s Department of Civil and Environmental Engineering, who advises the L.A. Mayor’s Office of Resilience.

See the full article here .

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

Stem Education Coalition

Earthquake Alert

Earthquake Alert

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

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

Get the app in the Google Play store.

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

Meet The Quake-Catcher Network

Quake-Catcher Network

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

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

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

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

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

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

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

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

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

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

Below, the QCN Quake Catcher Network map

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

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

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

The primary project partners include:

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

The Earthquake Threat

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

Part of the Solution

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

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

System Goal

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

Current Status

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

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

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

Authorities

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

For More Information

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

Learn more about EEW Research

ShakeAlert Fact Sheet

ShakeAlert Implementation Plan

For nearly 100 years, UCLA has been a pioneer, persevering through impossibility, turning the futile into the attainable.

We doubt the critics, reject the status quo and see opportunity in dissatisfaction. Our campus, faculty and students are driven by optimism. It is not naïve; it is essential. And it has fueled every accomplishment, allowing us to redefine what’s possible, time after time.

This can-do perspective has brought us 12 Nobel Prizes, 12 Rhodes Scholarships, more NCAA titles than any university and more Olympic medals than most nations. Our faculty and alumni helped create the Internet and pioneered reverse osmosis. And more than 100 companies have been created based on technology developed at UCLA.

From temblor: “Pele, the Hawai’i Goddess of Fire, Lightening, Wind, and Volcanoes”

From temblor

May 5, 2018
Jason R. Patton, Ph.D.
Ross Stein, Ph.D.
Volkan Sevilgen, M.Sc.

At 12:46 p.m. HST, a column of robust, reddish-brown ash plume occurred after a magnitude 6.9 South Flank of Kïlauea earthquake shook the Big Island of Hawai‘i. (USGS HVO)

Hawai’i Earthquakes and Eruptions

Over the past week there has been a flurry of earthquake activity on the Big Island of Hawai’i. These earthquakes are related to the volcanic activity associated with Kïlauea magmatism. As magma rises and moves within the magma chamber, we can infer the motion direction and velocity as earthquakes respond to these changes in magma pressure. At the time we write this, there have been over 900 shallow depth earthquakes reported on the U.S. Geological Survey earthquake website.

Hawai’i as seen in Google Earth, 3X vertical exaggeration. One week of earthquakes from USGS (orange dots)

Below is a map that shows seismicity from the past week. Blue circles are located relative to the Pu’u ‘Ō’ō-Kupaianaha Volcano April 30 activity and the May 3 and May 4 fissure eruptions near the Leilani Estates (a residential subdivision near Pāhoa, Hawai’i). This area was evacuated and nobody was harmed. Several buildings were destroyed by fire. The seismicity also initially followed this eastward trend in motion. Initially, earthquakes were located to the west, but migrated to the east prior to the fissure eruptions. In addition, the lava lake formed in late April dropped in elevation prior to the fissure eruption (possibly due to the migration of magma from west to east). However, later seismicity migrated back to the west. This may be due to the changes in pressure associated with magma movement.

Temblor map showing earthquakes, faults, and shaded topography.

Hawai’ian Hotspot Volcanism

The Hawai’ian Islands are part of a chain of volcanoes and seamounts that are formed as the oceanic Pacific plate moves over a magmatic hotspot. This hotspot is a region where there exists a plume of upwelling magma that erupts through the Pacific plate to form volcanic eruptions. Over time, as the plate moves, the older volcanoes get further away from the hotspot. The most recent and currently volcanically active part of the Hawai’ian Islands is located on the Big Island of Hawai’i, where the Kïlauea volcano is located. Below is a visualization of how the magma chamber below Kïlauea may be oriented. Note how the magma plume rises to the Kïlauea Caldera, then spreads laterally to feed additional volcanic centers along the rift zones.

Cut away view looking beneath Kïlauea Volcano (USGS, 2010).

Hawai’ian Tectonics, Seismicity, and Eruptions

There are three main sources of earthquakes in Hawai’i: magmatic, volcanic edifice, and deep tectonic (IRIS). Magmatic earthquakes occur when magma rises or moves within the crust. As the magma rises beneath the volcanoes it can break up the crust. Changes in pressure and volume in the magma and volcano can increase the stress on faults in the region causing earthquakes.

There are faults within the volcanic edifice (the cone shaped structure that forms the shape of the volcano), as well as faults that exist beneath the volcano, between the volcano and the underlying Pacific plate. These faults can be sources of earthquakes independent of volcanism. Earthquakes in the volcanic edifice are extensional and caused by gravitational collapse of the volcanic rocks that form the edifice. These earthquakes tend to be small, with maximum magnitudes in the M 5 range. These extensional earthquakes may trigger earthquakes on the fault formed beneath the volcano. Earthquakes along this fault system can be much larger, including a M 7.9 Ka’u earthquake in 1868. A more recent example is the November 29, 1975 M 7.1 earthquake that happened near the current seismic and volcanic activity.

Earthquakes can occur within both the upper brittle mantle and oceanic crust as changes in pressure and temperature are exerted by the overlying volcano. The October 15, 2006 Kiholo Bay earthquake is an example of this type of earthquake. These are deeper than the other earthquakes, are further away from people and cause lesser shaking, for the same magnitude, than for shallower magmatic and volcanic edifice earthquakes.

The major fault systems on the southern part of the Big Island include rift zones and normal faults formed by extension either from gravitational collapse or extension related to the rift zones. The East Rift Zone and the Hilina fault appear to be the likely fault systems associated with this ongoing seismic activity. The 1975 earthquake may be a good analog to the current seismicity because it was also associated with magma injection.

Map showing the major volcanic centers, rift zones, and fault systems in Hawai’I (USGS, 2010).

The current sequence of earthquakes began near the Pu’u ‘Ō’ō-Kupaianaha Volcano, where there is a crater formed from prior eruptions. This crater was filled with lava and the lava level reached the rim of the crater and overflowed the crater on 4/30/2018.

Tsunami

The 1975 M 7.1 earthquake generated a tsunami observed by tide gages located in Maui, Kauai, Hawai’i, and Oahu. Wave heights were up to several feet in Hilo and several inches high in Oahu. This tsunami was too small to have an impact elsewhere. The M 6.9 earthquake also generated a tsunami, but it was smaller than the 1975 tsunami. The Hilo tide gage shows a wave height of less than a foot (amplitude = 0.399 meter).

Water surface elevation data from Hilo, Hawai’i from IOC.

What is Next?

Using the 1975 earthquake as an analogy, the M 6.9 earthquake is possibly the main shock in this sequence. However, our historic record is only about 200 years long and we may not have enough knowledge to fully understand the entire range of possible outcomes. In terms of volcanism, this part of Hawai’i has eruptions on an almost ongoing basis. Below is a figure that shows the volcanic activity since 1780. Note that the USGS considers that we are currently in a period of continuous activity.

Graph summarizing the eruptions of Mauna Loa and Kïlauea Volcanoes during the past 200 years (USGS, 2010).

Here is another great map showing the relative volcanic hazard for the areas around the Big Island of Hawai’i. Severity of volcanic hazard is represented by color. The gray areas show regions where lava flows have happened in the past ~200 years. Note that the rift zones of Kïlauea are considered a region of increased volcanic hazard. So, if one resides or visits to regions of increasing severity of hazard, be prepared to respond to volcanic and seismic activity. Be prepared and know your hazard!

Map of Island of Hawai‘i showing the volcanic hazards from lava flows (USGS, 2010).

References

IRIS, Hawai’ian Islands: Origins of Earthquakes https://www.iris.edu/hq/inclass/animation/Hawai’ian_islands_origin_of_earthquakes
USGS, 2010. Eruptions of Hawaiian Volcanoes—Past, Present, and Future, U.S. Geological Survey, General Information Product 117, 72 pp.
Ando, M., 1979. The Hawaii Earthquake of November 29, 1975: Low Dip Angle Faulting Due to Forceful Injection of Magma in JGR, v. 84, no. B13
IOC Sea Level Station Monitoring Facility http://www.ioc-sealevelmonitoring.org/index.php
USGS HVO, Hawaiian Volcano Observatory https://volcanoes.usgs.gov/volcanoes/kilauea/
Additional background material can be found here: http://earthjay.com/?p=7350

See the full article here .

Please help promote STEM in your local schools.

Stem Education Coalition

Earthquake Alert

Earthquake Alert

Earthquake Network project

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

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

Get the app in the Google Play store.

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

Meet The Quake-Catcher Network

Quake-Catcher Network

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

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

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

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

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

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

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

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

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

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

Below, the QCN Quake Catcher Network map

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

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

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

The primary project partners include:

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

The Earthquake Threat

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

Part of the Solution

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

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

System Goal

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

Current Status

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

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

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

Authorities

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

For More Information

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

Learn more about EEW Research

ShakeAlert Fact Sheet

ShakeAlert Implementation Plan

From Argonne National Laboratory ALCF: “ALCF supercomputers advance earthquake modeling efforts”

News from Argonne National Laboratory

ALCF

May 1, 2018
John Spizzirri

Southern California defines cool. The perfect climes of San Diego, the glitz of Hollywood, the magic of Disneyland. The geology is pretty spectacular, as well.

“Southern California is a prime natural laboratory to study active earthquake processes,” says Tom Jordan, a professor in the Department of Earth Sciences at the University of Southern California (USC). “The desert allows you to observe the fault system very nicely.”

The fault system to which he is referring is the San Andreas, among the more famous fault systems in the world. With roots deep in Mexico, it scars California from the Salton Sea in the south to Cape Mendocino in the north, where it then takes a westerly dive into the Pacific.

Situated as it is at the heart of the San Andreas Fault System, Southern California does make an ideal location to study earthquakes. That it is home to nearly 24-million people makes for a more urgent reason to study them.

San Andreas Fault System. Aerial photo of San Andreas Fault looking northwest onto the Carrizo Plain with Soda Lake visible at the upper left. John Wiley User:Jw4nvc – Santa Barbara, California

USGS diagram of San Andreas Fault. http://nationalatlas.gov/articles/geology/features/sanandreas.html

Jordan and a team from the Southern California Earthquake Center (SCEC) are using the supercomputing resources of the Argonne Leadership Computing Facility (ALCF), a U.S. Department of Energy Office of Science User Facility, to advance modeling for the study of earthquake risk and how to reduce it.

Headquartered at USC, the center is one of the largest collaborations in geoscience, engaging over 70 research institutions and 1,000 investigators from around the world.

The team relies on a century’s worth of data from instrumental records as well as regional and seismic national hazard models to develop new tools for understanding earthquake hazards. Working with the ALCF, they have used this information to improve their earthquake rupture simulator, RSQSim.

RSQ is a reference to rate- and state-dependent friction in earthquakes — a friction law that can be used to study the nucleation, or initiation, of earthquakes. RSQSim models both nucleation and rupture processes to understand how earthquakes transfer stress to other faults.

ALCF staff were instrumental in adapting the code to Mira, the facility’s 10-petaflops supercomputer, to allow for the larger simulations required to model earthquake behaviors in very complex fault systems, like San Andreas, and which led to the team’s biggest discovery.

Shake, rattle, and code

The SCEC, in partnership with the U.S. Geological Survey, had already developed the Uniform California Earthquake Rupture Forecast (UCERF), an empirically based model that integrates theory, geologic information, and geodetic data, like GPS displacements, to determine spatial relationships between faults and slippage rates of the tectonic plates that created those faults.

Though more traditional, the newest version, UCERF3, is considered the best representation of California earthquake ruptures, but the picture it portrays is still not as accurate as researchers would hope.

“We know a lot about how big earthquakes can be, how frequently they occur, and where they occur, but we cannot predict them precisely in time,” notes Jordan.

The team turned to Mira to run RSQSim to determine whether they could achieve more accurate results more quickly. A physics-based code, RSQSim produces long-term synthetic earthquake catalogs that comprise dates, times, locations, and magnitudes for predicted events.

Using simulation, researchers impose stresses upon some representation of a fault system, which changes the stress throughout much of the system and thus changes the way future earthquakes occur. Trying to model these powerful stress-mediated interactions is particularly difficult with complex systems and faults like San Andreas.

“We just let the system evolve and create earthquake catalogs for a hundred thousand or a million years. It’s like throwing a grain of sand in a set of cogs to see what happens,” explains Christine Goulet, a team member and executive science director for special projects with SCEC.

The end result is a more detailed picture of the possible hazard, which forecasts a sequence of earthquakes of various magnitudes expected to occur on the San Andreas Fault over a given time range.

The group tried to calibrate RSQSim’s numerous parameters to replicate UCERF3, but eventually decided to run the code with its default parameters. While the initial intent was to evaluate the magnitude of differences between the models, they discovered, instead, that both models agreed closely on their forecasts of future seismologic activity.

“So it was an a-ha moment. Eureka,” recalls Goulet. “The results were a surprise because the group had thought carefully about optimizing the parameters. The decision not to change them from their default values made for very nice results.”

The researchers noted that the mutual validation of the two approaches could prove extremely productive in further assessing seismic hazard estimates and their uncertainties.

Information derived from the simulations will help the team compute the strong ground motions generated by faulting that occurs at the surface — the characteristic shaking that is synonymous with earthquakes. To do this, the team couples the earthquake rupture forecasts, UCERF and RSQSim, with different models that represent the way waves propagate through the system. Called ground motion prediction equations, these are standard equations used by engineers to calculate the shaking levels from earthquakes of different sizes and locations.

One of those models is the dynamic rupture and wave propagation code Waveqlab3D (Finite Difference Quake and Wave Laboratory 3D), which is the focus of the SCEC team’s current ALCF allocation.

“These experiments show that the physics-based model RSQSim can replicate the seismic hazard estimates derived from the empirical model UCERF3, but with far fewer statistical assumptions,” notes Jordan. “The agreement gives us more confidence that the seismic hazard models for California are consistent with what we know about earthquake physics. We can now begin to use these physics to improve the hazard models.”

This project was awarded computing time and resources at the ALCF through DOE’s Innovative and Novel Computational Impact on Theory and Experiment (INCITE) program. The team’s research is also supported by the National Science Foundation, the U.S. Geological Survey, and the W.M. Keck Foundation.

ANL ALCF Cetus IBM supercomputer

ANL ALCF Theta Cray supercomputer

ANL ALCF Cray Aurora supercomputer

ANL ALCF MIRA IBM Blue Gene Q supercomputer at the Argonne Leadership Computing Facility

See the full article here .

Earthquake Alert

Earthquake Alert

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

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

Get the app in the Google Play store.

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

Meet The Quake-Catcher Network

Quake-Catcher Network

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

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

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

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

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

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

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

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

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

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

Below, the QCN Quake Catcher Network map

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

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

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

The primary project partners include:

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

The Earthquake Threat

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

Part of the Solution

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

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

System Goal

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

Current Status

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

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

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

Authorities

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

For More Information

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

Learn more about EEW Research

ShakeAlert Fact Sheet

ShakeAlert Implementation Plan

Please help promote STEM in your local schools.

Stem Education Coalition

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