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  • richardmitnick 1:37 pm on August 31, 2018 Permalink | Reply
    Tags: "Earthquake Precursors, AGU, and Predictions, , , , Processes, ,   

    From Eos: “Earthquake Precursors, Processes, and Predictions “ 

    From AGU
    Eos news bloc

    From Eos

    8.31.18
    Dimitar Ouzounov

    A new book presents various studies that may establish a link between earthquakes and different types of precursor signals from the Earth, atmosphere and space.

    1
    The village of Onna was severely damaged in the 2009 earthquake that struck the Abruzzo region of Italy. Our goal is to find robust earthquake precursors that may be able to predict some of the most damaging events, like Onna. The proposed earthquake precursor signals described in our book could contribute to reliable forecasting of future seismic events; however, additional study and testing is needed. Credit: Angelo_Giordano / 170 images (CC0)

    Scientists know much more about what happens after an earthquake (e.g. fault geometry, slip rates, ground deformation) than the various and complex phenomena accompanying the preparatory phases before a seismic event. Pre-Earthquake Processes: A Multi-disciplinary Approach to Earthquake Prediction Studies, a new book just published by the American Geophysical Union, explores different signals that have been recorded prior to some earthquakes and the extent to which they might be used for forecasting or prediction.

    The reporting of physical phenomena observed before large earthquakes has a long history, with fogs, clouds, and animal behavior recorded since the days of Aristotle in Ancient Greece, Pliny in Ancient Rome, and multiple scholars in ancient China [Martinelli, 2018]. Many more recent case studies have suggested geophysical and geochemical “anomalies” occurring before earthquakes [Tributsch, 1978; Cicerone et al., 2009 Nature].

    It should not be surprising that a large accumulation of stress in the Earth’s crust would produce precursory signals. Some of these precursors have been correlated with a range of anomalous phenomena recorded both in the ground and in the atmosphere. These have been measured by variations in radon, the electromagnetic field, thermal infrared radiation, outgoing longwave radiation, and the total electron content of the ionosphere.

    Earth observations from sensors both in space and on the ground present new possibilities for investigating the build-up of stress within the Earth’s crust prior to earthquakes and monitoring a broad range of abnormal phenomena that may be connected. This could enable us to improve our understanding of the lead up to earthquakes at global scales by observing possible lithosphere-atmosphere coupling.

    For example, the French Detection of Electro-Magnetic Emissions Transmitted from Earthquake Regions (DEMETER) satellite mission (2004-2010) was the first to systematically study electro-magnetic signals in relation to earthquakes and volcanoes. Earlier in 2018, the China Seismo-Electromagnetic Satellite (CSES-1) was launched, dedicated to monitoring electromagnetic fields and particles. There is also a global initiative to develop and coordinate test sites for observation and validation of pre-earthquake signals located in Japan, Taiwan, Italy, Greece, China, Russia, and the United States of America.

    We have carried out statistical checks of historic data to study the correlations between precursor signals and major earthquake events. For example, a decadal study of statistical data for Japan and Taiwan suggested a significant increase in the probability of electromagnetic, thermal infrared, outgoing longwave radiation, and total electron content measurements before large earthquakes [Hattori and Han, 2018; Liu et al., 2018]. A study of satellite data from DEMETER for more than 9000 earthquakes indicated a decrease of the intensity of electromagnetic radiation prior to earthquakes with a magnitude greater than five [Píša et al. 2013, Parrot and Li, 2018]. These results suggest that the earthquake detection based on measurements of these variables is better than a random guess and could potentially be of use in forecasting.

    Our book also presents testing of the CN earthquake prediction algorithm for seismicity in Italy [Peresan, 2018], the first attempt of combining probabilistic seismicity models with precursory information [Shebalin, 2018], and the testing of short-term alerts based on a multi-parameter approach for major seismic events in Japan, Chile, Nepal and Iran [Ouzounov et al., 2018]. Further testing is needed to better understand false alarm ratios and the overall physics of earthquake preparation.

    2
    Conceptual diagram of an integrated satellite and terrestrial framework for multiparameter observations of pre‐earthquake signals in Japan. The ground component includes seismic, electro-magnetic observations, radon, weather, VLF–VHF radio frequencies, and ocean‐bottom electro-magnetic sensors. Satellite component includes GPS/total electron content, synthetic-aperture radar, Swarm, microwave, and thermal infrared satellites. Credit: Katsumi Hattori, presented in Ouzounov et al, 2018, Chapter 20

    Based on our international collaborative work, we found that reliable detection of pre-earthquake signals associated with major seismicity (magnitude greater than 6) could be done only by integration of space- and ground-based observations. However, a major challenge for using precursor signals for earthquake prediction is gathering data from a regional or global network of monitoring stations to a central location and conducting an analysis to determine if, based on previous measurements, they indicate an impending earthquake.

    We also found that no single existing method for precursor monitoring can provide reliable short-term forecasting on a regional or global scale, probably because of the diversity of geologic regions where seismic activity takes place and the complexity of earthquake processes.

    The pre-earthquake phenomena that we observe are intrinsically dynamic but new Earth observations and analytical information systems could enhance our ability to observe and better understand these phenomena.

    See the full article here .

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    Please help promote STEM in your local schools.

    Stem Education Coalition

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

    Earthquake Alert

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    Earthquake Alert

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

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

    Get the app in the Google Play store.

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

    Meet The Quake-Catcher Network

    QCN bloc

    Quake-Catcher Network

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

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

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

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

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

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

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

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

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

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

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

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

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

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

    The primary project partners include:

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

    The Earthquake Threat

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

    Part of the Solution

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

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

    System Goal

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

    Current Status

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

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

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

    Authorities

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

    For More Information

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

    Learn more about EEW Research

    ShakeAlert Fact Sheet

    ShakeAlert Implementation Plan

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  • richardmitnick 2:22 pm on August 24, 2018 Permalink | Reply
    Tags: 3-D models of the North American continent on scales varying from urban to continental, AGU, , , , Geology in 3-D and the Evolving Future of Earth Science   

    From Eos: “Geology in 3-D and the Evolving Future of Earth Science” 

    From AGU
    Eos news bloc

    From Eos

    8.24.18
    O. S. Boyd
    L. H. Thorleifson

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    A new 3-D stratigraphic model of the subsurface of western Alberta in Canada. The uppermost surface represents the bedrock topography, and formations and groups of interest are shown in different colors. A speaker at a recent meeting on 3-D mapping discussed the modeling methods used to create this image. Credit: Alberta Geological Survey

    Last March, nearly 100 geoscientists from state, federal, academic, and private sector institutions in the United States and Canada gathered on the University of Minnesota campus. They presented current research on and discussed issues related to the latest developments in geologic mapping. They also discussed the synthesis of geological and geophysical information into 3-D models of the North American continent on scales varying from urban to continental.

    The geoscientists were concerned with mapping capabilities, from surficial materials to Precambrian basement, from young tectonic environments to well-established cratons, from water and mineral resources to natural hazards to basic science and education.

    In his opening plenary, Harvey Thorleifson of the University of Minnesota and the Minnesota Geological Survey briefly reviewed the history of 2-D geologic mapping from paper maps to Internet-accessible databases. He summarized scientific literature that highlighted enhanced data collection through digital capture of field data and the application of geoinformatics and 3-D methods to create maps. These advances have enabled the creation of models that contribute greatly to the science and planning of energy, minerals, water, hazards, and infrastructure design. These models are made possible by improved 3-D mapping that is well coordinated with spatial data infrastructure and well supported by global initiatives. Thorleifson suggested that geologic mapping is an essential service, part of a spectrum of activities that benefit society—from research and monitoring to modeling and resource management.

    Other presenters gave examples of the process to develop 3-D geological maps on various scales and the applications and benefits of this mapping:

    Kelsey MacCormack of the Alberta Geological Survey presented work on a 3-D geologic model of Alberta that is part of an effort to create a single source of geological information for the benefit of its diverse stakeholder groups (Figure 1).
    Don Sweetkind of the U.S. Geological Survey presented examples of regional groundwater systems, which require a regionally integrated 3-D geologic framework.
    Dick Berg of the Illinois State Geological Survey presented work on 3-D geologic mapping for urban areas, emphasizing the need to protect our local food and water supplies, as well as to help inform subsurface infrastructure.

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    Fig. 1. A spatial breakdown of 12 models that can be used to understand the structures that underly Alberta. The models, developed at a variety of scales, are helping researchers to understand geospatial relationships and interactions between the surface and subsurface. Credit: Alberta Geological Survey

    Attendees recognized the benefits of 3-D geologic mapping and the role that our interconnected electronic world can play to realize and maximize these benefits. They agreed that developing 3-D geologic products that are relevant, accessible, consistent, and readily updatable requires strong coordination among state, federal, academic, and industry partners, as well as a deep appreciation of the needs of potential users.

    Attendees were invigorated by the workshop and felt that the Geologic Mapping Forum should continue every 1–2 years and complement the annual Digital Mapping Techniques workshops held each year in late spring. A full workshop summary is available here.

    This meeting was hosted by the Minnesota Geological Survey.

    See the full article here .

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    Please help promote STEM in your local schools.

    Stem Education Coalition

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

     
  • richardmitnick 10:07 am on August 17, 2018 Permalink | Reply
    Tags: AGU, Bhutan Earthquake Opens Doors to Geophysical Studies, , , , ,   

    From Eos: “Bhutan Earthquake Opens Doors to Geophysical Studies” 

    From AGU
    Eos news bloc

    From Eos

    13 August 2018
    György Hetényi
    Rodolphe Cattin
    Dowchu Drukpa

    1
    Taktsang, also known as the Tiger’s Nest, is a famous cliffside monastery in western Bhutan. Recent geophysical surveys have uncovered evidence of past earthquakes in this region that were much stronger than more recent events. Credit: iStock.com/KiltedArab

    In 2015, a magnitude 7.8 earthquake shook the Gorkha District of Nepal, killing more than 9,000. The memory of this event is still vivid for the residents of this central Himalayan nation.

    But farther east in the mountains, in Bhutan, many residents doubt the likelihood of a similar event happening to them. Bhutan had experienced several other earthquakes with a magnitude of about 6 during the past century. However, there was no clear evidence that Bhutan had ever seen an earthquake similar to the M7.8 Nepal event.

    Findings from recent geophysical exploration suggest that this confidence may be overly optimistic. These results have shown that the eastern Himalayas region is extremely complex compared with the rest of the mountain belt.

    The kingdom of Bhutan sets great store in its traditions and its principle of Gross National Happiness. Although its rugged terrain and remote location have allowed this kingdom to preserve its unique culture, these factors have also limited the development of international collaborations there, notably in the Earth sciences. This situation changed in 2009 after a damaging M6.1 earthquake that claimed 11 lives persuaded Bhutan to open its doors to exploration of the region’s geophysics.

    Our team studied mountain-building processes in this region after the 2009 earthquake. After 7 years of multipronged field campaigns, we learned that Bhutan’s geodynamics are as unique as its culture. The region’s crustal structure, seismicity, and deformation pattern are all different from what scientists had speculated previously.

    During our campaigns, we found evidence that at least one M8 earthquake had, in fact, occurred in Bhutan. This means that other earthquakes of this magnitude could occur in the region again [Hetényi et al., 2016b; Berthet et al., 2014; Le Roux-Mallouf et al., 2016].

    A Different Plate?

    Although the western and central Himalayan arc curves gently from Pakistan to Sikkim and has a low-lying foreland, the eastern third curves more sharply and has significant topographical relief south of the mountain belt, namely, the Shillong Plateau and neighboring hills (Figure 1). Previous studies proposed that these structures accommodate part of the India-Eurasia tectonic plate convergence. These earlier studies also proposed that the great 1897 Assam earthquake (M8.1) had relieved some of the strain between these converging tectonic plates, thereby lowering earthquake hazard in Bhutan.

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    Fig. 1. Topographic map of the 2,500-kilometer-long Himalayan arc and surrounding region, with formerly (yellow) and newly (pink) cataloged seismicity. The dextral fault zone (white arrows) between Sikkim and the Shillong Plateau marks the break of the India plate, east of which a zone of complex 3-D deformation begins. Red dates mark the three largest earthquakes mentioned in the text. Green lines mark the surface trace of the megathrust along which the India plate underthrusts the Himalayan orogen, as well as the thrust faults bounding the Shillong Plateau. Political boundaries are shown for reference. Abbreviations: Pl. = plateau; Pr. = Pradesh; Sik. = Sikkim.

    We collected new gravity, geodetic, and seismology data, and we found that the lithosphere—the rigid top layer of Earth—beneath Bhutan and the Shillong Plateau is most likely not part of the Indian plate or, if it once was, that it is now detached from it. The demarcation between plates stretches in a NW–SE direction, without a surface trace, but it is evident in a middle to lower crustal zone of continuously active seismicity and dextral (right-lateral) motion [Diehl et al., 2017]. This fault zone most likely hosted an M7 earthquake in 1930.

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    Research team member Théo Berthet monitors data collection during a campaign to a less visited region in central Bhutan. The Black Mountains, which rise to 4,500–4,600 meters, are visible in the background. Credit: György Hetényi

    Our GPS measurements confirm the relative motion of the newly defined microplate. These measurements also show that this microplate is rotating clockwise with respect to the Indian plate [Vernant et al., 2014]. The different behaviors of the two lithospheres are clearly expressed in their differences in flexural stiffness along the strike direction of the orogen (mountain belt). The flexural stiffness beneath Nepal is homogeneous [Berthet et al., 2013] but is comparatively weaker beneath Bhutan [Hammer et al., 2013].

    A similar, but less well defined, deep seismicity zone, with distinct GPS vectors and flexural signatures, may mark another terrain boundary farther east along the Himalayas in Arunachal Pradesh [Hetényi et al., 2016a].

    Not a Safe Haven

    India’s 1897 Assam earthquake, which occurred farther south, is only a few human generations in the past and has not completely faded from memory. No event since then has reached magnitude 7 in Bhutan, and many of the local population believe that big earthquakes cannot happen there.

    However, the return period of large Himalayan events is longer than oral history: Western Nepal, for example, has not experienced a significant event since 1505. It is true that over the past decades, the seismicity rate in Bhutan has been low, but we have found evidence of several great earthquakes in the past on the local megathrust.

    Geomorphological analysis of uplifted river terraces in central Bhutan revealed two major events over the past millennium [Berthet et al., 2014]. A newly excavated paleoseismological trench has documented surface rupture during a medieval event and a 17th–18th century event [Le Roux-Mallouf et al., 2016]. Calculations based on newly translated historical eyewitness reports, macroseismic information, and reassessed damage reports have constrained a M8 ± 0.5 earthquake on 4 May 1714 [Hetényi et al., 2016b].

    Thus, the seismic gap proved to be an information gap: The entire length of the Himalayas can generate earthquakes with a magnitude greater than 7.5, and it has done so in the past 500 years.

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    The landscape in eastern Bhutan, south of Trashigang, typically features incised valleys, steep slopes, and terraces. The hut in the center is shown in the inset for scale. The view here is to the east, and the hut is located at 27.2784°N, 91.4478°E. Credit: György Hetényi

    Differences at Multiple Scales

    The major change along the Himalayas occurs between their central western part (with a single convergence zone) and the eastern third (with distributed deformation including strike-slip motion), and the east–west extent of Bhutan exhibits even greater complexity. The crust appears to be smoothly descending in western Bhutan and is subhorizontal in the eastern part of the country [Singer et al., 2017a]. Our measurements of seismic wave speeds in the upper crust show important changes across the country, and they coincide well with the geological structure mapped at the surface [Singer et al., 2017b].

    The most striking difference between western and eastern Bhutan is the crustal deformation pattern. In the west, the accommodation of present-day crustal shortening is very similar to the rest of the Himalayas: The plates in the megathrust region are fully locked [Vernant et al., 2014], and microseismicity (the occurrence of small events) is scattered across the crust [Diehl et al., 2017]. In the east, the locked segment of the megathrust is shorter, and it focuses most of the microseismic activity within a smaller region. Also, the fault appears to be creeping (sliding without producing significant seismicity) in both shallower and deeper segments [Marechal et al., 2016].

    This variation of loading and background seismicity warrants further research along the entire Himalayan orogen because there is very little existing insight into variations of structures and processes at such short distance scales.

    6
    Gangkhar Puensum, a mountain in north central Bhutan, is clearly visible from the main road between Ura and Sengor, looking north-northwest. Gangkhar Puensum, at an altitude of 7,570 meters, is the highest unclimbed peak on Earth. For religious reasons, mountaineering above 6,000 meters is prohibited in Bhutan, so this record is very likely to remain. Credit: György Hetényi

    Bhutan Is Moving Forward

    Bhutan is an exotic place that has self-imposed isolation for a long time, but the country’s technology is now catching up at a rate that is higher than for the rest of the Himalayan regions. During our 2010 campaign, we used paper traveler’s checks, and we lacked individual cell phones. During our 2017 campaign, we had access to automated teller machines (ATMs) and 3G internet.

    Likewise, our 7 years of field campaigns in this region have advanced our geophysical exploration and geodynamic understanding considerably. Still, there is a strong need to continue and build on the existing knowledge, which includes freely available seismological, gravity, and GPS data from our projects.

    Focusing on three areas would help improve future development in Bhutan:

    Broadening timescales. Acquiring long-term data needed to confirm or to adjust interpretations made on relatively short timescales is possible only with national observatories. We have launched seismology and GPS monitoring initiatives, and we hope for long-term funding and training of local manpower for all levels of operation.
    Broadening investigations. Some fields of study have advanced dramatically, including work on glacial lake outburst floods and on landslides. Others, like seismic microzonation, have been limited so far and could benefit from more extensive efforts. There is also a strong need for up-to-date building codes that reflect the scientific knowledge coming from these investigations.
    Increasing public awareness of natural hazards. The Bhutanese Ministry of Home and Cultural Affairs now has a full department devoted to disaster management that includes well-trained employees and comprehensive administration. However, education is the key to reaching the broadest population possible, which requires regular adaptation of school curricula and concise, practical information that local residents from any generation can understand.

    We hope that recent efforts by our teams have promoted progress in the right direction. We also hope that large portions of the population will be sufficiently aware to deal with the next natural disaster. As our research shows, the next event may come sooner than previously thought.

    6
    The main Himalayan peaks in northwest Bhutan, on the border with southern Tibet, are, from left to right, Chomolhari, Jichu Drake, and Tserim Kang. Exact altitudes are debated, but Chomolhari is higher than 7,000 meters, and Tserim Kang towers above 6,500 meters. Credit: György Hetényi

    Acknowledgments

    The authors gratefully acknowledge all scientific, fieldwork, and logistical help provided by participants of the projects GANSSER and BHUTANEPAL, carried out in collaboration with the Department of Geology and Mines and the National Land Commission, Thimphu, Bhutan, and with support of Helvetas. Research highlighted in this article became possible thanks to the seed funding of the North-South Centre (ETH Zurich), followed by funding from the Swiss National Science Foundation (grants 200021_143467 and PP00P2_157627) and the French Agence Nationale de la Recherche (grant 13-BS06-0006-01).

    References

    Berthet, T., et al. (2013), Lateral uniformity of India plate strength over central and eastern Nepal, Geophys. J. Int., 195, 1,481–1,493, https://doi.org/10.1093/gji/ggt357.

    Berthet, T., et al. (2014), Active tectonics of the eastern Himalaya: New constraints from the first tectonic geomorphology study in southern Bhutan, Geology, 42, 427–430, https://doi.org/10.1130/G35162.1.

    Diehl, T., et al. (2017), Seismotectonics of Bhutan: Evidence for segmentation of the eastern Himalayas and link to foreland deformation, Earth Planet. Sci. Lett., 471, 54–64, https://doi.org/10.1016/j.epsl.2017.04.038.

    Hammer, P., et al. (2013), Flexure of the India plate underneath the Bhutan Himalaya, Geophys. Res. Lett., 40, 4,225–4,230, https://doi.org/10.1002/grl.50793.

    Hetényi, G., et al. (2016a), Segmentation of the Himalayas as revealed by arc-parallel gravity anomalies, Sci. Rep., 6, 33866, https://doi.org/10.1038/srep33866.

    Hetényi, G., et al. (2016b), Joint approach combining damage and paleoseismology observations constrains the 1714 A.D. Bhutan earthquake at magnitude 8±0.5, Geophys. Res. Lett., 43, 10,695–10,702, https://doi.org/10.1002/2016GL071033.

    Le Roux-Mallouf, R., et al. (2016), First paleoseismic evidence for great surface-rupturing earthquakes in the Bhutan Himalayas, J. Geophys. Res. Solid Earth, 121, 7,271–7,283, https://doi.org/10.1002/2015JB012733.

    Marechal, A., et al. (2016), Evidence of interseismic coupling variations along the Bhutan Himalayan arc from new GPS data, Geophys. Res. Lett., 43, 12,399–12,406, https://doi.org/10.1002/2016GL071163.

    Singer, J., et al. (2017a), The underthrusting Indian crust and its role in collision dynamics of the eastern Himalaya in Bhutan: Insights from receiver function imaging, J. Geophys. Res. Solid Earth, 122, 1,152–1,178, https://doi.org/10.1002/2016JB013337.

    Singer, J., et al. (2017b), Along-strike variations in the Himalayan orogenic wedge structure in Bhutan from ambient seismic noise tomography, Geochem. Geophys. Geosyst., 18, 1,483–1,498, https://doi.org/10.1002/2016GC006742.

    Vernant, P., et al. (2014), Clockwise rotation of the Brahmaputra Valley relative to India: Tectonic convergence in the eastern Himalaya, Naga Hills, and Shillong Plateau, J. Geophys. Res. Solid Earth, 119, 6,558–6,571, https://doi.org/10.1002/2014JB011196.

    Author Information

    György Hetényi (email: gyorgy.hetenyi@unil.ch), Faculty of Geosciences and Environment, Institute of Earth Sciences, University of Lausanne, Switzerland; Rodolphe Cattin, Géosciences Montpellier, University of Montpellier, France; and Dowchu Drukpa, Department of Geology and Mines, Ministry of Economic Affairs, Thimphu, Bhutan

    See the full article here .

    Earthquake Alert

    1

    Earthquake Alert

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

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

    Get the app in the Google Play store.

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

    Meet The Quake-Catcher Network

    QCN bloc

    Quake-Catcher Network

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

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

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

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

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

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

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

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

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

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

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

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

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

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

    The primary project partners include:

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

    The Earthquake Threat

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

    Part of the Solution

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

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

    System Goal

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

    Current Status

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

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

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

    Authorities

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

    For More Information

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

    Learn more about EEW Research

    ShakeAlert Fact Sheet

    ShakeAlert Implementation Plan

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  • richardmitnick 11:33 am on August 3, 2018 Permalink | Reply
    Tags: AGU, , Two Active Volcanoes in Japan May Share a Magma Source,   

    From Eos: “Two Active Volcanoes in Japan May Share a Magma Source” 

    From AGU
    Eos news bloc

    From Eos

    31 July 2018
    Kimberly M. S. Cartier

    Evidence collected following the 2011 eruption of Japan’s Shinmoedake volcano suggests that the powerful event affected the behavior of an active caldera nearby.

    1
    Japan’s Shinmoedake volcano on the island of Kyushu, erupting on 27 January 2011. Credit: Kyodo via AP Images

    A single magma reservoir deep beneath Japan’s Kyushu Island may feed two of its most active volcanoes. GPS measurements of Aira caldera show that its once steady inflation stalled while the nearby Shinmoedake volcano erupted in early 2011 and then resumed when the eruption stopped. This suggests that the two volcanic areas draw from a common magma source deep under Kyushu and that the two areas may interact before, during, and after eruptions.

    “We observed a radical change in the behavior of Aira before and after the eruption of its neighbor,” Elodie Brothelande, lead scientist on the study and a postdoctoral researcher at the Rosenstiel School of Marine and Atmospheric Science at the University of Miami in Florida, said in a press release. “The only way to explain this interaction is the existence of a connection between the two plumbing systems of the volcanoes at depth,” she said.

    Observations of interconnected volcanic systems like this one are rare, so finding and studying them may help forecasters improve their eruption prediction and hazard models, Brothelande told Eos. Her team published its results in late June in the journal Scientific Reports.

    An Underground Connection

    Shinmoedake, which is part of the Kirishima volcanic group in southwestern Japan, began erupting in January 2011 and released more than 20 million tons of magma, ash, and pyroclastic rock. Watch a snippet of this eruption in the video below.

    2
    https://www.sciencedirect.com/science/article/pii/S037702731300111X

    To probe the possible connection between Shinmoedake and Aira, the researchers measured the vertical and horizontal displacements of the land in and around Aira caldera. They gathered daily GPS data from 32 stations in Kyushu spanning 2009–2013, 2 years before and after the Shinmoedake eruption. With these data, they calculated how Aira swelled and deflated in the time surrounding the eruption.

    The researchers compared the caldera’s behavior to models of how it would have reacted had it been responding only to geologic stress caused by Shinmoedake erupting. They found that Aira’s behavior was inconsistent with having geologic stress as the primary cause: Its pattern of inflation and deflation was wrong, and the amount it deflated didn’t match predictions.

    However, the models showed that an underground magma reservoir in the mantle feeding both volcanoes could explain the caldera’s behavior during the nearby eruption. Brothelande said that Aira and Shinmoedake are “good candidates” for this type of connection because they share the same active fault block and are relatively close to each other.

    3
    Lava forms ropey pāhoehoe textures. How molten must the subsurface rock that fueled this lava be to get classified as “magma”? Credit: iStock.com/Justin Reznick
    By Allen F. Glazner, John M. Bartley, and Drew S. Coleman 22 September 2016.

    4
    Satellite image of southern Kyushu on 3 February 2011 during an eruption of Shinmoedake. The two areas compared in this study, the Kirishima volcanic group and Aira caldera, are circled. The volcanoes at the foci of the research, Shinmoedake and Sakurajima, are marked by triangles. Credit: NASA

    5
    Basaltic lava erupting from an active parasitic cone (about 5 meters tall) on the side of Puʻu ʻŌʻō, Hawaii, 1997. The flowing material is unquestionably erupted magma, but whether its partially molten source region should be called magma is debatable. Credit: Allen Glazner

    Here’s how that scenario would have worked: In the period before Shinmoedake’s eruption, the magma reservoir inflated both volcanoes. The eruption then rapidly drew magma up from the reservoir and caused a sudden drop in pressure underground. The reservoir, in turn, drew magma from Aira in response to the pressure drop, causing the observed caldera deflation. Once Shinmoedake finished erupting, the magma reservoir resumed filling both volcanoes.

    A Promising Step

    “When a volcano enters a period of unrest or eruption, a common concern from communities and media is the chance of a neighboring volcano being ‘triggered,’” said Janine Krippner, a volcanologist and postdoctoral researcher at Concord University in Athens, W.Va., who was not involved with the project.

    “Research into the relationships between neighboring volcanic systems is important, but it is rare that evidence is found for systems affecting one another,” she said. “This study is a step in the direction of understanding any links between neighboring volcanic systems.”

    Although the research is very promising, more evidence is needed to solidify the ties between the two volcanoes, Krippner added. For example, repeat observations of the volcanoes during the time before and after an eruption, as well as geochemical analysis of the pair’s eruption products, could help. “I would expect to see similarities in geochemistry trends—the magma ‘genetics’—in eruption products like lavas, volcanic ash, and pyroclastic deposits if they have a common source,” she said.

    Past geochemical [Journal of Volcanology and Geothermal Research] studies have shown that eruption products from the two volcanic systems have similar isotope ratios for strontium and neodymium, the paper notes. However, Brothelande told Eos, a “real comparative study is still required” to geochemically link Shinmoedake and Aira to a common source.

    Shinmoedake and Aira’s associated volcanic peak, Sakurajima, erupted in 2017, and each has seen ongoing intermittent activity throughout 2018. The research team is planning to study the activity at Shinmoedake and Aira from the past 2 years to better understand their underground connection.

    Brothelande pointed out that there are other volcanic systems in which similar hidden connections may cause a volcano to interact with its neighbor, for example, in Hawaii, Alaska, and Italy. This occurs even in smaller systems of lava domes and maars like those in France and Colorado. Models that calculate eruption probabilities, she said, likely need to include these interactions.

    “External factors that have an impact on volcanic eruptions—triggering or delaying—have been neglected for a long time,” Brothelande said. But the findings at Shinmoedake and Aira open a new door, she added. “Nearby eruptions have to be included as well.”

    See the full article here .

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  • richardmitnick 8:28 am on July 27, 2018 Permalink | Reply
    Tags: AGU, , Drones Swoop in to Measure Gas Belched from Volcanoes, , ,   

    From Eos: “Drones Swoop in to Measure Gas Belched from Volcanoes” 

    From AGU
    Eos news bloc

    25 July 2018
    Fiona D’Arcy
    John Stix
    J. Maarten de Moor
    Julian Rüdiger
    Jorge Andres Diaz
    Alfred Alan
    Ernesto Corrales

    Volcanic gases are important eruption forecasting tools often used in volcano monitoring. However, collecting gas samples requires scientists to enter high-risk volcanic areas.
    This is where drones come in.

    Drones are the perfect tools for volcanologists to access these danger zones. Although they’re rapidly becoming popular among the scientific community for photography and aerial mapping, few studies have attempted to quantitatively measure gas emissions with drones [e.g., McGonigle et al., 2008; Mori et al., 2016].

    A drone, or unmanned aerial vehicle (UAV), is a remote-controlled device that allows a pilot to remain a safe distance from an active crater while the drone is maneuvered to the site of interest. Drones can be piloted manually or with an autonomous navigation system. Compact gas sensors can be mounted onto the drone that take measurements while the drone is in the air.

    Last year, a team of researchers gathered in Central America for a 2-week excursion to test a variety of instrument and drone combinations. Their numbers included gas geochemists, volcanologists, physicists, engineers, and chemists from four institutions across Canada, Germany, and Costa Rica. Most, of course, doubled as drone pilots.

    Why Measure These Gases?

    Scientists measure volcanic gases for three main reasons.

    First, changes in the ratios of certain gases can indicate an imminent eruption. The concentrations of carbon dioxide (CO2), sulfur dioxide (SO2), and hydrogen sulfide (H2S) can be measured by flying the drone right into the plume of gas as it emerges from the volcano.

    Second, researchers need to know which reactive species are coming out of the volcano so that the interactions between volcanoes, climate, and ozone can be better understood. These compounds contain such halogens as chlorine and bromine, and a drone hovering directly in the gas at varying distances from the source can help scientists determine how the compounds change as the plume ages.

    Third, the total amount of gas being emitted can be used to calculate the exchange of volatiles between the deep Earth and the atmosphere. The emission amount can also be used to monitor volcanic activity. This is done by flying transects under the entire width of the gas plume to measure the output, or flux, of SO2.

    Usually, a researcher drives or walks under the width of the plume to collect the needed transects, but limited road access and obstructions at ground level often prevent or curtail surveying such transects. The drone bypasses these problems, is faster, and can even directly measure wind speed at plume height, which is a key variable for the flux calculation.

    By combining gas concentration ratios and SO2 flux measurements, scientists can also calculate the CO2 flux.

    Gas Giants

    Turrialba and Masaya are Central America’s largest degassing volcanoes, with each having emitted well more than 4 million tons of SO2, among other gases, over the past 20 years alone (calculations are based on data from de Moor et al. [2016] and Martin et al. [2010]). Both of these gas giants lie dangerously close to major cities, making them key locations to test new measurement techniques.

    2
    The location of Masaya and Turrialba volcanoes. Credit: Fiona D’Arcy

    1
    Turrialba volcano. Rodtico21

    3
    Masaya volcano.Leon petrosyan

    Turrialba was sculpted by a series of violent eruptions during the past 10,000 years, but all activity came to a halt in 1866. Then, in 1996, the volcano sprang to life again.

    More than 20 years later, explosive bursts of ash frequently rise several hundred meters above the summit, causing havoc at the international airport in San José, Costa Rica’s capital. The opening of new vents and the escape of magmatic gas from intruding magma are the main drivers of the ongoing volcanic activity, and a small lava lake has been spotted forming at the bottom of the crater.

    Masaya is a different kind of volcano altogether. It is composed of a large caldera complex that formed 2,500 years ago, with volcanic cones rising from the floor of the caldera. One of the craters atop the largest cone hosts a vigorously bubbling lava lake that has attracted a multitude of tourists in recent years.

    Unlike Turrialba, Masaya has been persistently active throughout the past several hundred years, with a long-standing history of degassing from the surface of the lava lakes that have come and gone for centuries.

    The extraordinary degassing at these two volcanoes makes them ideal locations to test new drone-mounted instrumentation, thereby improving hazard assessments.

    Building Compact Instrumentation

    For measuring concentrations of CO2, SO2, and H2S, we designed two compact variations of multiple-gas analyzers (Multi-GAS) for drone flights. Multi-GAS instruments are typically the size of a toaster and require heavy batteries and a case and are meant for long-term measurements atop a volcano. We created miniaturized versions weighing under 1.5 kilograms, around the size of a football.

    We named the two instruments MiniGAS and MicroGAS. MicroGAS was designed by the volcanology group at McGill University, and MiniGAS was designed by GasLab of the Universidad de Costa Rica. Both have varying sensor ranges, but both consist of a pump, electrochemical sensors, and onboard data loggers to store or, in the case of MiniGAS, transmit the data by telemetry.

    We also deployed a lightweight gas diffusion sampling device to measure halogen species and their compositional variations. This device uses a pump and glass tubes with reactive coatings, called denuders, designed to collect the desired halogen compounds. An SO2 sensor and additional wiring that connects to the drone telemetry system allow the pilot to remotely start the sampling once high SO2 levels are reached, signaling that the drone is in the plume.

    In addition, we built a drone-mounted miniaturized differential optical absorption spectrometer (DROAS) to make SO2 flux measurements. Typical instruments are also toaster-sized and weigh roughly 2–4 kilograms, plus they require a large battery and a computer connection; the DROAS weighs roughly 950 grams and contains a telescope, an ultraviolet spectrometer, and a microcomputer running the data collection program.

    Choosing the Right Drone

    We used two octocopters and two quadcopters for this expedition, which was conducted in late April 2017. The drones were flown in combination with different types of compact sensors and spectrometers. What drones we chose depended on the goals of the particular flight in question.

    3
    The fleet of drones used in a campaign to test new drone-mounted instrumentation designed to measure gas emissions from volcanoes. Credit: Alfred Alan

    For example, if the goal was to perform a DROAS traverse, which requires covering a large distance (a kilometer or more) beyond the line of sight, then a sturdy octocopter with autonomous flying capability was ideal.

    If the goal was to fly straight up until the gas plume was reached and then hover there as long as the battery allowed, a manual flight by a lightweight quadcopter was best suited to the mission.

    The team discovered the suitability and limitations of each drone and created an effective protocol for assessing when and where it was useful or too dangerous to fly each type. A preflight checklist was used to ensure that wind, fog, and other hazards were taken into consideration and that any bystanders in the area were in a safe viewing location.

    Flying High

    We flew a dozen missions at Turrialba and Masaya from the crater rim, from the base, and downwind from the plume at each volcano. Each of the instruments was deployed, sometimes in tandem, on at least one drone.

    During these flights, we successfully entered the volcanic plume to measure SO2 and CO2 concentrations. We also conducted several flight transects to estimate SO2 flux values. Examples of these missions can be seen in Figure 1 and in the video below.

    3
    Fig. 1. Sample flight mission showing the carbon dioxide/sulfur dioxide (CO2/SO2) ratio measured in the plume of Masaya volcano. At t1, the drone takes off from the edge of the crater. At t2, the drone passes through the plume and turns around for the return journey through the plume again. At t3, the drone lands back at the start location.

    Soaring into the Future

    Researchers demonstrated an array of drone and sensor capabilities in volcanic gas plumes during 2 weeks of field testing in Costa Rica and Nicaragua. At the same time, we learned countless lessons about the adaptability and preparedness needed to undertake such a task. In addition to acquiring permits, customs letters, plane-approved batteries, and spare parts prior to travel, coordinating with local authorities proved vital to dealing with the surprises that abounded at every stage of the fieldwork.

    With proper safety measures and permissions in place, this kind of work could revolutionize volcanic gas measurements made at volcanoes without ever putting the researchers in danger. New ash deposits and crater lakes could be sampled during eruptive periods. Instrumentation could be deployed in craters by drones. The possibilities are endless.

    Acknowledgments

    We thank the Observatorio Vulcanológico y Sismológico de Costa Rica (OVSICORI) and the Instituto Nicaragüense de Estudios Territoriales (INETER) for their aid during the field campaign. We also thank José Pinell and the Instituto Nicaragüense de Aeronáutica Civil (INAC) for their assistance in Nicaragua and the Vicerrectoría de Investigación and Centro de Investigación en Ciencias Atómicas, Nucleares y Moleculares (CICANUM) from the Universidad de Costa Rica for their support on the CARTA-UAV research project.

    References

    de Moor, J. M., et al. (2016), Turmoil at Turrialba Volcano (Costa Rica): Degassing and eruptive processes inferred from high-frequency gas monitoring, J. Geophys. Res. Solid Earth, 121, 5,761–5,775, https://doi.org/10.1002/2016JB013150.

    Martin, R. S., et al. (2010), A total volatile inventory for Masaya Volcano, Nicaragua, J. Geophys. Res., 115, B09215, https://doi.org/10.1029/2010JB007480.

    McGonigle, A. J. S., et al. (2008), Unmanned aerial vehicle measurements of volcanic carbon dioxide fluxes, Geophys. Res. Lett., 35, L06303, https://doi.org/10.1029/2007GL032508.

    Mori, T., et al. (2016), Volcanic plume measurements taken using a UAV for the 2014 Mt. Ontake eruption, Earth Planets Space, 68(49), 18 pp., https://doi.org/10.1186/s40623-016-0418-0.

    Author Information

    Fiona D’Arcy (email: fiona.darcy@mail.mcgill.ca) and John Stix, Department of Earth and Planetary Sciences, McGill University, Montreal, QC, Canada; J. Maarten de Moor, Observatorio Vulcanológico y Sismológico de Costa Rica, Heredia; Julian Rüdiger, Institute of Inorganic and Analytical Chemistry, Johannes Gutenberg University Mainz, Mainz, Germany; and Jorge Andres Diaz, Alfred Alan, and Ernesto Corrales, GasLab, CICANUM, Physics School, Universidad de Costa Rica, San José

    See the full article here .

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  • richardmitnick 11:41 am on April 25, 2018 Permalink | Reply
    Tags: AGU, , , , , , ,   

    From Eos: “Capturing Structural Changes of Solar Blasts en Route to Earth” 

    AGU
    Eos news bloc

    Eos

    4.25.18
    Sarah Stanley

    Comparison of magnetic field structures for 20 coronal mass ejections at eruption versus Earth arrival highlights the importance of tracking structural evolution to refine space weather predictions.

    1
    Coronal mass ejections erupt when flux ropes—the blue loops seen here—lose stability, resulting in a blast of plasma away from the Sun. New research [AGU Space Weather] emphasizes the importance of changes in the magnetic field structure of flux ropes between eruption of plasma blasts and their arrival at Earth. Credit: NASA/Goddard Space Flight Center/SDO, CC BY 2.0

    NASA/SDO

    Huge clouds of plasma periodically erupt from the Sun in coronal mass ejections. The magnetic field structure of each blast can help determine whether it might endanger spacecraft, power grids, and other human infrastructure. New research by Palmerio et al. highlights the importance of detecting any changes in the magnetic field structure of a coronal mass ejection as it races toward Earth.

    Coronal mass ejections often erupt in the form of a flux rope—a twisted, helical magnetic field structure that extends outward from the Sun. A flux rope can come in a variety of types that depend on the direction of the magnetic field axis and whether its helical component curves to the left or right. While the direction of the helical curve remains unchanged, the axis can alter direction after eruption from the Sun.

    In the new study, the researchers analyzed observations of 20 different coronal mass ejections, comparing their flux rope structure at eruption to their structure once they reached satellites near Earth. They used a variety of satellite and ground-based observations to reconstruct the eruption structures, and they directly observed structures close to Earth as the plasma blasts washed over NASA’s Wind spacecraft.

    NASA Wind Spacecraft

    The analysis showed that between Sun eruption and Earth arrival, flux rope structure changed axis direction by more than 90° for 7 of the 20 coronal mass ejections. The rest of the blasts had an axis rotation of less than 90°, with five changing by less than 30° after eruption.

    These results highlight the importance of capturing posteruption changes in flux rope magnetic field structures of coronal mass ejections to refine space weather predictions. Such rotations can result from a variety of causes, including deformations in the Sun’s corona and interaction with other coronal mass ejections.

    However, capturing these changes remains a challenge. Reconstructions of flux rope structure from direct spacecraft observations may vary depending on which reconstruction technique is used. In addition, such observations depend on the spacecraft’s particular path through a coronal mass ejection, which might not give an accurate picture of the overall structure.

    And although posteruption structural changes are important, the researchers emphasize that the flux rope structure of a coronal mass ejection at eruption is still a good approximation for its structure upon Earth arrival and serves as a key input for space weather forecasting models.

    See the full article here .

    Please help promote STEM in your local schools.

    STEM Icon

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  • richardmitnick 9:48 am on April 6, 2018 Permalink | Reply
    Tags: AGU, , Welcoming Women into the Geosciences,   

    From Eos: Women in STEM – “Welcoming Women into the Geosciences” 

    AGU
    Eos news bloc

    Eos

    3 April 2018
    Emily V. Fischer
    evf@atmos.colostate.edu
    Amanda Adam,
    Rebecca Barnes
    Brittany Bloodhart
    Melissa Burt
    Sandra Clinton
    Elaine Godfrey
    Ilana Pollack
    Paul R. Hernandez

    Early results of a program to foster the careers of women entering the geosciences demonstrate the effectiveness of several specific factors.

    1
    Early-career scientists and their mentors share a lighthearted moment while learning firsthand about snow crystal formation and snowpack metamorphism at a snow science event in Laramie, Wyo. The event, organized by the University of Wyoming’s Multicultural Association of Student Scientists, included participants from PROGRESS, a program that supports undergraduate women as they begin careers in the geosciences. Credit: Ilana Pollack

    Women are underrepresented in the geosciences, in part because of systemic attitudes and behaviors [e.g., Rosen, 2017]. Why do we need to close this gap? Diverse teams produce better ideas—they set the bar for scholarly excellence [McLeod et al., 1996]. So what are the best ways to welcome the next generation of women into geoscience careers?

    Born from Collaboration

    The Earth Science Women’s Network (ESWN) set out to find and test some answers to this question. ESWN, an organization with more than 3,000 members around the world, focuses on the peer mentoring and professional development of early-career women at the graduate and postdoc levels. This organization grew out of an informal gathering of six early-career women at the 2002 Fall Meeting of the American Geophysical Union.

    In 2014, members of the ESWN Leadership Board sought out expertise in gender and quantitative educational psychology. We wanted to find out the effects of connecting undergraduate women to a same-gender mentoring network and challenging their perceptions of their ability to succeed in science. We designed an experiment to quantify and qualify such effects on first- and second-year undergraduate women.

    We implemented our experiment at nine universities in two U.S. regions (Colorado/Wyoming Front Range and North and South Carolina) between fall 2015 and fall 2016. We are now halfway through our National Science Foundation–funded project, and we see positive results [Hernandez et al., 2017]: Undergraduate women with large mentoring networks that include faculty mentors are more likely than those without such networks to identify as scientists and are more intent on pursuing the geosciences.

    Our experiment has developed into an effective and scalable program that benefits the undergraduate women it serves and thus may be part of the solution to the gender gap in the geosciences. Although we are still learning the full effect of our intentionally designed mentoring experiment, the early results are robust enough for us to share the general format of the resulting program in the hope that similar programs can be implemented at additional universities.

    A Recipe for PROGRESS

    This program, the Promoting Geoscience, Research, Education and Success (PROGRESS) framework, offers three resources to undergraduate participants: a professional development workshop, access to female mentors and role models, and online discussions and resources. Many of the PROGRESS volunteer mentors and role models are also members of ESWN.

    Here we explain the essential components of our professional development workshop because this module of PROGRESS is mature and ready to be propagated. The goals of this first intervention component are as follows:

    to introduce the women to geoscience careers
    to establish connections among students
    to help participants identify role models and the value of mentoring
    to discuss how to overcome expected hurdles

    The workshop module begins with an introduction to the geosciences that focuses on teamwork and societal context. Why? People value people-oriented work environments [Su and Rounds, 2015], and linking to societal context enhances learning.

    Two panel discussions follow this introduction. Each panel features women representing different ethnic, career, and other perspectives because when people see others like themselves succeeding, they feel like they belong [Rattan et al., 2012]. Panelists give “Ignite”-style presentations—5 minutes, 20 slides—followed by student questions. In the first panel, the women present their career and personal pathways. The second panel has a “day in the life” theme because exposure to women succeeding in counterstereotypic roles helps break down stereotypes [Zawadzki et al., 2013].

    Engaging the Participants

    Seeing specific factors that fuel curiosity, frustration, and thrill of discovery in the geosciences is important to students. To add more exposure to women doing science, we offer our workshop participants hands-on activities, including a weather balloon launch, a Doppler on Wheels demonstration, and a water quality experiment.

    The workshop introduces gender stereotypes and biases—discussing these issues is important for overcoming their effects. We introduce these topics via a board game [Shields et al., 2011] and using group exercises, including a modified version of the Implicit Association Test (IAT) that helps reveal unconscious attitudes toward gender. The students also identify other stereotypes (e.g., socioeconomic status and race), and we review the ubiquity of these issues.

    Throughout the session, the facilitator reiterates that ability can be improved with effort. This conception appears important for building academic tenacity [Dweck et al., 2014] and overcoming the effects of stereotype threat—the idea that people underperform when they feel at risk of conforming to negative stereotypes surrounding their social group [Good et al., 2003]. Discussions also offer the chance for students to validate sexism and racism they may have experienced [Moss-Racusin et al., 2012].

    A Network of Support

    PROGRESS students consider all the support they will need by completing a mentor map exercise, where they reflect on who advocates for them, who they turn to for scientific advice, who gives them safe spaces to discuss their frustrations, etc. [Glessmer et al., 2015]. Supportive connections help students attain academic goals [Skahill, 2002]. We also teach skills like constructing emails to help students connect themselves to faculty.

    Following the workshop, students can be paired with a mentor who also identifies as a woman in science, technology, engineering, and mathematics (STEM), or they can continue their interactions with each other via campus get-togethers. There is evidence that same-gender mentoring can be more effective than cross-gender mentoring for female undergraduates [Blake-Beard et al., 2011].

    As discussed in a recent National Academy of Sciences report, more research is needed on how to foster effective mentoring relationships. We are exploring multiple models, such as one-to-one versus group mentoring, and also different ways of pairing students with mentors on the basis of perceived similar interests [Gehlbach et al., 2016].

    We do not yet know which strategy is better, but our program is already serving women across multiple institutions in two U.S. regions, which speaks to its transferability. In addition to a website, we have a closed Facebook group where we share news, internships, and other professional development opportunities, and students can also seek advice on their challenge du jour [Ellison et al., 2007].

    PROGRESS to Date

    As a result of our study, we found that PROGRESS participants develop larger mentor networks than their peers and that having a faculty mentor is related to greater personal identity as a scientist and greater intent on pursuing the geosciences. This is a critical result because most students who change their major away from STEM do so early in their college education.

    Many of our PROGRESS participants, who began the program as freshmen and sophomores, are now thinking about graduation and planning for their next steps. As we continue to track the women in the PROGRESS program, we will continue to update the geoscience community on widely transferable aspects of our research. All of our PROGRESS materials are available online for anyone who wants to start a similar program.

    Acknowledgments

    Support was provided by the National Science Foundation (DUE-1431795, DUE-1431823, and DUE-1460229). We thank all our volunteer mentors.

    References

    Blake-Beard, S., et al. (2011), Matching by race and gender in mentoring relationships: Keeping our eyes on the prize, J. Soc. Issues, 67(3), 622–643, https://doi.org/10.1111/j.1540-4560.2011.01717.x.

    Dweck, C. S., G. M. Walton, and G. L. Cohen (2014), Academic tenacity: Mindsets and skills that promote long-term learning, Bill & Melinda Gates Found., Seattle, Wash., https://ed.stanford.edu/sites/default/files/manual/dweck-walton-cohen-2014.pdf.

    Ellison, N. B., C. Steinfield, and C. Lampe (2007), The benefits of Facebook “friends:” Social capital and college students’ use of online social network sites, J. Comput. Mediated Commun., 12(4), 1,143–1,168, https://doi.org/10.1111/j.1083-6101.2007.00367.x.

    Gehlbach, H., et al. (2016), Creating birds of similar feathers: Leveraging similarity to improve teacher–student relationships and academic achievement, J. Educ. Psychol., 108(3), 342–352, https://doi.org/10.1037/edu0000042.

    Glessmer, M. S., et al. (2015), Taking ownership of your own mentoring: Lessons learned from participating in the Earth Science Women’s Network, in The Mentoring Continuum: From Graduate School Through Tenure, edited by G. Wright, pp. 113–132, Syracuse Univ. Grad. Sch. Press, Syracuse, N.Y.

    Good, C., J. Aronson, and M. Inzlicht (2003), Improving adolescents’ standardized test performance: An intervention to reduce the effects of stereotype threat, J. Appl. Dev. Psychol., 24(6), 645–662, https://doi.org/10.1016/j.appdev.2003.09.002.

    Hernandez, P. R., et al. (2017), Promoting professional identity, motivation, and persistence: Benefits of an informal mentoring program for female undergraduate students, PLoS One, 12(11), e0187531, https://doi.org/10.1371/journal.pone.0187531.

    McLeod, P. L., S. A. Lobel, and T. H. Cox Jr. (1996), Ethnic diversity and creativity in small groups, Small Group Res., 27(2), 248–264, https://doi.org/10.1177/1046496496272003.

    Moss-Racusin, C. A., et al. (2012), Science faculty’s subtle gender biases favor male students, Proc. Natl. Acad. Sci. U. S. A., 109(41), 16,474–16,479, https://doi.org/10.1073/pnas.1211286109.

    Paunesku, D., et al. (2015), Mind-set interventions are a scalable treatment for academic underachievement, Psychol. Sci., 26, 784–793, https://doi.org/10.1177/0956797615571017.

    Rattan, A., C. Good, and C. S. Dweck (2012), Why do women opt out? Sense of belonging and women’s representation in mathematics, J. Pers. Soc. Psychol., 102(4), 700–717, https://doi.org/10.1037/a0026659.

    Rosen, J. (2017), Data illuminate a mountain of molehills facing women scientists, Eos, 98, https://doi.org/10.1029/2017EO066733.

    Shields, S. A., M. Zawadzki, and R. N. Johnson (2011), The impact of the Workshop Activity for Gender Equity Simulation in the Academy (WAGES-Academic) in demonstrating cumulative effects of gender bias, J. Diversity Higher Educ., 4(2), 120–129, https://doi.org/10.1037/a0022953.

    Skahill, M. P. (2002), The role of social support network in college persistence among freshman students, J. Coll. Stud. Retention, 4(1), 39–52, https://doi.org/10.2190/LB7C-9AYV-9R84-Q2Q5.

    Su, R., and J. Rounds (2015), All STEM fields are not created equal: People and things interests explain gender disparities across STEM fields, Front. Psychol., 6, 189, https://doi.org/10.3389/fpsyg.2015.00189.

    Zawadzki, M. J., et al. (2013), Reducing the endorsement of sexism using experiential learning, Psychol. Women Q., 38(1), 75–92, https://doi.org/10.1177/0361684313498573.

    Author Information

    Emily V. Fischer (evf@atmos.colostate.edu), Colorado State University, Fort Collins; Amanda Adams, University of North Carolina at Charlotte; Rebecca Barnes, Colorado College, Colorado Springs; Brittany Bloodhart and Melissa Burt, Colorado State University, Fort Collins; Sandra Clinton and Elaine Godfrey, University of North Carolina at Charlotte; Ilana Pollack, Colorado State University, Fort Collins; and Paul R. Hernandez, West Virginia University, Morgantown
    Citation: Fischer, E. V., A. Adams, R. Barnes, B. Bloodhart, M. Burt, S. Clinton, E. Godfrey, I. Pollack, and P. R. Hernandez (2018), Welcoming women into the geosciences, Eos, 99, https://doi.org/10.1029/2018EO095017. Published on 03 April 2018.

    See the full article here .

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  • richardmitnick 7:05 am on March 23, 2018 Permalink | Reply
    Tags: AGU, , , , , , Radon Tells Unexpected Tales of Mount Etna’s Unrest,   

    From Eos: “Radon Tells Unexpected Tales of Mount Etna’s Unrest” 

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    22 March 2018
    Susanna Falsaperla
    Marco Neri
    Giuseppe Di Grazia
    Horst Langer
    Salvatore Spampinato

    Readings from a sensor for the radioactive gas near summit craters of the Italian volcano reveal signatures of such processes as seismic rock fracturing and sloshing of groundwater and other fluids.

    1
    Mount Etna in Sicily, Italy, spews lava from a Strombolian and effusive eruption on 24 April 2012. The church Santa Maria della Provvidenza stands in the foreground in the town of Zafferana Etnea on the mountain’s eastern flank. New research from a team studying the volcano finds that variations in its radon emissions provide insights into volcanic and tectonic influences inside the mountain and, for some seismic activity, up to tens of kilometers away. Credit: Marco Neri.

    Some researchers view radon emissions as a precursor to earthquakes, especially those of high magnitude [e.g., Wang et al., 2014; Lombardi and Voltattorni, 2010], but the debate in the scientific community about the applicability of the gas to surveillance systems remains open. Yet radon “works” at Italy’s Mount Etna, one of the world’s most active volcanoes, although not specifically as a precursor to earthquakes. In a broader sense, this naturally radioactive gas from the decay of uranium in the soil, which has been analyzed at Etna in the past few years, acts as a tracer of eruptive activity and also, in some cases, of seismic-tectonic phenomena.

    To deepen the understanding of tectonic and eruptive phenomena at Etna, scientists analyzed radon escaping from the ground and compared those data with measurements gathered continuously by instrumental networks on the volcano (Figure 1). Here Etna is a boon to scientists—it’s traced by roads, making it easy to access for scientific observation.

    2
    Fig. 1. Panoramic view of the volcano as it appeared during 2008 and 2009. No image credit.

    Dense monitoring networks, managed by the Istituto Nazionale di Geofisica e Vulcanologia, Catania-Osservatorio Etneo (INGV-OE), have been continuously observing the volcano for more than 40 years. This continuous dense monitoring made the volcano the perfect open-air laboratory for deciphering how eruptive activity may influence radon emissions.

    Tower of the Philosopher

    3
    Volcanologist Marco Neri during the winter of 2008–2009 downloads data onto a laptop from the ERN1 radon sensor at the site (later buried in lava) known as the Tower of the Philosopher. Behind him, less than 1 kilometer away, ash billows from the summit craters of the volcano. Credit: Marco Neri.

    In a recently published study [Falsaperla et al., 2017], we analyzed a period of dynamic and variable volcanic activity of Etna between January 2008 and July 2009. In those 19 months, the volcano produced seismic swarms, surface ground fractures, a vigorous lava fountain, and an eruption lasting 419 days.

    In short, the volcano delivered enough diverse behaviors to test whether radon detected by a station located near the top of Etna, at an altitude of about 3,000 meters, showed any patterns that matched eruptive behavior recorded by the networks. The station is at a place formerly known as the Torre del Filosofo (Tower of the Philosopher), which in 2013 became buried below meters of lava flows that completely changed the location’s appearance.

    The network’s data are plentiful and are related to physical occurrences, such as the vibrations produced by magma movements in the feed conduits, or so-called volcanic tremor, as well as the tremor source’s localization within the volcano; isolated seismic events or swarms; and ground fractures accompanying the opening of eruptive fissures and associated explosive and effusive events. We conducted an analysis of this enormous amount of data through a statistical-mathematical approach that revealed possible correlations and, in many cases, obvious synchronicities with radon emissions.

    What Did We Discover?

    Our study revealed that essentially two processes influenced radon levels at the monitoring station. The first, easily imaginable given the location of the measuring probe less than a kilometer from the summit craters of Etna, is linked to the rise of magma in the volcano’s central conduit. Short, intense radon bursts, which researchers refer to as gas pulses, occur when a carrier gas that conveys the radon to the surface also bursts from the volcano (Figure 2). In the area in question, this carrier consists mainly of water vapor that feeds the local fumarolic activity.

    4
    Fig. 2. Volcanic processes may have influenced the flux of radon recorded by the ERN1 probe during Mount Etna’s 2008–2009 flank eruption. Variations in magmatic activity could have caused gas pulses near the feeding dike, as well as the rapid increase in radon values recorded by the ERN1 station probe. Conceptual model by the authors (2017).

    The second process is rock fracturing from an earthquake or seismic swarm. Radon rising from rock fractures is a well-known, recurrent phenomenon caused by greater permeability of the ground following earthquake-induced breakage of rock.

    Action at a Distance

    We have also discovered that the radon probe of the Torre del Filosofo was sensitive even to relatively small earthquakes taking place several kilometers away. We noted a clear synchronism between seismic swarms more than 10 kilometers away from the probe and significant variations of radon, impossible to explain by the diffusion of radon gas to rocks and toward the surface. We therefore had to find a different solution, which we identified as a sloshing phenomenon, like the lapping of waves.

    Slosh dynamics describes the movement of liquids within a container [Ibrahim, 2005]. Experimental observations prove that sloshing may occur inside the conduits of volcanoes, promoting magma oscillations [Namiki et al., 2016].

    Applied to Etna, sloshing may explain how rock shaking induced by a seismic swarm can cause oscillatory motion in the groundwater and in the magmatic fluids contained within the volcano (Figure 3). These oscillations can propagate quickly inside the mountain, reaching far greater distances than had been imagined in relatively short times. Sloshing may also be favored by flank instability affecting the eastern and southeastern sectors of the volcano, as it can produce tensile stresses both on the summit and on the rift zones, increasing the permeability of the rocks in those areas [Acocella et al., 2016].

    5
    Fig. 3. Along with volcanic triggers (Fig. 2), tectonic activity may have influenced the flux of radon recorded by the ERN1 probe during Mount Etna’s 2008–2009 flank eruption. Seismicity in the rift zone could have caused microfracturing of the rocks, changing their porosity and permeability. Resulting gas migration inside the highly fractured zone related to the rift may have led to fluctuations in radon emissions recorded by the ERN1 station. Conceptual model by the authors (2017).

    In some ways, these remote influences are an unforeseen discovery that implicitly reveals that the volcano is in a perpetually precarious balance and therefore easily disturbed. Reminiscent of a butterfly effect, even a small phenomenon occurring, for example, on the north side of Mount Etna can make its effects felt on the opposite side.

    Acknowledgments

    We are grateful to Stephen Conway for his help in the English editing of this article. This work was supported by the Mediterranean Supersite Volcanoes (MED-SUV) project, which has received funding from the European Union’s Seventh Framework Programme for research, technological development, and demonstration under grant agreement 308665.

    References

    Acocella, V., et al. (2016), Why does a mature volcano need new vents? The case of the new Southeast Crater at Etna, Front. Earth Sci., 4, 67, https://doi.org/10.3389/feart.2016.00067.

    Falsaperla, S., et al. (2017), What happens to in-soil radon activity during a long-lasting eruption? Insights from Etna by multidisciplinary data analysis, Geochem. Geophys. Geosyst., 18(6), 2,162–2,176, https://doi.org/10.1002/2017GC006825.

    Ibrahim, R. A. (2005), Liquid Sloshing Dynamics: Theory and Applications, 948 pp., Cambridge Univ. Press, Cambridge, U.K., https://doi.org/10.1017/CBO9780511536656.

    Lombardi, S., and N. Voltattorni (2010), Rn, He and CO2 soil gas geochemistry for the study of active and inactive faults, Appl. Geochem., 25, 1,206–1,220, https://doi.org/10.1016/j.apgeochem.2010.05.006.

    Namiki, A., et al. (2016), Sloshing of a bubbly magma reservoir as a mechanism of triggered eruptions, J. Volcanol. Geotherm. Res., 320, 156–171, https://doi.org/10.1016/j.jvolgeores.2016.03.010.

    Wang, X., et al. (2014), Correlations between radon in soil gas and the activity of seismogenic faults in the Tangshan area, north China, Radiat. Meas., 60, 8–14, https://doi.org/10.1016/j.radmeas.2013.11.001.
    Author Information

    Susanna Falsaperla (email: susanna.falsaperla@ingv.it), Marco Neri, Giuseppe Di Grazia, Horst Langer, and Salvatore Spampinato, Istituto Nazionale di Geofisica e Vulcanologia, Sezione di Catania, Italy

    See the full article here .

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  • richardmitnick 12:05 pm on March 22, 2018 Permalink | Reply
    Tags: AGU, An Improved Understanding of How Rift Margins Evolve, , ,   

    From Eos: “An Improved Understanding of How Rift Margins Evolve” 

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    3.22.18
    Terri Cook

    1
    An extensional detachment fault in western Norway. In a new study, researchers examine how crustal-scale extensional faults successively link and interact to produce the architecture of a rifted margin. Credit: Per Terje Osmundsen.

    Earth’s surface is continuously reconfigured by the assembly and breakup of supercontinents. As part of this cycle, landmasses split apart at continental rifts, linear zones where the lithosphere is stretched and lowered and new oceanic crust forms.

    Geologists have long understood that rifted margins are characterized by several types of normal faults that accommodate this extension, including steep faults with up to a few kilometers of vertical displacement and lower-angle faults that can accommodate tens of kilometers of horizontal motion. Although the growth of these steeper faults has been systematically studied in rift margins, the role that the lower-angle faults plays in these settings is not as well understood.

    To bridge this gap, Osmundsen and Péron-Pinvidic [Tectonics] studied the range of faults present along the mid-Norwegian margin, an important oil- and natural gas–producing area that experienced multiple episodes of rifting between the late Paleozoic and early Cenozoic. Using several sources of seismic reflection data collected in the Norwegian Sea between 1984 and 2008, the researchers identified five structural domains that formed via the linkage of large extensional faults.

    The faults combined into what the authors call “breakaway complexes,” which distinguish the margin’s proximal and necking domains, with thicker continental crust and higher-angle faults, from its distal and outermost portions, which are recognized by increasingly isolated slivers of crystalline continental crust and the presence of lower-angle faults. Seaward of the outermost breakaway complex, nearly flat detachment faults prevail. The 3-D architecture of the rifted margin develops mainly through the lateral and downdip interaction between these faults.

    By defining these structural domains in a novel way, this study places low-angle, high-displacement faults within a broader framework. This perspective will help researchers better understand the lateral variability of rift-forming processes and, ultimately, how these margins—and their economically important sedimentary deposits—evolve.

    See the full article here .

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  • richardmitnick 1:45 pm on March 20, 2018 Permalink | Reply
    Tags: AGU, , , , How Earthquakes Start and Stop, ,   

    From Eos: “How Earthquakes Start and Stop” 

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    14 March 2018
    David Marsan
    Greg Beroza
    Joan Gomberg

    Earthquakes: Nucleation, Triggering, Rupture, and Relationships to Aseismic Processes; Cargèse, Corsica, France, 2–6 October 2017.

    1
    This fault scarp in Italy’s Apennine Mountains, an example of surface-rupturing normal faulting, formed during the complex 2016 Amatrice-Norcia earthquake sequence. Attendees at a school in Cargèse, on the French island of Corsica, discussed current topics of interest in earthquake behavior and new developments in understanding complex earthquake sequences. Photo Credit: Maxime Godano.

    The second Cargèse school on earthquakes, held last October, covered important and persistently challenging topics in earthquake behavior, including what factors control earthquake nucleation, how static or dynamic stresses and fluid injection trigger earthquakes, and how recent progress in measuring aseismic deformation might inform our understanding.

    The 79 participants representing 21 nationalities, mostly Ph.D. students and postdocs, and the 20 lecturers addressed these questions from a range of disciplines and over a range of spatial and temporal scales.

    Throughout this school, a recurring topic of discussion was what new insights have been gained since the first school in 2014. Here are some of the new developments presented at the 2017 school.

    Presentations on new observations of the complexity of earthquake rupture—perhaps most notably in the 2016 Kaikoura, New Zealand, earthquake—emphasized the critical role that geometric complexity must play in earthquake physics. With some notable exceptions, earthquake scientists have confronted this complexity only intermittently in the past. However, recent developments in sensor technology, such as nodal-style seismic instruments, remote sensing using interferometric synthetic aperture radar (InSAR), and high-performance computing, increasingly allow scientists to discern complexity and explore its role in earthquake behavior.

    Another new development presented at the school arises from multiple studies of large subduction zone earthquakes. These studies point to a preparation phase that manifests as foreshocks and possibly slow slip before some large events, sometimes originating at relatively shallow depths where the fault friction is thought to be high. The question of whether this preparation phase is the manifestation of a cascading failure process or is driven by an underlying aseismic process of unknown origin remains at issue.

    Another important contributor to progress, discussed at the school, is the continuing development and application of new signal processing approaches to discern small earthquakes and weak deformation transients. This development is especially significant because the mechanical processes at work in weak deformation transients are poorly known. Laboratory exploration of established and proposed friction laws, of the slip rate–dependent and slip-dependent types, will be essential to elucidate those processes. Lab experiments and numerical simulations are making steady progress toward more realistic physical models that account for such factors as fluids, roughness, and damage zones. These models also provide new insight into earthquake processes.

    Induced seismicity, which was also discussed at the school, provides an opportunity to accelerate progress in understanding the role of fluids in faulting. It also fills the spatial gap between laboratory experiments and naturally occurring tectonic earthquakes. Greater access to data relevant to induced seismicity would help realize its potential for furthering earthquake science in general.

    At the end of the school, there were rumblings about the next one. What important current trends might we anticipate? Machine learning and data mining applied to earthquake science are emerging as an important area. Other examples include continued new insights from studies of induced seismicity and potentially even a controlled earthquake experiment. Finally, new observational capabilities—the ramping up of InSAR satellites, lidar surveys, dense seismometer arrays, and novel and highly ambitious deployments like S-net, which spans the seafloor from the Japanese coast to beyond the Japan Trench—are certain to provide new insights and will help ensure that future earthquakes teach us more than has been possible previously.

    More information about the school can be found on its website.

    David Marsan, ISTerre, Université Savoie Mont Blanc, Le Bourget du Lac, France; Greg Beroza (email: beroza@stanford.edu), Department of Geophysics, Stanford University, Calif.; and Joan Gomberg, U.S. Geological Survey, Seattle, Wash.

    See the full article here .

    Earthquake Alert

    1

    Earthquake Alert

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

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

    Get the app in the Google Play store.

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

    Meet The Quake-Catcher Network

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    Quake-Catcher Network

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

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

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

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

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

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

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

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

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

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

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

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

    1

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

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

    The primary project partners include:

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

    The Earthquake Threat

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

    Part of the Solution

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

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

    System Goal

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

    Current Status

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

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

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

    Authorities

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

    For More Information

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

    Learn more about EEW Research

    ShakeAlert Fact Sheet

    ShakeAlert Implementation Plan

    Please help promote STEM in your local schools.

    STEM Icon

    Stem Education Coalition

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

     
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