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  • richardmitnick 11:47 am on November 24, 2017 Permalink | Reply
    Tags: , , Eos, , Looking Inside an Active Italian Volcano,   

    From Eos: “Looking Inside an Active Italian Volcano” 

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    17 November 2017
    Emily Underwood

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    Fumarolic emissions at Italy’s Solfatara crater. Credit: Marceau Gresse

    Italy’s Solfatara crater lies in the Phlegraean Fields caldera, near Mount Vesuvius, the volcano that buried the city of Pompeii in 79 CE. The Phlegraean Fields caldera is located inside the metropolitan area of Naples, and it is one of the largest volcanic systems on Earth. This caldera is currently showing significant volcanic unrest, mainly located around the Solfatara volcano. The crater’s boiling, sulfurous mud pools and fumaroles indicate an intense volcanic activity, which many scientists view as a serious potential threat to the roughly 3 million inhabitants of this region.

    Scientists have long struggled to track Solfatara’s activity because the interactions between the gases in magma, water, and steam within volcanoes are still poorly understood. Now, however, a 3-D map of the complex water and gas-bearing tunnels and chambers within the caldera could aid that effort.

    Gresse et al [Journal of Geophysical Research]. used electrical resistivity tomography (ERT), a technique commonly used to study aquifers and other underground structures, to map the structure of Solfatara’s inner cracks and chambers. In ERT, researchers induce an electrical current between multiple electrodes placed on the ground and then collect profiles of the resistance it encounters as it passes through substances such as water, rock, mud, or gas. After doing this repeatedly, they can compile a 3-D picture of what lies below.

    This study reveals, for the first time, the structure of a gas-filled reservoir 50 meters below the surface of the Solfatara caldera. It shows that the reservoir is attached to a 10-meter-thick channel that turns into an opening known as the Bocca Grande fumarole, a vent through which foul-smelling volcanic gases escape to the surface. It also reveals the hidden condensate water channels beneath the surface, as well as the precise dimensions of features such as the cryptodome, a body of magma that can make the surface of a volcano bulge without erupting.

    Solfatara releases thousands of tons of hot carbon dioxide and water through vents such as the Bocca Grande fumarole every day. As pressure within the volcano builds over time, the ground above often rises and can cut off or change the shape of these internal release valves. Although the Phlegraean Fields caldera hasn’t erupted since 1538 CE, three ground uplift events have occurred since the 1950s, suggesting to some that the next eruption could be coming soon.

    See the full article here .

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  • richardmitnick 11:28 am on October 31, 2017 Permalink | Reply
    Tags: , , Asthenosphere, Eos, Lithosphere, , Volcanic activity causes the seafloor to spread along oceanic ridges forming new areas of crust and mantle   

    From Eos: “Seafloor Activity Sheds Light on Plate Tectonics” 

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    27 October 2017
    Sarah Witman

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    Seafloor topography under the Atlantic Ocean. Credit: ETOPO1/NOAA

    Much like the way humans constantly generate new skin cells, the bottom of the ocean regularly forms fresh layers of seafloor. Volcanic activity causes the seafloor to spread along oceanic ridges, forming new areas of crust and mantle. After being generated, this new oceanic lithosphere cools down and contracts by up to 3% of its own volume. This contraction can trigger oceanic earthquakes.

    The basic mechanics of tectonic plates—the massive, constantly shifting puzzle pieces that make up the Earth’s surface—are fairly well understood.

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

    However, scientists cannot accurately predict how much the oceanic lithosphere will contract horizontally during the process described above.

    Sasajima and Ito studied this thermal contraction [Tectonics]by examining stress released by oceanic earthquakes over the past 55 years in newly formed sections of oceanic lithosphere (approximately 5–15 million years old). They also simulated this activity using mathematical models.

    The team found a distinct difference in two components of the released stress: one parallel to the ridge and another perpendicular to the ridge (i.e., in the seafloor spreading direction). Namely, the ridge-parallel components experienced 6 times as much extensional stress release, whereas the spreading components endured 8 times as much compressional stress release.

    In their numerical simulation, the researchers found that young oceanic lithosphere hardly ever contracts in the ridge-parallel direction. At most, it would do so only a quarter of the times that it would contract in the spreading direction. They concluded that because the layer of mantle underneath the lithosphere (the asthenosphere) is weak (low viscosity) and also because oceanic ridges are relatively weak, the young oceanic lithosphere is able to contract more freely in the spreading direction.

    This study provides critical insight into the driving and resisting forces underlying plate tectonics, one of the greatest physical phenomena in our world. (Tectonics, https://doi.org/10.1002/2017TC004680, 2017)

    See the full article here .

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  • richardmitnick 12:03 pm on October 20, 2017 Permalink | Reply
    Tags: , , Eos, , How to Trigger a Massive Earthquake   

    From Eos: “How to Trigger a Massive Earthquake” 

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    19 October 2017
    Lucas Joel

    Humans may be to blame for California’s second-largest 20th century earthquake, and a team of seismologists has now proposed how that could have happened.

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    A school in Kern County in California destroyed by the 1952 earthquake. A new study suggests that this earthquake could have been set off by nearby oil drilling activities, and it explains how that might have happened. Credit: NOAA National Geophysical Data Center

    A Los Angeles Times article published on 11 June 1952 tells of a successful new oil well at Wheeler Ridge in Kern County in California. The well operated for 98 days, but then, on 21 July at 4:52 a.m. local time, a 7.5-magnitude earthquake let loose beneath the well along the White Wolf fault. It was the second-largest earthquake in California in the 20th century, and it killed 12 people. A team of seismologists, reporting new research, thinks the oil drilling triggered the event. The work is the first to give a detailed explanation for how industrial activity could cause such a big earthquake, the researchers said.

    Taking oil out of the ground likely destabilized the White Wolf fault, triggering the Kern County quake, explained Susan Hough, a seismologist at the U.S. Geological Survey in Pasadena, Calif., and lead author of a study published this month in the Journal of Seismology.

    The work follows a 2016 Bulletin of the Seismological Society of America study in which Hough and a colleague suggest that oil drilling played a role in other historic southern California earthquakes, like the deadly 1933 6.4-magnitude Long Beach earthquake that killed 120 people. That study, however, lacked an explanation for how drilling could trigger such large quakes when modern experience shows that induced quakes rarely exceed a magnitude of even 5. This time, Hough and her colleagues propose a mechanism.

    Putting the Pieces Together

    Hough told Eos how she stumbled across old California state reports that give detailed accounts of oil drilling activity in southern California. The reports revealed evidence for a spatial and temporal association between oil industry activity and earthquakes. “From the industry data for the [oil] production volumes and the location of the well and the location of the [White Wolf] fault, we can show that the stress change on the fault would’ve been potentially significant,” she said.

    The stress change Hough refers to happened as the well pumped oil out of the ground. This, Hough explained, likely triggered the quake by “unclamping” the underlying fault. In this case, picture the fault as a fracture along an inclined plane where crustal blocks on opposite sides stall as they try to move past one another. “The fault is locked because there’s friction on the fault, and part of the reason for that is there’s the weight of the overlying crust on the fault plane,” said Hough. “But if you take some of that weight off, it shifts; it’s going to reduce the confining pressure…depending on the faults that are there, that could just destabilize what had been a locked fault.”

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    Oil wells line the Huntington Beach shoreline in southern California in 1926. In 1933, the 6.3-magnitude Long Beach earthquake struck, and according to seismologists, the temblor was likely due to oil drilling in the Huntington Beach region. Credit: Photo courtesy of Orange County Archives

    Liquids like oil, however, typically lubricate faults, making them more prone to slipping. So how could removing oil help trigger an earthquake? The answer lies in the structure of the rock layers beneath the well, which, Hough explained, prevented the oil’s lubricating effects from reaching the White Wolf fault. This means it was only a matter of removing the oily overburden that led to the fault destabilization.

    According to the team’s calculations, the amount of oil removed from above the fault generated a stress change of about 1 bar of pressure, a value that seismologists generally think of as the amount of stress change required to set an earthquake in motion, Hough explained. “After 80 days of drilling, the stress change was right at and exceeding that magic number that we think is significant,” she said.

    “They’ve developed a very plausible geologic scenario for how the Kern County earthquake could’ve been induced,” said Gillian Foulger, a geophysicist at Durham University in the United Kingdom, who was not involved in the work. “They’re really putting flesh on the bones for this particular earthquake.”

    Foulger also agrees that a modest change in the overlying weight could have been enough to set off the quake. “Earthquakes are a little bit like snow avalanches,” she said. “You can have a massive amount of snow pile up on a mountainside, and then you have a skier who skis across it and that’s just enough to trigger the disturbance that causes the whole lot to fall off.”

    Unlikely Recurrence

    Hough presents a model for initiating a large earthquake based on just one case example, although she thinks her work can apply to induced earthquakes in general: “It highlights the possibility that inducing any initial [earthquake] nucleation in proximity to a major fault could be the spark that detonates a larger rupture,” she said.

    “Nucleation” refers to the small change in stress needed to destabilize a fault—a stress change that could happen in oil-producing regions today. But the chances of producing another temblor in the manner of the Kern County earthquake are slim, according to Hough, mostly because oil fields tend not to sit above major fault lines. In addition, oil producers long ago changed to a standard practice of injecting water into the ground after oil removal, something that was not done at the Wheeler Ridge oil field and that could have restored much of the otherwise lost weight locking the fault.

    Most induced earthquakes are small—usually no bigger than a 4 magnitude—although there is no reason to suspect that humans cannot induce a big quake, explained Hough. The reason most induced quakes tend to be relatively small, she added, is that most earthquakes, in general, tend to be small. “One school of thought argues that the size distribution is the same for induced and natural earthquakes,” she said. But whether there is a maximum size limit for induced earthquakes, seismologists still do not know, she added.

    An important aspect of the new work, Foulger said, is that Hough presents a model that other scientists can test, which is a first for a large induced event like the Kern County earthquake. For Seth Stein, a geophysicist at Northwestern University in Evanston, Ill., who also had no part in the study, “the take-home is that for one of the largest earthquakes that we know of in the last hundred years, a reasonable case can be made that it was induced.”

    See the full article here .

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  • richardmitnick 1:06 pm on October 16, 2017 Permalink | Reply
    Tags: , , Eos, , Volcanic Unrest at Mauna Loa Earth’s Largest Active Volcano,   

    From Eos: “Volcanic Unrest at Mauna Loa, Earth’s Largest Active Volcano” 

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    Weston Albert Thelen
    Asta Miklius
    Christina Neal

    Mauna Loa is stirring—is a major eruption imminent? Comparisons with previous eruptions paint a complicated picture.

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    Oblique aerial view looking north-northeast toward the summit area of Mauna Loa volcano (elevation 4,169 meters) on 15 January 1976. The summit caldera (Moku’āweoweo) is 6 kilometers long and 2.5 kilometers wide. The pit crater in the foreground marks the start of the Southwest Rift Zone. Mauna Kea volcano is on the skyline in the distance. Credit: D. Peterson, USGS

    Mauna Loa is showing persistent signs of volcanic unrest. Since 2014, increased seismicity and deformation indicate that Mauna Loa, the volcano that dominates more than half of the island of Hawaiʻi, may be building toward its first eruption since 1984.

    Thousands of residents and key infrastructure are potentially at risk from lava flows, so a critical question is whether the volcano will follow patterns of previous eruptions or return to its now historically unprecedented 33-year slumber.

    Mauna Loa has erupted 33 times since 1843, an average of one eruption every 5 years [Trusdell, 2012]. Typical of shield-building Hawaiian volcanoes, Mauna Loa hosts a summit caldera and two rift zones, the Northeast Rift Zone (NERZ) and the Southwest Rift Zone (SWRZ; Figure 1, inset).

    Since the two most recent eruptions, in 1975 and 1984, monitoring by the U.S. Geological Survey’s Hawaiian Volcano Observatory has changed dramatically. Ground-based instruments continuously record signals from global navigation satellite systems (GNSS, of which GPS is one example), measuring the changing shape of the ground surface in near-real time, and interferometric synthetic aperture radar (InSAR) provides extensive spatial coverage of deformation. Seismic monitoring has also improved with the addition of more stations, increased data fidelity, and improved data analysis.

    More people live on the slopes of Mauna Loa now than in the 1970s and 1980s, so improvements in monitoring technology are of more than just academic interest.

    How does this recent period of unrest compare with the periods just before previous eruptions? How reliable are these comparisons in predicting the next eruption?

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    Fig. 1. The Italian satellite system COSMO-SkyMed acquired radar images of Mauna Loa on 1 January 2013 and 30 April 2017 to produce this ascending mode interferogram. Each fringe represents 1.5 centimeters of motion in the line-of-sight direction to the satellite. The butterfly pattern of fringes suggests an inflating tabular body beneath the caldera and uppermost Southwest Rift Zone (see inset map). The sizes of the white dots represent the magnitudes of earthquakes that occurred during this period. The arrow at the bottom left shows the direction of the satellite’s motion. The satellite’s interferometric synthetic aperture radar (InSAR) antenna looks to the right of the satellite track, and the radar contacts the land surface at about 35° off vertical. The inset is a digital elevation map of Mauna Loa showing lava flows since 1843 in red. The box shows the approximate extent of the interferogram image. COSMO-SkyMed data were provided by the Agenzia Spaziale Italiana via the Hawaiʻi Supersite.

    The Current Unrest

    Several periods of unrest have occurred at Mauna Loa since the 1984 eruption. The shallow magma storage complex started refilling (inflating) immediately following the eruption, but inflation soon slowed, and stopped altogether in the mid-1990s (Figure 2). A short-lived inflation episode began in 2002 [Miklius and Cervelli, 2003], and another began in 2004. By 2009, inflation had largely ceased. Unlike the current unrest, these previous two inflation episodes were not associated with significant numbers of shallow earthquakes; rather, they started with brief periods of deep seismicity approximately 45 kilometers beneath the surface [Okubo and Wolfe, 2008].

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    Fig. 2. Changes in distance across Moku’āweoweo, Mauna Loa’s summit caldera, and earthquakes shallower than 15 kilometers from 1973 through April 2017 in the same area as Figure 1. Because today’s sensitive instruments can detect earthquakes that previous instruments would have missed, only earthquakes greater than M1.7 are plotted. Large, abrupt extensions are associated with the formation of volcanic dikes during the 1975 and 1984 eruptions; other extensions are mostly due to accumulation of magma in shallow reservoirs. Note that this distance change is not sensitive to extension across the upper SWRZ, where most of the magma accumulation occurred between October 2015 and mid-2016. (EDM is electronic distance measuring, and MOKP and MLSP are GPS instrument sites.)

    The current unrest started in earnest in 2014 (Figure 2). Seismicity rates began to rise above background levels as early as March 2013, and by summer 2014, both seismicity and deformation rates had increased significantly. The pattern of ground deformation indicated inflation of a magma storage complex beneath the caldera and uppermost SWRZ, areas that were also the most seismically active (Figure 3).

    Beneath the caldera, seismicity consists of mostly small earthquakes (magnitude M of less than 2.5) at depths of 2–3 kilometers. These earthquakes occur in swarms lasting days to weeks, separated by months of minor activity. Event rates have been as high as 15 earthquakes per hour, with most earthquakes too small to be formally located.

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    Fig. 3. Blue arrows (with gray 95% confidence error ellipses) show the average horizontal velocities of GNSS stations on Mauna Loa from mid-2014 through 2016. Red arrows represent velocities predicted by a model of a horizontally opening tabular body extending from about 3 to 6 kilometers beneath the summit and upper Southwest Rift Zone and a radially expanding body at about 3 kilometers beneath the southeastern wall of the caldera. The surface projections of these magma reservoirs are indicated by the black line and black circle. The average rate of magma accumulation in these shallow reservoirs is on the order of 13 million cubic meters per year.

    The uppermost SWRZ has been the most seismically active region during the current unrest, in terms of overall energy release and number of earthquakes. These earthquakes are typically 3–4 kilometers below the surface. Another area of seismicity has been high on the west flank of the volcano, where swarms of small earthquakes (mostly less than M2.5) at an average depth of about 7 kilometers typically last days to a week.

    In addition to shallow seismicity, there have been several deep (greater than 20 kilometers), long-period earthquakes loosely scattered beneath the summit area. During previous periods of inflation, earthquakes with similar characteristics have been associated with magma ascent [Okubo and Wolfe, 2008].

    Short-term rates of seismicity and deformation have varied in magnitude, with weeklong to monthlong periods of relative quiescence interspersed within longer-term trends of heightened activity. Although there is general long-term correlation between deformation and seismicity rates, there is no obvious relationship between them in the short term.

    The spatial pattern of deformation and seismicity has also varied. In fall 2015, after several months of decreased inflation at the summit, seismicity beneath the caldera largely ceased, and inflation in the upper SWRZ increased (Figure 4). In May 2016, inflation and seismicity beneath the caldera slowly resumed, but as of mid-2017, rates are low compared with those seen prior to fall 2015.

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    Fig. 4. COSMO-SkyMed ascending mode interferograms show the shift in locus of inflation toward the upper Southwest Rift Zone in October 2015. Each image covers about the same length of time: (left) 18 March 2015 to 9 August 2015 and (right) 24 July 2015 to 31 December 2015. Each full-color cycle represents 1.5 centimeters of motion in the line-of-sight direction toward the satellite. Arrow shows direction of motion of the satellite. The SAR antenna looks to the right of the satellite track; the incidence angle is about 35° off vertical. COSMO-SkyMed data were provided by the Agenzia Spaziale Italiana via the Hawaii Supersite.

    Comparison with Past Eruptions

    Deformation monitoring networks in place before the 1975 and 1984 eruptions were sufficient to provide long-term indications of inflation that along with increased seismicity, led to a general forecast for the 1984 eruption [Decker et al., 1983]. However, measurements were not frequent enough to evaluate whether there were precursory changes in extension or uplift in the summit area just prior to eruption.

    Direct comparison of magma storage geometries and volumes derived from deformation patterns is also not possible because of the limited spatial and temporal extent of the early geodetic monitoring networks. Pre-1984 measurements are consistent with, but cannot confirm, the existence of a large-volume tabular storage complex (a vertical, dikelike body) beneath the summit and upper SWRZ, similar to what we currently model from GNSS and InSAR data.

    Similarly, differences in seismic network sensitivity and data processing preclude direct comparison of current seismicity rates with pre-1975 and pre-1984 rates. Patterns in the locations of earthquakes stronger than about M1.7, however, are comparable, and these patterns show a clear coincidence between the locations of seismicity during the current unrest and previous preeruption patterns (Figure 5).

    Another approach to comparing precursory seismicity is to evaluate cumulative seismic energy release, which mainly reflects energy released by larger-magnitude earthquakes (energy release increases logarithmically with respect to earthquake magnitude). Between 1 May 2013 and 30 April 2017, energy release on the west flank was equivalent to an M4.1 earthquake. For the same region, energy releases during the 4 years prior to the 1975 and 1984 eruptions were M4.2 and M4.5, respectively. In the caldera and uppermost SWRZ, the current energy release sums to M4.4, compared with M4.9 and M4.4 for the 1975 and 1984 precursory periods.

    Thus, the energy released during the current 4 or so years of unrest is approaching that released during the 4 years prior to the 1975 and 1984 eruptions. In some volcanic systems, the amount of energy release compared with previous eruptions may be an indicator of whether a period of unrest results in an eruption [Thelen et al., 2010], but this relationship has not been established on shield volcanoes such as Mauna Loa.

    One to 2 years prior to the 1975 and 1984 eruptions, swarms of small earthquakes increased in intensity. The strongest swarms included hundreds of small earthquakes per day for weeks. Bursts, as they were called, were separated by 3–6 months of relative quiet [Koyanagi et al., 1975]. Recently, swarms on the west flank have increased in number and size, but the durations of the swarms are less than pre-1975 and 1984 levels. Similarly, swarms of tiny earthquakes beneath the caldera have not occurred at rates seen in the months prior to the 1975 and 1984 eruptions.

    Interestingly, during the days to weeks prior to the past two eruptions, the number of small earthquakes fluctuated instead of building up steadily, even reaching relatively low rates for short periods prior to eruption [Koyanagi, 1987; Lockwood et al., 1987]. However, both eruptions had distinct short-term seismic precursors. The 1975 eruption was preceded by less than an hour of strong tremor in the summit caldera area [Lockwood et al., 1987]. In 1984, small (less than M0.1) earthquakes increased in frequency, shaking the ground two or three times per minute about 2.5 hours before the eruption [Koyanagi, 1987]. Harmonic tremor began about 2 hours prior to eruption, with a large increase in tremor amplitude and a swarm of earthquakes 30 minutes prior to eruption. Seven earthquakes larger than M3 occurred during a period from 30 minutes before the 1984 eruption until just over 1 hour after the onset of the eruption.

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    Fig. 5. Earthquake epicenters for (a) the 4 years prior to the 1975 eruption, (b) the 4 years prior to the 1984 eruption, and (c) the latest 4 years of unrest (1 May 2013 to 30 April 2017). Earthquake symbol size is based on magnitude, and color is based on depth. Only earthquakes above M1.7 are included, in an attempt to compensate for differences in network sensitivity since 1975. All earthquakes are analyst reviewed. Because the analysis of earthquakes above M1.7 is only partially complete for the current episode of unrest, event rates since 2013 may actually be slightly higher than shown here.

    Is an Eruption in Our Near Future?

    Mauna Loa’s long history of observed activity aids in forecasting another eruption, but at present, any forecast still contains a high degree of uncertainty. Some aspects of the current unrest are similar to unrest prior to eruptions in 1975 and 1984. Earthquake locations, temporal behavior, and energy release suggest that the volcano may be following a similar pattern. Other aspects, however, differ from the periods prior to the 1975 and 1984 eruptions.

    During the current unrest period, we have not observed the kind of moderate to large flank earthquakes that preceded many historical eruptions [Walter and Amelung, 2006], including the 1975 and 1984 eruptions. Also, as of fall 2017, we have not seen the high rates of small earthquakes observed about 7–14 months prior to the 1975 and 1984 eruptions, even though our ability to detect them has improved. Thus, if current unrest follows previous patterns of seismicity, we may expect that the volcano is still many months from eruption.

    We must also consider that current unrest might not follow previous patterns, and an eruption could occur without months of elevated microseismicity. It is possible that after years of intermittent inflation, shallow magma storage is exerting pressures already near the breaking point of the overlying rock.

    We can’t say for certain whether there will be a precursory months-long increase in microseismicity before the next Mauna Loa eruption. However, an eruption will likely be immediately preceded by an hours-long, dramatic increase in small earthquakes (at least one earthquake per minute), strong tremor, and the occurrence of several M3 or stronger earthquakes, similar to the lead-up to the 1975 and 1984 eruptions. Real-time deformation data from tiltmeters and GNSS stations will show large anomalies as magma moves from storage reservoirs toward the surface to the eventual eruption site in the summit area and/or along one of the rift zones or (less likely) from radial vents on the west flank.

    It is also possible that current elevated rates of seismicity and deformation may not culminate in eruption anytime soon; rather, this could be yet another episode of unrest that gradually diminishes. During the 25-year repose between the 1950 and 1975 eruptions, seismic unrest in 1962, 1967, and 1970 did not lead to eruption, although in hindsight, each is considered a long-term precursor to the 1975 eruption [Koyanagi et al., 1975].

    The high rate of volcanic activity at neighboring Kīlauea volcano complicates assessing the likelihood of a Mauna Loa eruption in the coming months or years. Klein [1982] noted that longer repose intervals at Mauna Loa were statistically correlated with eruptive activity at Kīlauea. Indeed, the current long repose time at Mauna Loa is occurring at the same time as the long-lived Puʻu ʻŌʻō eruption at Kīlauea, which began in 1983 and continues today. Even so, the most recent eruption of Mauna Loa in 1984 occurred during this eruption at Kīlauea, so the impact of nearby volcanic activity on Mauna Loa’s behavior over short timescales is unknown.

    We can make one forecast with relative certainty: On the basis of nearly 200 years of documented activity, it is highly likely that the next eruption will begin in the summit region and then, within days to years, migrate into one of the two primary rift zones [Lockwood et al., 1987].

    It is important to note that seismicity and inflation beneath the uppermost SWRZ do not imply an increased likelihood of eruption along the SWRZ. Similar patterns of seismicity prior to the 1975 and 1984 eruptions did not result in sustained activity in the SWRZ. In 1984, the eruption began at the summit and migrated to the upper SWRZ before activity focused along the NERZ, suggesting that a magma body extending into the uppermost SWRZ—similar to that inferred from current data—was also active prior to that eruption.

    Communicating the Hazards

    In response to more than a year of persistently elevated rates of seismicity and deformation, the Hawaiian Volcano Observatory (HVO) elevated the Volcano Alert Level and Aviation Color Code for Mauna Loa to advisory/yellow on 17 September 2015, indicating that the volcano was restless and that monitoring parameters were above the long-term background levels.

    Since then, HVO has continued public education efforts and engaged agency partners, including Hawaiʻi County Civil Defense and the National Park Service, to discuss preparedness and response planning. In 2016, HVO installed new web cameras and upgraded real-time gas and temperature sensors in the summit caldera. Alarms have been set to alert scientists to significant changes in several data streams, including real-time seismic amplitude (a measure of seismic energy release), ground tilt, and satellite- and ground-based thermal imagery. Revised maps showing potential inundation zones and likely lava flow paths based on topography derived from digital elevation maps have been prepared.

    As with any precursory volcanic eruption sequence, it will be challenging to choose the correct time to alert authorities and elevate public concern about a possible eruption. Once an eruption has commenced, pinpointing the exact location of the outbreak—especially at night or in cloudy conditions—may not be straightforward and may require the use of new tools such as infrasound. Vent location determines which downslope areas are at greatest risk, so addressing this capability gap is a high priority.

    As of this writing, elevated rates of seismicity and deformation continue. Improvements in monitoring networks and alarming systems since 1984 put HVO in a better position to provide early warning and, once an eruption has commenced, help guide emergency response. Additional efforts to inform and prepare the public for the eventual eruption are an important step in minimizing impacts to life and property.

    References

    Decker, R. W., et al. (1983), Seismicity and surface deformation of Mauna Loa volcano, Hawaii, Eos Trans. AGU, 64(37), 545–547, https://doi.org/10.1029/EO064i037p00545-01.

    Klein, F. W. (1982), Patterns of historical eruptions at Hawaiian volcanoes, J. Volcanol. Geotherm. Res., 12, 1–35, https://doi.org/10.1016/0377-0273(82)90002-6.

    Koyanagi, R. Y. (1987), Seismicity associated with volcanism in Hawaii: Application to the 1984 eruption of Mauna Loa volcano, U.S. Geol. Surv. Open File Rep., 87-277, 76 pp.

    Koyanagi, R. Y., E. T. Endo, and J. S. Ebisu (1975), Reawakening of Mauna Loa volcano, Hawaii: A preliminary evaluation of seismic evidence, Geophys. Res. Lett., 2(9), 405–408, https://doi.org/10.1029/GL002i009p00405.

    Lockwood, J. P., et al. (1987), Mauna Loa 1974–1984: A decade of intrusive and extrusive activity, in Volcanism in Hawaii, chap. 19, U.S. Geol. Surv. Prof. Pap., 1350, 537–570.

    Miklius, A., and P. Cervelli (2003), Interaction between Kīlauea and Mauna Loa, Nature, 421, 229, https://doi.org/10.1038/421229a.

    Okubo, P. G., and C. J. Wolfe (2008), Swarms of similar long-period earthquakes in the mantle beneath Mauna Loa volcano, J. Volcanol. Geotherm. Res., 178, 787–794, https://doi.org/10.1016/j.jvolgeores.2008.09.007.

    Thelen, W. A., S. D. Malone, and M. E. West (2010), Repose time and cumulative moment magnitude: A new tool for forecasting eruptions?, Geophys. Res. Lett., 37, L18301, https://doi.org/10.1029/2010GL044194.

    Trusdell, F. A. (2012), Mauna Loa—History, hazards, and risk of living with the world’s largest volcano, U.S. Geol. Surv. Fact Sheet, 2012-3104, 4 pp., https://pubs.usgs.gov/fs/2012/3104/.

    Walter, T. R., and F. Amelung (2006), Volcano-earthquake interaction at Mauna Loa volcano, Hawaii, J. Geophys. Res., 111, B05204, https://doi.org/10.1029/2005JB003861.

    Author Information

    Weston Albert Thelen (email: wthelen@usgs.gov), Cascade Volcano Observatory, U.S Geological Survey, Vancouver, Wash.; and Asta Miklius and Christina Neal, Hawaiian Volcano Observatory, U.S. Geological Survey, Hawaiʻi National Park, Hawaii

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  • richardmitnick 2:33 pm on October 10, 2017 Permalink | Reply
    Tags: , Eos, , Ritter Island, , Volcanic islands are the source of some of the world’s largest landslides,   

    From Eos: “An 1888 Volcanic Collapse Becomes a Benchmark for Tsunami Models” 

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    10.10.17
    Aaron Micallef
    Sebastian F. L. Watt
    Christian Berndt
    Morelia Urlaub
    Sascha Brune
    Ingo Klaucke
    Christoph Böttner
    Jens Karstens
    Judith Elger

    1
    Scientists aboard the R/V Sonne (shown here) profiled the seafloor and subsurface structures near Ritter Island, north of New Guinea, in 2016. A large portion of this volcanic island collapsed and slid into the sea in 1888, making it an ideal case study for modeling volcanic collapse landslides and the tsunamis they generate. Credit: Christian Berndt

    Early one March morning in 1888, a 4-cubic-kilometer chunk of the Ritter Island volcano collapsed into the Bismarck Sea northeast of New Guinea. This volume of land was about twice that of the Mount St. Helens landslide in 1980, and it is the largest historically recorded tsunami-causing volcanic sector collapse.

    The ensuing landslide triggered a tsunami tens of meters high. The waves were still 8 meters high when they reached parts of the island of New Guinea that are several hundreds of kilometers away, according to observers who witnessed the event [Ward and Day, 2003].

    Volcanic islands are the source of some of the world’s largest landslides. These landslides have the potential to generate large tsunamis. Scientists have debated the magnitude of these tsunamis, but much uncertainty remains over landslide dynamics and how far a tsunami can travel across an ocean basin while remaining large enough to cause damage.

    Studies of Ritter Island’s landslide and ensuing tsunami could significantly reduce that uncertainty. During a 6-week-long expedition in November and December 2016 aboard the German R/V Sonne, we mapped the Ritter Island collapse scar and deposit using hull-mounted multibeam sonar systems, which produced high-resolution bathymetry (Figure 1) and acoustic backscatter data.

    We are using data from this expedition, alongside a range of direct observations and samples, to generate a detailed interpretation of the Ritter Island landslide. With these robust field data, we set the stage for testing coupled landslide-tsunami models.

    An Ideal Study Site

    Ritter Island’s historic landslide, along with a heightened awareness of tsunami hazards following several recent devastating events, has caused some to wonder if other volcanic islands could experience flank or total collapse and, if so, how far tsunamis could reach. One hypothetical scenario that captured the attention of the popular media in 2004 involves a potential collapse of the Cumbre Vieja volcano on the southern half of the island of La Palma, one of the Canary Islands off the northwest coast of Africa.

    Such a collapse could trigger a tsunami that races across the Atlantic Ocean. However, recent tsunami models span an order of magnitude in their predictions of far-field wave heights for the La Palma collapse scenario.

    Resolving such discrepancies in our understanding of landslide and tsunami processes requires a field data set in which both phenomena can be observed to test current models. The sector collapse of Ritter Island, Papua New Guinea, in 1888 meets both these criteria.

    The landslide generated a tsunami that devastated shorelines as far as 600 kilometers away [Day et al., 2015]. An important factor is that there are eyewitness observations of the tsunami height, arrival time, and frequency at a range of locations around the Bismarck Sea [Day et al., 2015]. The event can thus be used as a benchmark for testing models of landslide-generated tsunamis if the volume, distribution, and dynamics of the landslide mass can be reconstructed.

    2
    Fig. 1. (a) Three-dimensional view of the Bismarck Sea between Umboi and Sakar islands compiled using data from the SO-252 multibeam echo sounder, bathymetric data from the General Bathymetric Chart of the Oceans (GEBCO), and altimetry from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) satellite. The gray transparent cone represents Ritter Island before the 1888 event. Black lines and the red box indicate 2-D and 3-D seismic reflection data, respectively, acquired during the SO-252 expedition. The white arrows here and below indicate the direction of material mobilization during the 1888 event. (b) Three-dimensional reflection seismic data (from the area in the red box above) showing the Ritter Island deposit, remnant block, and parasitic volcanic cone. No image credit.

    Geological Setting

    Ritter Island is located north of Australia in the Bismarck Sea about 80 kilometers north of New Guinea and some 20 kilometers off the western end of New Britain. Situated between the islands of Umboi and Sakar (Figure 1), it forms part of the Bismarck Volcanic Arc, which results from the northward subduction of the Solomon Plate underneath the Bismarck Plate [Baldwin et al., 2012]. Today, Ritter Island is a narrow, crescent-shaped island, around 1.2 kilometers long and 200 meters wide, reaching an elevation of approximately 140 meters above sea level.

    This island is all that remains of a larger, steep-sided conical island that was around 750 meters high before it collapsed in 1888 [Day et al., 2015]. During the 19th century, Ritter Island was known among navigators in the region as a highly active volcano, characterized by frequent Strombolian activity [Johnson, 2013].

    There is evidence for several submarine eruptions since 1888 that have constructed a cone with a current summit around 200 m beneath sea level. The remnant of the island above the waterline is dominated by interbedded sequences of basaltic scoria and thin lava flows that are consistent with low-level Strombolian activity.

    3
    This arc is all that remains of the Ritter Island volcanic cone. Underwater deposits show clear evidence of the landslide triggered by the collapsing cone, and eyewitness accounts described the resulting tsunami. Credit: Christian Berndt.

    Contemporary observations of the tsunami triggered by the 1888 event suggest a single wave train, which is consistent with one main phase of landslide movement and tsunami generation [Day et al., 2015]. The landslide deposit is young enough to be preserved at the seafloor without significant overlying sedimentary cover, so it can be examined today to understand the emplacement dynamics of a large volcanic island landslide.

    Volcanic island landslides with volumes of 1 to 10 cubic kilometers, such as the Ritter Island landslide, have a global recurrence interval of 100 to 200 years [Day et al., 2015]. Therefore, a similar event is likely to occur in the next 100 years, in contrast to the extremely large ocean island collapses (e.g., Canary Islands and Lesser Antilles) that have recurrence intervals of tens of thousands of years or more.

    Collecting the Field Data Set

    During our 2016 expedition, we used a Parasound subbottom profiler with 10-centimeter resolution, as well as 2-D multichannel seismic data and P-Cable 3-D reflection seismic data acquisition systems to image the collapse deposit with 5-m vertical and horizontal resolution (Figure 1). Additional observations and samples collected across the deposit and island flanks, using towed video cameras and sediment samplers, provide ground truthing of the geophysical data and allow us to construct a detailed interpretation of landslide emplacement processes.

    The acquired data show the three-dimensional structure of the Ritter Island landslide deposit and enabled us to reconstruct the kinematics of the emplacement process. The new data set will be used to do the following:

    quantify the overall volume of the material that has been mobilized
    decipher the nature and extent of landslide disintegration
    determine the location, distribution, and size of transported blocks
    identify the nature and origin of different regions of the landslide deposit
    understand the relationship between landslides and the eruption history of Ritter Island and surrounding volcanoes

    These are key parameters for determining the landslide failure and emplacement process and the dynamics of the 1888 tsunami. An initial assessment of the data indicates that the flanks of Ritter Island below sea level expose clastic sequences similar to those in the scar above the water, with an increase in more massive lava units in the lowermost part of the edifice. The landslide cuts deeply into the island structure, and the scar exposures suggest an edifice that is dominated by loosely compacted layers of volcanic rock fragments.

    The landslide mass split and flowed around a remnant block of the island and dispersed within the channel between Umboi and Sakar (Figure 1), where it formed a deposit that is relatively flat at the margins and has irregular channelization in the central part. Parts of the landslide deposit traveled through a constriction between Umboi and Sakar and incorporated underlying seafloor sediment.

    A Framework for Future Models

    Our observations indicate that minor changes in slope gradient can strongly affect landslide dynamics. The deposition of the Ritter landslide entailed a progressive, multiphase, brittle to plastic failure that mobilized material over a considerable distance. The distal deposit, near the leading edge of the landslide, incorporates a major proportion of underlying seafloor sediment.

    Seismic profiles through the distal deposit indicate that the 1888 landslide was only the latest of a series of large-volume volcanic landslides from the surrounding islands. Some blocks piercing the seafloor are, in fact, rooted within older and much larger landslide deposits.

    How large a tsunami a volcanic collapse landslide of a given size will generate and how far the tsunami will travel before it dissipates remain open questions. The information we gathered on this expedition will provide the framework for coupled landslide-tsunami models, which are required to assess the destructive potential of sector collapse–related tsunamis.
    Acknowledgments

    This work reflects the joint effort of the SO252 expedition’s shipboard scientific party. We thank Simon Day, Eli Silver, and Russell Perembo for sharing data and helping with the survey planning. We thank the master and crew of R/V Sonne and our technicians for support during the cruise. Data collection was funded through the BMBF project Ritter Island 03G0252A. A.M. acknowledges funding from the European Research Council under the European Union’s Horizon 2020 Programme (MARCAN, grant agreement 677898).

    References

    Baldwin, S. L., P. G. Fitzgerald, and L. E. Webb (2012), Tectonics of the New Guinea region, Annu. Rev. Earth Planet. Sci., 40, 495–520, https://doi.org/10.1146/annurev-earth-040809-152540.

    Day, S., et al. (2015), Submarine landslide deposits of the historical lateral collapse of Ritter Island, Papua New Guinea, Mar. Pet. Geol., 67, 419–438, https://doi.org/10.1016/j.marpetgeo.2015.05.017.

    Johnson, R. (2013), Fire Mountains of the Islands: A History of Volcanic Eruptions and Disaster Management in Papua New Guinea and the Solomon Islands, ANU Press, Acton, Australia, https://doi.org/10.26530/OAPEN_462202.

    Ward, S. N., and S. Day (2003), Ritter Island volcano—Lateral collapse and the tsunami of 1888, Geophys. J. Int., 154, 891–902, https://doi.org/10.1046/j.1365-246X.2003.02016.x.

    Author Information

    Aaron Micallef, Marine Geology and Seafloor Surveying group, University of Malta, Msida; Sebastian F. L. Watt, School of Geography, Earth and Environmental Sciences, University of Birmingham, U.K.; Christian Berndt (email: cberndt@geomar.de) and Morelia Urlaub, GEOMAR Helmholtz Centre for Ocean Research Kiel, Germany; Sascha Brune, GFZ German Research Centre for Geosciences, Potsdam; and Ingo Klaucke, Christoph Böttner, Jens Karstens, and Judith Elger, GEOMAR Helmholtz Centre for Ocean Research Kiel, Germany
    Citation: Micallef, A., S. F. L. Watt, C. Berndt, M. Urlaub, S.Brune, I. Klaucke, C. Böttner, J. Karstens, and J. Elger (2017), An 1888 volcanic collapse becomes a benchmark for tsunami models, Eos, 98, https://doi.org/10.1029/2017EO083743. Published on 10 October 2017.

    See the full article here .

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  • richardmitnick 8:44 pm on October 6, 2017 Permalink | Reply
    Tags: A mission to the Sun first recommended in 1958 is set to launch in 2018, Eos, ISIS-Integrated Scientific Investigation of the Sun instrument suite, ,   

    From Eos: “Solar Probe Will Approach Sun Closer Than Any Prior Spacecraft” 

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    4 October 2017
    Randy Showstack

    NASA Parker Solar Probe Plus

    A mission to the Sun first recommended in 1958 is set to launch in 2018, 6 decades later. NASA’s Parker Solar Probe, which the agency plans to send to space next summer for a nearly 7-year journey, will fly within 4 million miles (6.4 million kilometers) of the Sun’s surface, more than 7 times closer than any other satellite. There, it will help scientists seek answers to fundamental questions about our star such as why its outer atmosphere, or corona, is several hundreds of times hotter than the photosphere, or the Sun’s surface.

    The mission “is a real voyage of discovery,” said Nicola Fox, project scientist for the probe at Johns Hopkins University’s Applied Physics Laboratory (APL) in Laurel, Md. “We’ve been to every major planet, but we’ve never managed to go up into the corona.” Until recently, we haven’t had the technology needed for a spacecraft to fly so close to the Sun and survive, Fox noted.

    She spoke with Eos in an interview last week in a clean room at APL where the probe was temporarily housed in its full flight configuration. APL is implementing the mission for NASA.

    Although scientists have learned a great deal about the Sun from remote sensing and from other spacecraft operating within the outward flow of energetic, charged particles from the Sun known as the solar wind, “you really need to get into [the solar atmosphere] to be able to answer the fundamental questions,” said Fox, who is a member of the Eos Editorial Advisory Board.

    In addition to probing why the corona sizzles at temperatures about 300 times higher those at the surface, the mission aims to explore “why in this region the solar wind suddenly gets so energized that it can actually break away from the pull of the Sun and move out at millions of miles an hour to bathe all of the planets,” Fox added. Entering the envelope of hot plasma surrounding the star may also help researchers understand more about high-energy solar particles.

    Technological Advances

    The probe is named for astrophysicist Eugene Parker, professor emeritus at the University of Chicago, who in 1958 wrote a paper about what is now referred to as the solar wind and whose work underpins a great deal of our knowledge about how stars interact with planets. In the decades since a committee of the National Academy of Sciences recommended the mission, improvements in thermal protection technology have made it possible to shield the spacecraft and its suite of instruments from the intense radiation and heat from the Sun.

    On 21 September, scientists lowered an 11.43-centimeter-thick carbon composite heat shield onto the probe to test its alignment and ensure that it will shade the craft and keep the instruments safe in the harsh environment. Those instruments will study the Sun’s electric and magnetic fields, plasma, and energetic particles and image the solar wind.

    “Everything lives in the shadow” created by the heat shield that will always be oriented to face toward the Sun, said James Kinnison of APL, a mission system engineer for the space probe who also spoke with Eos in the clean room. With the heat shield forming a cone-shaped shadow, “all the electronics stay at normal temperature [and] nothing gets really hot as long as the heat shield is pointed toward the Sun,” he said.

    1
    Engineers at APL lowered the heat shield onto the Parker Solar Probe spacecraft last month to test alignment. Credit: NASA/JHUAPL, CC BY 2.0

    Because the spacecraft will often need to operate autonomously when it is behind the Sun or subject to communication delays because of its distance from Earth, the probe includes a system to detect and quickly recover from even a slight misalignment of its axis.

    “If it starts tilting, for instance, that would be a problem that would have to be detected very quickly, and you want to recover from that,” said Kinnison. “We do an awful lot of testing on the spacecraft here on Earth before we launch to know that that’s going to work. We’re very certain that it will work.”

    The development of solar power arrays able to withstand the intense solar environment has also enabled the mission, Kinnison said. The probe will operate on about 350 watts of power for all of its science and engineering needs, including collecting scientific measurements and downlinking data. Aside from the solar array and the heat shield, most of the spacecraft’s other components are “relatively normal,” he said.

    Space Weather

    Fox and others noted that the mission, which has a launch window from 31 July to 19 August 2018, could help scientists to better understand how outbursts of energy and particles from the Sun, known as space weather, affect Earth. “We can have beautiful aurora. We can also have catastrophic events,” Fox said. “Until you go up and really understand what’s going on in that region, you really can’t do a better job of predicting what’s going to hit the Earth. So [the mission] is important for fundamental science, but it has very real world impacts.”

    It could lead to “transformational changes to the models that we use to predict space weather,” she added.

    Eric Christian, deputy principal investigator for the solar probe’s Integrated Scientific Investigation of the Sun (ISIS) instrument suite, told Eos that the Sun’s activities can affect the power grid and human and satellite operations in space.

    Just as terrestrial weather forecasting has gotten better, space weather forecasting also needs to improve, he contended.

    “If we want to spread throughout the solar system with robots and manned missions,” Christian said, “we’re going to need to understand [the Sun and space weather] better.”

    See the full article here .

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  • richardmitnick 7:56 pm on October 6, 2017 Permalink | Reply
    Tags: , , Eos, Long floating arrays of hydrophones pick up the sound waves, Marine seismic surveys, Ocean bottom seismometers, , Seventy percent of Earth’s surface geology is under water,   

    From Eos: “Keeping Our Focus on the Subseafloor” 

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    3 October 2017
    Nathan Bangs and
    James A. Austin Jr.

    1
    University of Texas at Austin Ph.D. students Kelly Olsen and Brooklyn Gose work on recovering, cleaning, and storing 1 of 50 streamer depth control birds on the back deck of the R/V Langseth during a marine seismic survey cruise. Although relatively few scientists go to sea to collect such data themselves, the data from these surveys provide valuable information on subseafloor structures to a much wider scientific community. Credit: Nathan Bangs

    Seventy percent of Earth’s surface geology is under water, but let’s face it: There are few options for exploring beneath the seafloor, and the limited number of techniques for subseafloor exploration presents a challenge. But with modern seismic imaging techniques it’s surmountable, and the opportunities are extremely exciting.

    The real challenge at present is finding financial support. We need a new funding commitment in the United States to address recent declines in National Science Foundation (NSF) seismic facilities support. We are at a juncture where an increment of additional support from U.S. funding agencies, academic institutions, and/or private contributions for seismic facilities will have a leveraging effect with tremendous science impact for a broad community. With less support, we will still progress, but with substantial new challenges and uncertainty throughout marine science.

    During marine seismic surveys, ships use pneumatic sound sources to generate acoustic waves beneath the water’s surface. Long floating arrays of hydrophones pick up the sound waves, reflected back by subsurface sedimentary layers and crustal structures, to provide a detailed picture of the geology below the ocean floor.

    This technique provides invaluable information for the scientific and petroleum exploration communities alike. However, research funding reductions continue to hamper the marine geoscience community’s ability to collect seismic data in areas of scientific interest.

    Although relatively few scientists are directly involved in collecting these data, a much larger community relies on the data they produce. Thus, a dwindling data stream produces ripple effects that extend far beyond the scientists and crews who go to sea.

    The science community needs to understand what those ripple effects mean. Below, we’ve outlined a few options that we see as the most likely going forward.

    Seismic Techniques Provide Context

    Data from beneath the ocean floor come from several sources, and each type has its own strengths and limitations.

    Drilling and piston coring provide valuable samples for establishing lithologies, ages, geochemistry, and physical properties, but they provide a keyhole view beneath the ocean floor. Cores are only a few centimeters wide, and the information we gain is generally limited by both depth of penetration and the cost of coring expeditions.

    Electromagnetic methods are designed for a broader view, but they provide only bulk property constraints, averaged over the sampling area.

    The reality is that only marine seismic data have the resolution to see into the subsurface, to reveal regional geologic structure, and to help us understand the broader context of “ground truth” sampling from cores.

    2
    Coherence volume derived from the Costa Rica 3-D seismic data acquired on the R/V Langseth in 2011. These data show amazing 3-D detail in the subseafloor geology. Dark lines indicate the disruption in the continuity of seismic reflections from a complex pattern of faulting (mostly normal faults here) within margin shelf and slope cover sediment sequences. Horizontal slices are at 455 and 1,060 m depth. Credit: Nathan Bangs

    We have some amazing seismic data analysis techniques available to us: 3-D imaging, full-waveform inversion, and vertical profiling. We also have technologies to gather these data: Large spatial deployments of ocean bottom seismometers (OBSs), for example, are now possible with governmentally supported OBS instrument pools in the United States and other countries. Advanced multichannel seismic (MCS) reflection platforms, like the United States’ R/V Marcus G. Langseth, are equipped with multiple hydrophone arrays and streamers, which can be as long as 15 kilometers. And we have improved computational facilities for data analyses.

    3
    United States’ R/V Marcus G. Langseth. https://marine.usgs.gov

    Together, these capabilities allow us to “see” into the subseafloor to address fundamental geologic questions on ocean crust formation and evolution, subduction zone earthquake genesis, fluid migration within the crust, continental rifting, and the list goes on.

    More Technology but Fewer Cruises

    However, the availability of high-quality seismic images is in decline. The International Ocean Discovery Program (IODP) Science Evaluation Panel (SEP), scientific ocean drilling’s primary review body, sent the following statement for programmatic review in 2015:

    “The SEP wishes to convey concern regarding the increased pressures on the acquisition of academic active-source seismic data, some of which by design is conducted in support of scientific ocean drilling. Continued reduction in the international marine geoscience communities’ ability to collect seismic data in areas of scientific interest is jeopardizing the scope and impact of IODP science. The SEP consensus is that the IODP should stress the importance, both to member country funding agencies and environmental permit organizations worldwide, of high-quality subsurface images for science and safety in connection with expected continuation of IODP.”

    The SEP concern is justified. From 1995 to 2005, the R/V Maurice Ewing, then the primary U.S. seismic acquisition facility, conducted on average 4.7 seismic (MCS and OBS) cruises each year (in addition to higher-resolution surveys) and participated in multiship vertical seismic profiling projects.

    4
    R/V Maurice-Ewing (Photo courtesy Lamont-Doherty Earth Observatory of Columbia University)

    In contrast, during the past decade, the R/V Marcus G. Langseth, the Maurice Ewing’s successor ship, has conducted an average of 3.2 cruises each year, with only 5 total in 2016 and 2017.

    This decline raised questions explicitly addressed in the 2015 National Academy of Sciences’ decadal survey of ocean sciences: Should the National Science Foundation consider divestiture of this expensive facility to maintain a healthy balance between spending on technology and infrastructure and spending on science? Are seismic facilities serving too few scientists to justify such infrastructure?

    Worth the Investment?

    To address these questions, the University–National Oceanographic Laboratory System (UNOLS) conducted a June 2016 survey to assess the community’s seismic needs. Response was excellent; in 2.5 weeks, 263 completed the survey. (As a comparison, the virtual town hall that surveyed the ocean sciences community as input to the National Academy of Sciences report generated about 400 responses over 20 weeks.)

    The UNOLS survey confirmed that although a minority of the respondents acquire data at sea, and most of those are senior scientists (at least 20 years post Ph.D.), the seismic data they collect are used by many more. Half of the respondents considered themselves nonspecialists who rely only on processed seismic data and interpretations, without other involvement.

    The majority of respondents had never submitted an NSF proposal to acquire seismic data; 75% had not served as a primary investigator (PI) or co-PI on a seismic acquisition and processing project in the previous 5 years. Many stated that they do not have the background to acquire seismic data. However, 94% said they plan to use seismic data in the future, primarily through collaborations.

    The most commonly cited reason for not serving as a PI on a Langseth-type acquisition cruise was a lack of background in seismology or know-how with acquisition, processing, and interpretation techniques. Processing seismic reflection data requires extensive technical knowledge, advanced computer systems equipped with appropriate (often expensive) software, and generally 1–2 years or more of postacquisition processing effort.

    Overcoming these challenges is not practical or even possible for many; the pool of seismic specialists will remain small. Yet the UNOLS survey confirms the demand for seismic data beyond the small number of PIs who acquire and process them. Therefore, a loss of acquisition facilities would have wide-reaching effects on Earth sciences.

    The survey also confirms that many seismic tools (Figure 1) are needed to address the diverse science goals of current and envisioned U.S. Earth science programs, some of which include international partners and span shore lines (e.g., IODP, Geodynamic Processes at Rifting and Subducting Margins (GeoPRISMS), and subduction zone observatory).

    Weighing the Options

    Can we maintain seismic acquisition capabilities with reduced funding? With the exception of the Scripps Institution of Oceanography high-resolution (short-streamer) portable MCS system, Langseth is the only U.S. seismic facility. Langseth can acquire 3-D volumes and 2-D data with streamers more than 6,000 meters long, an “aperture” long enough to image at crustal scales.

    4
    Fig. 1. Results of a June 2016 UNOLS survey to assess the scientific community’s needs for seismic data from the ocean floor and below. Shown here are the percentages of respondents for each type of primary interest and the facilities they use. Multiple responses were allowed. Credit: Nathan Bangs

    In August 2016, the NSF Division of Ocean Sciences distributed a “Dear Colleague” letter stating that “OCE anticipates spending an annual average of ~$8M for ship support and ~$2M for technical support, funding permitting, and supporting seismic infrastructure.” At current Langseth rates, this amounts to operations for some 90 to 112 days, only about 75% of the total 120–150 days per year considered viable for any UNOLS vessel.

    Operating fewer than 120–150 days in a given year actually increases the cost per day. This makes the Langseth operational costs stand out even more while limiting support for the highly experienced crew necessary for state-of-the-art seismic operations.

    Aside from making Langseth a general-purpose vessel and using it to serve other marine science programs, options are limited:

    Option 1. One option is to improve efficiency and increase funding. Since 2015, Langseth has operated according to a long-range framework to minimize transits and maximize opportunities through developing regional and international collaborations. In late 2017 and 2018, Langseth will operate offshore New Zealand, with support from that country, Japan, and the United Kingdom. Unfortunately, international support is limited because partner countries must also support their own facilities.

    Improved efficiency is also possible through sharing facilities internationally. Langseth is currently the most capable academic facility for crustal-scale 2-D/3-D imaging, but it is the only U.S. option for crustal-scale work. International collaboration to exchange Langseth with other international vessels would improve both opportunity and efficiency globally; the Ocean Facilities Exchange Group does this within the European Union.

    A scaled back seismic program will not only affect the PIs who responded to the UNOLS survey, but it will also affect U.S. institutions they represent through loss of NSF support: those who receive funding for seismic data acquisition and those relying on seismic results. Among international programs affected by scaled-back seismic facilities, IODP stands out. Broad support for seismic facilities from U.S. academic institutions would produce returns for these institutions.

    Institutional support could provide Langseth operational costs, but only through collaborative, multiyear commitments. As NSF described in their recent program solicitation “Provision of Marine Seismic Capabilities to the U. S. Research Community,” the agency is committed to providing Langseth or equivalent capabilities, but the proposed funding levels ($10 million per year) would be problematic for the current model. Is any other model viable?

    Option 2. Without Langseth, there will still be exciting science to do, using data from shorter streamers, archived data, and data available (occasionally and in certain areas) from industry.

    Unfortunately, this approach will change the foci of U.S. seismic studies. For example, reduced seismic imaging capability would limit large, successful international programs like IODP. Recent progress on understanding the largest earthquakes and tsunamis on Earth generated at subduction zones will be severely compromised in the future without an ability to see deep subduction zone structures and measure physical properties with seismic tools. Science would need to target shallower settings: submarine landslides, gas hydrates, fluid and gas migration, sea level change, and the like, using cheaper, portable (higher-resolution, smaller) seismic systems.

    Data would be less complicated and easier to process. Higher resolution could even be 3-D, using P-cable systems available from multiple U.S. institutions. However, these systems can rarely deploy streamers long enough or sources powerful enough to fully characterize even shallow stratigraphy and structure, and they can’t address crustal-scale problems at all.

    Going Commercial?

    In 2015, NSF conducted a workshop with invited members from the marine seismic community, primarily the now disbanded Marcus Langseth Scientific Oversight Committee, to consider a long-streamer portable system and commercial contracting. The workshop report concluded that the weight and size of portable systems incorporating long (6–8 kilometer) streamers with moderate-size, tuned acoustic sources made them impractical for current UNOLS vessels.

    Commercial contracting is viable for long-offset 2-D and 3-D acquisition; however, availability could be limited by high costs (especially mobilization costs for work far from oil and gas provinces, where commercial efforts tend to focus), cost volatility, and changes in ship availability due to hydrocarbon market cycles. These cruises would also lack simultaneous multibeam or gravity and magnetics data acquisition, which has historically been available on U.S. seismic vessels, and student training opportunities would be uncertain and problematic.

    Commercial contracting has been used successfully occasionally in the past, but it is risky to rely on contracting to maintain a regular, global crustal-scale acquisition program as we do now.

    Ironically, this development comes at a time when the IODP is increasing its number of operational days. Other exciting developments, such as seafloor geodesy, will also need an understanding of subsurface structure for tectonic context.

    There is considerable imaging science to be done, with or without Langseth. However, the broad impact of scaling back marine seismic facilities on Earth science makes it time to find more financial support for marine seismic acquisition.

    See the full article here .

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  • richardmitnick 10:10 am on September 27, 2017 Permalink | Reply
    Tags: , Drone Peers into Open Volcanic Vents, Eos, Fortunately robotic technology can go where humans cannot, , UAVs-Unmanned aerial vehicles,   

    From Eos: “Drone Peers into Open Volcanic Vents” 

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    9.27.17
    Nicolas Turner, Bruce Houghton, Jacopo Taddeucci, Jost von der Lieth, Ullrich Kueppers, Damien Gaudin, Tullio Ricci, Karl Kim, and Piergiorgio Scalato

    1
    Stromboli, one of the world’s most active volcanoes, ejects large, hot volcanic bombs in this long-exposure image of the northeastern region of the summit crater terrace. During a May 2016 pilot project, the authors sent unmanned aerial vehicles where humans couldn’t go to capture images and gather data on the locations and characteristics of Stromboli’s craters and vents. Credit: Rainer Albiez/Shutterstock.com

    Volcanoes that erupt frequently give researchers special opportunities to make repeated high-resolution observations of rapid eruption processes. At explosive volcanoes like Stromboli, situated just off the southwestern coast of Italy, “normal” explosive eruptions take place every few minutes to tens of minutes. However, the rainout of hot volcanic bombs, some as large as a meter across, makes it hazardous for scientists and their instruments to get close enough to Stromboli’s active vents to collect some forms of essential data.

    At volcanoes like Stromboli, we can make many key observations from safe locations, hundreds of meters from the erupting vents. Other key observations must be made from locations beside or immediately above the vents. These underrecorded observations include the exact locations of vents, their dimensions, and the depth to the magma’s free surface. These observations have generally not been feasible because explosions occur at irregular frequencies, and they seldom provide warning; our inability to make these observations has been a major impediment to our models of the eruption process.

    Fortunately, robotic technology can go where humans cannot. Unmanned aerial vehicles (UAVs) have become cheaper and more accessible, and they now have the ability to carry lightweight optical sensors for mapping and aerial observations of volcanic activity.

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    Fig. 1. (top) Digital point cloud model of Stromboli crater terrace showing the two vent areas of the crater terrace. (middle) Digital elevation models (DEMs) of the northeast and southwest vent areas showing morphology. (bottom) Classification maps of active vents, inactive vents, and fumaroles from the high-resolution DEMs, aerial imagery, and low-altitude video observations of activity for active vents and fumaroles. Inactive vents were identified by examining the DEMs for features with morphology similar to that of the active vents.

    We used a UAV in a May 2016 pilot survey campaign at Stromboli to map detailed features of the active crater terrace and produce a high-resolution digital elevation model, with details as small as about 5 centimeters. Different vent areas within this crater terrace host active and inactive vents as well as fumaroles, and the UAV helped us determine their locations and dimensions.

    What We Do Know

    There are many things scientists can observe from volcanoes without drones. For example, remote observations from closely positioned cameras and sensors can record initial velocities for the erupted particles (bombs and ash) [Patrick et al., 2007; Gaudin et al., 2016], event durations and mass eruption rates [Taddeucci et al., 2012; Rosi et al., 2013; Gaudin et al., 2014], temperature and flux of gas species [Burton et al., 2007], and the sizes of the ejected bombs [Gurioli et al., 2013; Bombrun et al., 2015 (sorry, no links)].

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    Fig. 2. A sudden shift in wind direction momentarily sweeps away a gas cloud, giving the UAV a clear view of the interior of the crater and revealing an active vent (2) and an inactive vent (3). Active vent 1 is obscured, but it lies directly behind the bluish gas plume to the left of vent 2.

    Through recent field campaigns at Stromboli, scientists have gathered excellent time-synchronized databases of geophysical data and observations of eruption timings, pulsations, and mass flux derived from seismometers, high-speed cameras, webcams, Doppler radar, and infrasound sensors [e.g., Scarlato et al., 2014]. MultiGAS instruments (which combine optical and electrochemical sensors), Fourier transform infrared spectrometers, and ultraviolet and thermal infrared cameras have captured the nature and flux of key magmatic gases (water, carbon dioxide, and sulfur gases) associated with the activity.

    These sensors, however, have their limits. UAVs, however, can push data collection beyond these limits.

    Soaring Above the Danger

    Over the past 2 decades, Stromboli has been surveyed with lidar technology, but because of the high costs involved with lidar surveys, they are not conducted frequently enough to capture rapid changes at the summit of Stromboli.

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    Fig. 3. The UAV captured this visible-light still frame of an expanding ash-rich explosion from the dominant vent 4. The ash plume is more than 300 meters high.

    UAV-based mapping can supplement or replace lidar surveys. UAVs, popularly known as drones, were first used at Stromboli in 2007 to collect ash samples [Taddeucci et al., 2007]. Since that time, they have become cheaper, smarter, and able to carry higher-quality imaging sensors, such as the X5 camera mounted on the DJI Inspire-1 quadcopter for our 2016 study.

    Advances in the field of computer vision have also yielded software capable of extracting 3-D topography from multiple 2-D images in a process called structure from motion. Pairing this practical technique with UAVs has resulted in widespread adoption across multiple fields in science, and volcanology is no exception [James and Robson, 2012].

    UAVs, in combination with the live webcams deployed around the crater terrace [Fornaciai et al., 2010; Calvari et al., 2016], provide an unprecedented level of monitoring via imaging and sampling eruption plumes. UAVs could even be used to deploy sensors near or inside the vent.

    What’s more, with an extended range, UAVs could allow observations when human access to the summit is forbidden and dangerous. This capability would be especially useful, for example, during the rare paroxysmal phases, which can last several months.

    Given this potential, we decided to put the utility of UAVs to the test.

    First Results

    Even UAVs face challenges like constant gas emissions, high and gusting winds, and unpredictable explosions when mapping volcanic environments like Stromboli. In the worst case, UAVs may be severely damaged, or their data may be lost.

    During our 2016 campaign, explosions proved the most challenging to cope with: On more than one occasion, the UAV was almost engulfed by a rising ash plume while it was mapping directly above an active vent. Active fumaroles constantly sent up clouds of gas, condensed water vapor, and ash particles, making it difficult for the onboard camera to get clear images of these vents for use in mapping the interior of the source craters. Fortunately, shifts in wind would briefly clear the craters, providing the camera with an occasional clear view, as seen in the video below.


    During a May 2016 mapping survey, an unmanned aerial vehicle (drone) captured this close-up view of several active vents on the slopes of Stromboli, one of the world’s most active volcanoes, situated just off the southwestern coast of Italy. Stromboli often produces explosive eruptions every few minutes, making it too hazardous for researchers to approach these vents to take data. Credit: Nicolas Turner and coauthors.

    We constructed the final maps of the crater terrace (Figure 1) by selecting the highest-quality images from more than a dozen mapping flights over 2 days. We processed the images with structure from motion software to construct a relatively gas free orthomosaic (aerial map corrected for distortions) and accompanying digital elevation model.

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    Fig. 4. The UAV captured this image of vents 2 and 5 in the northeast and southwest regions, respectively, between explosions.

    We mapped a total of 4 active vents, 11 inactive vents, and 33 fumaroles in the southwest and northeast vent areas present in May 2016 (Figure 1). There is no clear pattern to vent distribution within the larger structures on the crater terrace. Inactive vents, particularly fumaroles, tend to occur in clusters without a single, consistent orientation. The two principal northeast vents are aligned approximately east–west and are 69 meters apart. The two principal southwest vents are 55 meters apart and aligned roughly north to south.

    Overall, the northeastern active vents were similar to each other in depth and diameter (Figure 2), but the southwestern active vents were significantly deeper. Inactive vents were much shallower than active vents. During a week of observations, the southwestern vents produced the larger and more powerful explosions. Explosions from vent 4 (see Figure 1) were typically ash charged, and the free surface was generally covered by debris between successive explosions. These plumes often reached heights of several hundred meters (Figure 3).

    In contrast, an incandescent free surface was often visible in vent 5 and the active northeastern vents (see Figure 4), and in Figure 5, spattering and outgassing are clearly visible in vent 2 during a repose interval.

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    Fig. 5. Close-up view of vent 2 showing weak discontinuous spattering activity that continued between explosions.

    Implications for Eruption Processes and Volcano Monitoring

    This pilot survey yielded useful data, and it serves as a guide for future more ambitious and repeated deployments. The data we gathered—the precise source locations of explosions, for example—can potentially help us reduce the uncertainty in geophysical model inputs for seismic and acoustic arrays and gravity measurements.

    We hope to establish precise correlations of changing eruption style and intensity with time for single vents, along with synchronous observations of depths to the free surface of magma in the parent vents. This and future deployments will help us to monitor abrupt and progressive changes in the diameter of single vents over time and the influence of these changes on eruptive behavior.

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    Near-infrared picture of a bomb-bearing explosion from vent 5. Light tones denote high (incandescent) temperatures. The vertical field of view is 20.5 meters.

    Our data will assist in making comparisons of how differences in vent width and depth to the free surface, the orientation and inclination of the conduit, and the extent of debris covering the free surface all influence contrasting eruption behavior at adjacent vents.

    The ability to capture such detail at an active volcano offers the opportunity to greatly enhance programs for short-term as well as long-term volcano monitoring. Scientists modeling Strombolian eruptions can use these new data to reduce the uncertainty in numerical model input parameters (e.g., conduit and acoustic modeling).

    The low cost and safety of UAV operations allow small-scale changes to be captured and UAV surveys to be launched as frequently as necessary. These benefits make UAVs a critical complement to other remote sensing and geophysical techniques.

    Acknowledgments

    This study was supported by funding from the National Science Foundation (NSF EAR14-27357) and the VERTIGO Marie Curie ITN, funded through the European Seventh Framework Programme (FP7 2007-2013) under grant agreement 607905. We acknowledge numerous companions during the 2016 campaign at Stromboli, especially Elisabetta del Bello, Valeria Cigala, Bianca Mintz, and Pierre-Yves Tournigand.

    References

    Bombrun, M., et al. (2015), Anatomy of a Strombolian eruption: Inferences from particle data recorded with thermal video, J. Geophys. Res. Solid Earth, 120, 2367–2387, https://doi.org/10.1002/2014JB011556.

    Burton, M., et al. (2007), Magmatic gas composition reveals the source depth of slug-driven Strombolian explosive activity, Science, 317, 227–230, https://doi.org/10.1126/science.1141900.

    Calvari, S., et al. (2016), Monitoring crater-wall collapse at active volcanoes: A study of the 12 January 2013 event at Stromboli, Bull. Volcanol., 78, 39, https://doi.org/10.1007/s00445-016-1033-4.

    Fornaciai, A., et al. (2010), A lidar survey of Stromboli volcano (Italy): Digital elevation model-based geomorphology and intensity analysis, Int. J. Remote Sens., 31, 3177–3194, https://doi.org/10.1080/01431160903154416.

    Gaudin, D., et al. (2014), Pyroclast tracking velocimetry illuminates bomb ejection and explosion dynamics at Stromboli (Italy) and Yasur (Vanuatu) volcanoes, J. Geophys. Res. Solid Earth, 119, 5384–5397, https://doi.org/10.1002/2014JB011096.

    Gaudin, D., et al. (2016), 3‐D high‐speed imaging of volcanic bomb trajectory in basaltic explosive eruptions, Geochem. Geophys. Geosyst., 17, 4268–4275, https://doi.org/10.1002/2016GC006560.

    Gurioli, L., et al. (2013), Classification, landing distribution, and associated flight parameters for a bomb field emplaced during a single major explosion at Stromboli, Italy, Geology, 41, 559–562, https://doi.org/10.1130/G33967.1.

    Harris, A. J. L., et al. (2013), Volcanic plume and bomb field masses from thermal infrared camera imagery, Earth Planet. Sci. Lett., 365, 77–85, https://doi.org/10.1016/j.epsl.2013.01.004.

    James, M. R., and S. Robson (2012), Straightforward reconstruction of 3D surfaces and topography with a camera: Accuracy and geoscience application, J. Geophys. Res., 117, F03017, https://doi.org/10.1029/2011JF002289.

    Patrick, M. R., et al. (2007), Strombolian explosive styles and source conditions: Insights from thermal (FLIR) video, Bull. Volcanol., 69, 769–784, https://doi.org/10.1007/s00445-006-0107-0.

    Rosi, M., et al. (2013), Stromboli volcano, Aeolian Islands (Italy): Present eruptive activity and hazards, Geol. Soc. London Mem., 37, 473–490, https://doi.org/10.1144/M37.14.

    Scarlato, P., et al. (2014), The 2014 Broadband Acquisition and Imaging Operation (BAcIO) at Stromboli Volcano (Italy), Abstract V41B-4813 presented at the 2014 Fall Meeting, AGU, San Francisco, Calif.

    Taddeucci, J., et al. (2007), Advances in the study of volcanic ash, Eos Trans. AGU, 88, 253, https://doi.org/10.1029/2007EO240001.

    Taddeucci, J., et al. (2012), High-speed imaging of Strombolian explosions: The ejection velocity of pyroclasts, Geophys. Res. Lett., 39, L02301, https://doi.org/10.1029/2011GL050404.

    Author Information

    Nicolas Turner (email: nrturner@hawaii.edu; @nicolasrturner) and Bruce Houghton, Department of Geology and Geophysics, University of Hawai‘i at Mānoa, Honolulu; Jacopo Taddeucci, Istituto Nazionale di Geofisica e Vulcanologia, Rome, Italy; Jost von der Lieth, Department of Earth Sciences, Universität Hamburg, Germany; Ullrich Kueppers and Damien Gaudin, Ludwig-Maximilians-Universität München, Munich, Germany; Tullio Ricci, Istituto Nazionale di Geofisica e Vulcanologia, Rome, Italy; Karl Kim, National Disaster Preparedness Training Center, University of Hawai‘i at Mānoa, Honolulu; and Piergiorgio Scalato, Istituto Nazionale di Geofisica e Vulcanologia, Rome, Italy
    Citation: Turner, N., B. Houghton, J. Taddeucci, J. von der Lieth, U. Kueppers, D. Gaudin, T. Ricci, K. Kim, and P. Scalato (2017), Drone peers into open volcanic vents, Eos, 98, https://doi.org/10.1029/2017EO082751. Published on 27 September 2017.

    See the full article here .

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  • richardmitnick 1:57 pm on September 12, 2017 Permalink | Reply
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    From Eos: “Revising an Innovative Way to Study Cascadia Megaquakes” 

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    Eos

    9.12.17
    Sarah Witman

    Researchers probe natural environments near subduction zones to decrypt underlying mechanisms of major earthquakes.

    1
    FEMA

    2
    A diagram of the Cascadia Subduction Zone provided by the Oregon Historical Society.

    3
    The Cascadia subduction zone is likely to experience a megathrust earthquake in the next 50 years or so, but a revised technique uses heat data to better understand the physical nature of subduction zones. Credit: NASA/ISS

    Along the west coast of North America, the Cascadia subduction zone stretches more than 1,000 kilometers from Vancouver Island to Cape Mendocino, Calif. It produced a magnitude 9 megathrust earthquake about 300 years ago, one of the biggest quakes in world history.

    Scientists know that Cascadia will produce another earthquake at some point in the future; the question is how soon. The odds of it happening in the next 50 years are 1 in 3. The Federal Emergency Management Agency projects that Cascadia’s next megathrust earthquake will cause thousands of deaths and injuries and leave millions in need of shelter, food, and water.

    To better understand subduction zones, scientists often study the thermal environments of material that has been pushed up onto the surface during past earthquakes. This buildup of material, called an accretionary wedge, might consist of rock, soil, sand, shells, or any other kind of debris. These wedges also sport subtly different average temperatures at various depths, compared to material located off the wedge.

    In a recent study, Salmi et al. [Journal of Geophysical Research] examined the thermal environment of the Cascadia subduction zone’s accretionary wedge, which stretches for about 97 kilometers along the coast of the state of Washington. Their goal was to find out more about the physical changes of fluids and solids within the wedge in the hopes that the knowledge can help them better anticipate future earthquakes.

    Using data collected on a cruise by the R/V Marcus G. Langseth, the researchers found significant variations in temperature within this section of the Cascadia subduction zone, as well as signs of gas hydrates (ice-like deposits that form from natural gas at the bottom of the ocean) throughout the region. They also detected that most fluids from the deep move upward through the accretionary wedge instead of through the crust, which is different than in most other subduction zones. This change in fluid pathway prevents the plate from cooling and reduces the area where an earthquake might rupture along the two plates: completely within the accretionary wedge, rather than under the continental plate.

    This is the first study to concentrate on the southern Washington margin alone, rather than the subduction zone as a whole, revealing the influence of fluid distribution on local, small-scale temperature variability. This insight opens the door to further research into how local temperature variability might interact with other factors, like stress or fault roughness, to affect earthquake hazards. Overall, this study provides a revised method for probing the thermal environment of an accretionary wedge, a crucial link to the cause of ruptures in Earth’s crust that can lead to earthquakes and tsunamis.

    By understanding these mechanisms more fully, scientists can tell us more about how to prepare for the smallest of tremors and the largest of megaquakes. (Journal of Geophysical Research: Solid Earth, https://doi.org/10.1002/2016JB013839, 2017)

    See the full article here .

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  • richardmitnick 3:06 pm on September 8, 2017 Permalink | Reply
    Tags: Eos, Largest Flare of Past 9 Years Erupts from Sun, ,   

    From Eos: “Largest Flare of Past 9 Years Erupts from Sun” 

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    Eos

    9.8.17
    Kimberly M. S. Cartier

    1
    NASA’s Solar Dynamics Observatory captured this image, blended from two ultraviolet filters, of (left) the X9.3 class solar flare that erupted from the Sun on 6 September and (right) a simultaneous smaller flare from a different active region. Credit: NASA/Goddard Space Flight Center/Solar Dynamics Observatory

    NASA/SDO

    A flare erupting from the surface of the Sun on Wednesday blocked communications and interfered with navigational frequencies across the globe. Large portions Europe, Africa, Asia, and Australia experienced disruptions to low-frequency radio communications, according to the U.S. National Oceanic and Atmospheric Administration (NOAA).

    As the flare jetted outward from the Sun’s surface, the star’s outer atmosphere, or corona, belched a huge cloud of ultrahot, electrically charged particles, known as a coronal mass ejection (CME) toward Earth. The CME prompted a warning from NOAA solar storm watchers of an impending strong (G3) geomagnetic storm or greater through today. An updated NOAA report at 1:57 p.m. Coordinated Universal Time (UTC) today revised the agency’s assessment to “G4 (Severe) geomagnetic storm levels” for the day-lit side of Earth.

    In addition to roiling communications and navigation signals, such geomagnetic storms can create surges or shutdowns in power grids and produce brilliant auroras visible at lower latitudes than usual.

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    Two solar flares exploded from the same region of the Sun within a few hours of each other. This time-lapse footage of the region, seen here in extreme-ultraviolet wavelengths, shows flares and CMEs many times larger than Earth. Credit: NASA/Goddard Space Flight Center/SDO

    According to NOAA’s Space Weather Prediction Center, the flare sprung from the Sun at 12:02 p.m. UTC on 6 September, accompanied by the CME, which arrived at Earth late last night and is expected to persist through today.

    A Blast amid the Calm

    NOAA heliophysicists identified Wednesday’s flare as the largest solar flare to date in the current solar cycle, which is an approximately 11-year cycle that tracks when solar activity increases and decreases. The current solar cycle began in December 2011. Although the Sun’s activity is declining on average, large flares such as these are not uncommon during this stage of the cycle.

    “Some of the strongest solar events occur near solar minimum,” Thomas Zurbuchen, associate administrator of NASA’s Science Mission Directorate, explained on Twitter. “Space Weather matters during the entire solar cycle!”

    Heliophysicists associated with NASA’s Solar Dynamics Observatory (SDO) classified this event as an X9.3 solar flare, meaning it’s in the most intense class of flares. What’s more, the same region of the Sun had produced another X-class flare about 3 hours earlier on the morning of 6 September. Three other moderate-intensity flares have exploded from the region since 4 September, in addition to flares from other active areas on the Sun’s surface.

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    The Sun produced five strong solar flares from 4 to 7 September, including the X9.3 event that generated the large CME near time mark “2017/09/06 14:00.” CMEs are best observed when the bright disk of the Sun is blocked by a coronagraph, as seen in this sequence of images taken by the Large Angle and Spectrometric Coronagraph (LASCO) instrument on the NASA/ESA Solar and Heliospheric Observatory (SOHO). Credit: SOHO/LASCO/National Research Laboratory team

    “It’s the active region that keeps on giving!” tweeted Sophie Murray, a space weather scientist at Trinity College in Dublin, Ireland.

    NOAA’s Space Weather Prediction Center also reported a strong (R3) radio blackout on Wednesday at 9:10 a.m. UTC due to both flares that day.

    See the full article here .

    Please help promote STEM in your local schools.

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

     
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