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  • richardmitnick 8:46 am on February 23, 2018 Permalink | Reply
    Tags: Drones in Geoscience Research: The Sky Is the Only Limit, , Eos   

    From Eos: “Drones in Geoscience Research: The Sky Is the Only Limit” All Drones Need Proper Control Legislation and Enforcement 

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    All Drones Need Proper Control Legislation and Enforcement

    Christa Kelleher
    Christopher A. Scholz
    Laura Condon
    Marlowe Reardon

    A quadcopter is deployed to collect visual and thermal imagery along Onondaga Creek in Syracuse, N.Y. Credit: Syracuse University photo by Steve Sartori.

    In the digital age, our capabilities for monitoring Earth processes are dramatically increasing, offering new opportunities to observe Earth’s dynamic behavior in fields ranging from hydrology to volcanology to atmospheric sciences. The latest revolution for imaging and sampling Earth’s surface involves unmanned aircraft systems, also known as unmanned aerial vehicles, remotely piloted aircraft, or, colloquially, drones.

    Drones come in a variety of shapes, sizes, and platforms. These include several different designs (single rotors, multirotors, hybrids, and fixed-wing platforms) that can be used to carry many different types of payloads, including sensors, cameras, and sampling equipment. More important, drones are now applied toward a range of objectives for assessing dynamic processes in two, three, and four dimensions, revolutionizing our ability to rapidly collect high-quality observations across Earth’s surface.

    The geosciences community at large has taken to the skies, with a broad spectrum of researchers using an array of drone platforms and sensors or samplers in several unique and innovative applications. The codevelopment of drone technology alongside new sensor technology is paving the way for drones to be used as more than just Earth surface imagers. This opens a world of possibilities for Earth science research.

    Six Ways That Drones Transform Geoscience Research and Environmental Monitoring

    A review of the geosciences literature shows that drones are now actively applied toward several objectives and across many fields (Figure 1). The latest generation of drones is especially versatile because these drones can carry payloads of sensors and sampling equipment capable of collecting an impressive variety of images, physical samples, and synoptic measurements.

    Here are six ways that drones blaze new paths of observation:

    1. Drones characterize topography. In recent years, drones have increasingly assisted with the photogrammetry technique known as structure from motion (SfM), where 2-D images are transformed into 3-D topographic surfaces (Figure 2). This technique provides high-resolution topographic imagery, which can be used to augment existing topographic data as well as to identify microtopographic features like small water channels on the surface of a glacier.

    In a study by Rippin et al. [2015], SfM techniques used drone imagery to produce high-resolution digital elevation models over the lower reaches of a glacier in Svalbard. The team then used the models to identify minor channels that were altering the roughness of the ice surface. Because roughness alters energy exchange, the findings of this study have implications for understanding the energy balance of glaciers.

    SfM is relatively inexpensive compared with traditional survey methods such as lidar, and it can be used with off-the-shelf software available for imagery postprocessing and development to produce high-resolution digital elevation models (DEMs).

    Fig. 2. A 3-D model produced using SfM photogrammetry obtained at Chimney Bluffs State Park in New York. Note the badlands landscape produced by severe shoreline erosion of Pleistocene age drumlins. The inset shows an aerial view of this type of topography on the southern Lake Ontario shoreline at Chimney Bluffs State Park. Credit: Main imaget: P. Cattaneo, J. Corbett; Inset: C. Scholz

    2. Drones assess hazardous or inaccessible areas. Drones are particularly useful for acquiring imagery or measurements over locations that are hazardous or difficult to reach on foot. In one early example, McGonigle et al. [2008] acquired measurements of volcanic gases using a quadcopter outfitted with spectrometers and electrochemical sensors within the La Fossa crater (Vulcano, Italy). The study set the benchmark for quadcopter use in volcanology and its ability to measure carbon dioxide flux and enhance eruption forecasting.

    In another example, Brownlow et al. [2016] deployed octocopters to monitor methane (CH4) dynamics both above and below the trade wind inversion on Ascension Island in the South Atlantic Ocean, an ideal location for characterizing tropical background methane concentrations. The octocopters operated at high elevations, sampling methane at altitudes up to 2,700 meters above mean sea level. The researchers then used observed air chemistries to delineate chemical signatures that indicate sources of air masses at various altitudes. The study demonstrated ultimately that atmospheric monitoring via drones can reveal spatial complexities (e.g., the air column) that are often missed by sampling at the surface.

    In another innovative application, Ore et al. [2015] designed and deployed a quadcopter capable of collecting water samples from rivers and lakes. These researchers successfully applied their system, which can collect three 200-milliliter water samples under moderate wind conditions, during more than 90 different missions on lakes and waterways. Such efforts present an exciting path for monitoring environmental hazards or disasters such as oil spills, tracking waterborne diseases, and sampling remote locations.

    3. Drones image transient events. Drones are ideal for mapping nutrient blooms, sediment plumes (Figure 3), and floods, examples of ecosystem and landscape responses that may occur for only short periods of time. Spence and Mengistu [2016] demonstrated the use of drones to identify an intermittent stream network in the St. Denis National Wildlife Area in Saskatchewan, Canada.

    The authors also found that drone delineation of narrow intermittent streams consistently outperformed delineation with multispectral SPOT-5 satellite imagery (10-meter resolution). In fact, training SPOT-5 delineation on drone imagery did not improve classification accuracy, suggesting that high-resolution drone imagery may be one of the few tools capable of capturing continuous images of fluvial dynamics at relatively fine scales.

    4. Drones contextualize satellite and ground-based imagery. With the proliferation of satellite data products, comparisons between drone-collected data and satellite imagery offer a pathway for reconciling data collected at multiple spatial scales. This nested approach was used by Di Mauro et al. [2015] to examine how such impurities as mineral dust may alter snow radiative properties in the European Alps.

    They used a combination of snow sampling, red-green-blue imaging with quadcopter drones, and Landsat 8 imagery, producing local and regional maps that demonstrated the effects of snow impurities on snow albedo. These impurities directly affect snow surface energy exchanges at many spatial scales, so these researchers’ findings are useful for climate modeling as well as for mapping potential feedbacks between snow surfaces and energy exchange.

    5. Drone imagery validates computational models. Drone-collected data have also been used to constrain model inputs or to compare data to model simulations in many different fields across the geosciences. One growing application is the spatial modeling of stratigraphy (the sequencing of rock layers in a formation). Drones have the potential to revolutionize assessments of spatial patterns of Earth processes, as demonstrated by two recent studies.

    Nieminski and Graham [2017] describe modeling stratigraphic architecture to characterize difficult-to-access outcrops in the Miocene East Coast Basin in New Zealand. They demonstrate how 3-D SfM alongside 2-D visual imagery can enable interpretations useful for both research and the classroom (Figure 4).

    Drones are also commonly used to create model inputs. Vivoni et al. [2014] demonstrated that fine-scale data collected via drones may be particularly useful for generating distributed hydrologic models. The authors describe several different drone-derived data sets, including elevation models and maps of vegetation classification, at resolutions ranging from about a centimeter to a meter that were used as inputs to a spatially distributed watershed model. Such applications may be useful in places where inputs with resolutions finer than 10 meters are desired but may not yet exist.

    6. Drones make the world a better place. Beyond the research world, the drone revolution is spilling over into many everyday humanitarian and environmental applications around the globe. DroneSeed, a company based in Seattle, Wash., is using swarms of off-the-shelf drones to control invasive vegetation with herbicides. The company aims to use drones to identify microhabitat sites ideal for tree planting, deploying biodegradable seedpods, and protecting tree development by limiting invasive vegetation growth. They seek to replant large areas of rough terrain with a fraction of the manpower required to perform the same work on foot.

    Meanwhile, conservationists are protecting vulnerable, threatened, or endangered species using drones. For example, the nonprofit organization Leatherback Trust is tracking leatherback sea turtles via drones, enabling professionals to follow the turtles to locate and observe their nesting sites, rather than painstakingly identifying nests on foot.

    And even more uses abound. For instance, in the wake of recent hurricane disasters in the southern United States, drones were used in search and rescue operations as well as for infrastructure damage assessment [Moore, 2017].

    Notes on Regulations

    As drone use has evolved, so has the regulatory landscape.

    In the United States, regulations distinguish between recreational operations and operations that are commercial and professional in nature, including research efforts [Federal Aviation Administration, 2017]. These regulations specify the necessary training and certification for remote pilots, and they lay out conditions for safe operation.

    Regulations vary among countries and localities; thus, anyone planning to use unmanned aircraft in a research program must review the applicable rules and obtain the required permits and certifications during the project planning stages. Such due diligence should ensure legal and safe data collection.

    Rising to New Heights

    Drones are revolutionizing the research world, industry, and the environment at large. The technology has untold potential for modernizing approaches to time- and energy-intensive tasks while improving documentation and imagery, environmental conservation, and, ultimately, quality of life around the world. When it comes to drones in the geosciences and environment at large, the sky is the limit.

    This work was supported by an award from Gryphon Sensors, LLC; the Syracuse Center of Excellence; and the Center for Advanced Systems and Engineering at Syracuse University. Special thanks for supporting flights and image processing go to Jacqueline Corbett, Ian Joyce, and Peter Cattaneo.


    Brownlow, R., et al. (2016), Methane mole fraction and δ13C above and below the trade wind inversion at Ascension Island in air sampled by aerial robotics, Geophys. Res. Lett., 43(22), 11,893–11,902, https://dx.doi.org/10.1002/2016GL071155.

    Di Mauro, B., et al. (2015), Mineral dust impact on snow radiative properties in the European Alps combining ground, UAV, and satellite observations, J. Geophys. Res. Atmos., 120, 6,080–6,097, https://doi.org/10.1002/2015JD023287.

    Federal Aviation Administration (2017), Small unmanned aircraft systems, Advis. Circ. 107-2, 1 p., U.S. Dep. of Transp., Washington, D. C., https://www.faa.gov/uas/media/AC_107-2_AFS-1_Signed.pdf.

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

    Moore, J. (2017), Drones deliver storm response, Aircraft Owners and Pilots Assoc., Frederick, Md., https://www.aopa.org/News-and-Media/All-News/2017/September/18/Drones-deliver-storm-response.

    Nieminski, N. M., and S. A. Graham (2017), Modeling stratigraphic architecture using small unmanned aerial vehicles and photogrammetry: Examples from the Miocene East Coast Basin, New Zealand, J. Sediment. Res., 87(2), 126–132, https://doi.org/10.2110/jsr.2017.5.

    Ore, J.-P., et al. (2015), Autonomous aerial water sampling, J. Field Robotics, 32, 1,095–1,113, https://doi.org/10.1002/rob.21591.

    Rippin, D. M., A. Pomfret, and N. King (2015), High resolution mapping of supra-glacial drainage pathways reveals link between micro-channel drainage density, surface roughness and surface reflectance, Earth Surf. Processes Landforms, 40(10), 1,279–1,290, https://doi.org/10.1002/esp.3719.

    Spence, C., and S. Mengistu (2016), Deployment of an unmanned aerial system to assist in mapping an intermittent stream, Hydrol. Processes, 30, 493–500, https://doi.org/10.1002/hyp.10597.

    Vivoni, E. R., et al. (2014), Ecohydrology with unmanned aerial vehicles, Ecosphere, 5(10), 130, https://doi.org/10.1890/ES14-00217.1.

    Author Information

    Christa Kelleher (email: ckellehe@syr.edu), Department of Earth Sciences and Department of Civil Engineering, Syracuse University, N.Y.;
    Christopher A. Scholz, Department of Earth Sciences, Syracuse University, N.Y.;
    Laura Condon, Department of Earth Sciences and Department of Civil Engineering, Syracuse University, N.Y.;
    Marlowe Reardon, Department of Television, Radio, and Film, Syracuse University, N.Y.

    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.

  • richardmitnick 10:13 am on February 16, 2018 Permalink | Reply
    Tags: , , Atmosphere science, Eos, NASA PACE,   

    From Eos: “A Novel Approach to a Satellite Mission’s Science Team” 

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    12 February 2018
    Emmanuel Boss
    Lorraine A. Remer

    NASA Plankton, Aerosol, Cloud, Ocean Ecosystem (PACE) mission satellite.

    The NASA Plankton, Aerosol, Cloud, Ocean Ecosystem (PACE) mission, with a target launch within the next 5 years, aims to make measurements that will advance ocean and atmospheric science and facilitate interdisciplinary studies involving the interaction of the atmosphere with ocean biological systems. Unique to this Earth science satellite project was the formation of a science team charged with a dual role: performing principal investigator (PI)-led peer-reviewed science relevant to specific aspects of PACE, as well as supporting the mission’s overall formulation as a unified team.

    This science team is serving a limited term of 3 years, and recompetition for membership is expected later this year. Overall, the cooperative, consensus-building approach of the first PACE Science Team has been a constructive and scientifically productive contribution for the new satellite mission. This approach can serve as a model for all future satellite missions.


    The PACE satellite, as envisioned, would carry multiple sensors into space as early as 2022. These instruments include a radiometer that will span the ultraviolet to the near infrared (NIR) with high spectral resolution (<5 nanometers). This radiometer will also scan individual bands from the NIR to the shortwave infrared. In addition, the instrument suite would include two different CubeSat polarimeters. These devices are radiometers that separate different polarization states of light over several viewing angles and spectral bands.

    Measurements from these sensors would be used to derive properties of atmospheric aerosols, clouds, and oceanic constituents. Derived products could lead to better understanding of the processes involved in determining sources, distributions, sinks, and interactions of these variables with critical applications including Earth’s radiative balance, ocean carbon uptake, sustainable fisheries, and more.

    The PACE Science Team

    To help map out the scope of the PACE mission, NASA first established a science definition team that provided a report on the desired characteristics of PACE in 2012. Following that report and just before the decision to fund PACE was made, in 2014 NASA published a call for proposals for participants in the first PACE Science Team.

    The scientists funded under this call and selected for the science team were partitioned into two subject areas: One focused on atmospheric correction and atmospheric products, and the other addressed the retrieval of inherent optical properties of the ocean. The team was enhanced with NASA personnel with specific portfolios in two areas: data processing and applications for societal relevance.

    NASA’s solicitation specified “the ultimate goal for each of the two measurement suite teams is to achieve consensus and develop community-endorsed paths forward for the PACE sensor(s) for the full spectrum of components within the measurement suite. The goal is to replace individual ST [science team] member recommendations for measurement, algorithm, and retrieval approaches (historically based on the individual expertise and interests of ST members) with consensus recommendations toward common goals.”

    This new framework differed from past NASA science teams in that PIs not only proposed their own science objectives and coordinated their own research but were also expected to contribute to common goals as well.

    Science Team Activities

    Soon after forming, the science team identified several issues or subject areas of common concern and formed subgroups to address these individual concerns. These areas included construction of novel data sets for algorithm development (both in situ and synthetic data sets), cross comparison and benchmarking of coupled ocean-atmosphere radiative transfer codes, and cross comparison of instruments in the field to assess and constrain uncertainties in the measurements of oceanic particle absorption.

    The science team was also asked by NASA to assess the designs of the PACE radiometer and polarimeter and to determine the value of adding a high spatial resolution coastal camera. An ad hoc subgroup was formed to produce a stand-alone report on the advantages and requirements for polarimetry for atmospheric correction, aerosol characterization, and oceanic retrievals. The team contributed to both the design and content of the PACE website.

    The PACE science team also developed an alternative style for their last two annual meetings that emphasized discussion and interaction. To improve the efficiency of the PACE science team’s workshops, a “flipped meeting” format was adopted in which team members prerecorded their individual presentations in advance and posted these recordings to an internal site. Science team members were able to view and listen to the recordings at their leisure and arrived at the meeting itself readied with questions and discussion points for the presenters. This meeting strategy was successful and led to invigorating two-way discussions.

    Enhanced Collaborations

    The PACE science team is in the last phase of the 3-year term. Several consensus reports are being finalized to provide NASA with input and recommendations about the most likely paths forward for PACE atmospheric correction, atmospheric products, and oceanic optical properties [e.g., Werdell et al., 2018].

    PACE has set itself up to be a model for interdisciplinary collaboration. Early fruits of this can be seen in the multiple collaborations that have sprouted up between ocean and atmospheric scientists, whose vocabulary and culture were initially vastly different. Collaborative products range from published papers that build realistic radiative transfer models from within the ocean to the top of the atmosphere to the assembly of novel databases that contain ocean and atmospheric measurements useful to develop novel algorithms.

    We hope these collaborations will result in increased cooperation in PACE’s future and on future missions. In particular, we’re hopeful that collaborations will lead to enhanced study of processes at the air-sea interface, a complex domain that is relatively unknown, where a holistic and interdisciplinary approach will lead to better understanding of the functioning of our planet.

    PACE’s future is currently uncertain (it is in Congress’s continuing resolutions but was one of the missions the current administration did not support). Although we hope that the mission keeps its funding, we note that the cooperative, consensus-building approach of the first PACE science team was a constructive and scientifically productive contribution to the path forward for a new satellite mission. We expect that this framework to support mission activities will be adopted in future NASA missions to maximize their utility across disciplines.

    Science paper:
    An overview of approaches and challenges for retrieving marine inherent optical properties from ocean color remote sensing, Progress in Oceanography

    See the full article here .

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

  • richardmitnick 12:22 pm on January 26, 2018 Permalink | Reply
    Tags: , , , China Catching Up to United States in Research and Development, Eos   

    From Eos: “China Catching Up to United States in Research and Development” 

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    Eos news bloc


    24 January 2018
    Randy Showstack

    China’s manned submersible Jiaolong on 1 June 2017 after it was retrieved from its 20th dive in the Mariana Trench, the world’s deepest known trench. Although the United States still leads the world in research and development investments, China’s expenditures in these areas soared by an average of 18% annually from 2000 to 2015. Credit: Xinhua/Liu Shiping/Alamy Stock Photo.

    The United States still leads the world in gross domestic expenditures on research and development according to the latest report on such spending. However, the U.S. global share of those activities has dropped from about 37% in 2000 to 26% in 2015, whereas China’s share has increased to 21%, reports the U.S. National Science Board’s (NSB) Science and Engineering Indicators 2018, a congressionally mandated analysis issued on 18 January.

    The new comparison is based on data from 2015. In that year, the United States spent $496.6 billion on research and development (R&D), whereas China spent the equivalent of $408.8 billion. The year 2015 is the most recent one available for many indicators because gathering and analyzing R&D data induce a lag, according to an NSB analyst.

    In 2015, China surpassed the European Union (EU) in gross domestic expenditures on research and development and now trails only the United States. According to the most recent (2015) data, the United States spent $496.6 billion, China spent $408.8 billion, and the EU spent $386 billion. The graph calculates selected country (and EU) expenditures from 1981 to 2015 and converts foreign currencies into U.S. dollars via “purchasing power parity” exchange rates. Credit: Science and Engineering Indicators 2018, Figure 4-6.

    Recent trends show China’s R&D growth is surging. Between 2000 and 2015, R&D has soared by an average of 18% annually in China, whereas U.S. spending rose by about 4% annually, according to the report.

    China has now surpassed the European Union and its $386 billion expenditure on R&D in 2015. At the time of the most recent previous version of the indicators report in 2016, the European Union was still slightly ahead of China according to the 2013 data that was the most recent at the time. If current trends continue, China could surpass the United States within a matter of several years, according to an Eos analysis of the data.

    “The U.S. is still the largest supporter of science and technology, but China is coming on fast, and they are making big commitments to the future,” NSB chair Maria Zuber told Eos. In addition to developing these indicators, NSB governs the National Science Foundation (NSF) and advises the president and Congress on science and engineering policy, research, and education issues.

    “It’s not to say the sky is falling, because the sky isn’t falling. But one also doesn’t want to be asleep at the wheel. There is room for lots of countries to get involved, and it’s good for everybody. But, of course, the U.S. wants to maintain its leadership role.”

    A Huge Increase in Global R&D

    Global R&D expenditures, led by growth in China and other countries, reached $1.92 trillion in 2015 from $722 billion in 2000, up an average of 6.3% annually, or 266% in total over that time period.

    After the United States, China, and the European Union, other countries—including individual members of the European Union—making major investments in R&D include Japan ($170 billion), Germany ($114.8 billion), South Korea ($70.1 billion), France ($60.8 billion), India ($50.3 billion), and the United Kingdom ($46.3 billion). Israel, which invested $13 billion, leads other countries in the percentage of its gross domestic product for R&D expenditures, at 4.25%, followed by South Korea’s 4.23%. By comparison, the United States is at 2.7%, and China is at 2.1%.

    “We are involved in a global race for new knowledge,” NSF director France Córdova said at an 18 January briefing about the report. The United States “may be an innovation leader today, but other countries are rapidly gaining ground. It is not inconceivable that we may be overtaken in time. Our investment in basic research must remain a national priority.”

    China Takes the Lead in Science and Engineering Articles

    The report also tracks a broad range of other indicators, including the number of science and engineering (S&E) articles published, for which 2016 data are the most recent available. For the first time, China has overtaken the United States in that metric.

    In 2016, China published 426,165 S&E articles, or 18.6% of the world’s total, with its numbers increasing from 189,760 in 2006 at an average annual growth of 8.4%. The United States published 408,985 S&E articles in 2016, or 17.8% of the world’s total, according to the report, increasing its output from 383,115 in 2006 at an average annual growth of 0.7%. Globally, the number of S&E articles increased from 1.6 million in 2006 to 2.3 million in 2016, an average annual increase of 2.9%.

    [I see no indication here that many papers by Chinese scientists have been discounted as either fraudulent or just wrong in their science. see http://www.sciencemag.org/news/2017/07/china-cracks-down-after-investigation-finds-massive-peer-review-fraud%5D%5D

    Education and Gender Diversity Trends

    In science, technology, engineering, and mathematics (STEM) education, the United States awarded about 40,000 S&E doctoral degrees in 2014, the most recent year for which data were analyzed, with China awarding 34,000. In 2000, the United States awarded about 25,000 S&E doctoral degrees, with China awarding fewer than 10,000.

    Of 7.5 million S&E bachelor’s level degrees awarded worldwide in 2014, India led with a 25% share, followed by China at 22%, the European Union at 12%, and the United States at 10%.

    Another indicator tracked the growth of academic R&D expenditures by technical field. The average annual growth rate for the geosciences in the United States was just 0.1% from 2007 to 2016, the lowest growth rate of the assessed fields; it grew 3.8% from 1997 to 2006. By comparison, engineering grew 3.2% from 2007 to 2016, down from 4.8%.

    Women in 2015 constituted just 28% of workers in S&E occupations in the United States. For the category of Earth scientists, geologists, and oceanographers, the number was 22.7%, and for physicists and astronomers, it was 18.4%.

    Zuber told Eos she hoped the release of the new report would encourage the U.S. government to invest more in science across all federal agencies and to provide funding stability. “If you don’t know what the budget is going to be, it’s very hard for federal agencies to do long-term planning,” she said.

    See the full article here .

    Please help promote STEM in your local schools.

    STEM Icon

    Stem Education Coalition

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

  • richardmitnick 11:48 am on January 22, 2018 Permalink | Reply
    Tags: , Eos, Geocorona, Lyman Alpha Imaging Camera U Tokyo, The PROCYON spacecraft NAOJ/ESA, Tracing the Path of Gas Atoms from Earth to the Final Frontier   

    From Eos: “Tracing the Path of Gas Atoms from Earth to the Final Frontier” 

    AGU bloc

    Eos news bloc


    Sarah Witman

    Scientists capture the first complete image of Earth’s luminous geocorona and prove its ecliptic north–south symmetry.

    An image of the geocorona, a luminous halo formed by photons released by hydrogen atoms in the outermost layer of Earth’s atmosphere. Credit: Rikkyo University.

    The outermost layer of Earth’s atmosphere, called the outer exosphere, is almost entirely made up of hydrogen. These hydrogen atoms scatter photons, producing a luminous halo called the geocorona. Observing the precise shape of the geocorona would shed light on the last phase of an important geophysical process: the escape of hydrogen atoms from Earth into interplanetary space.

    The exosphere has been observed from within—distances of less than 64,000 kilometers—extensively. But, from the outside looking in, past space missions have been able to observe the geocorona only from far greater distances. For example, Mariner 5 caught a glimpse from roughly 240,000 kilometers out, and Apollo 16 observed it from the Moon—about 380,000 kilometers away.

    In a recent study, Kameda et al. [Geophysical Research Letters] used the Lyman Alpha Imaging Camera on board the Proximate Object Close Flyby with Optical Navigation (PROCYON ) spacecraft to observe Earth’s geocorona from the greatest distance yet: more than 15 million kilometers away.

    LAICA flight model (image credit: U Tokyo.)

    The PROCYON spacecraft and comet 67P/Churumov-Gerasiment (Conceptual Image). Credit: NAOJ/ESA/Go Miyazaki.

    The camera was able to capture the first image of the entire geocorona, stretching more than 240,000 kilometers: 38 times the length of Earth’s radius. (In comparison, partial images captured by past observation revealed roughly 100,000 kilometers, or less than 16 times the length of Earth’s radius.)

    In addition to this comprehensive image—which proved the ecliptic north–south symmetry of the geocorona for the first time—the team used a mathematical model to determine the distribution of the geocoronal emission’s intensity. From this model, they found that the production of hot hydrogen in the magnetized plasmasphere (a layer of dense plasma surrounding Earth) is likely not the main process involved in shaping the outer exosphere, although it may still be involved somehow.

    This study is a step forward in the geophysical and space sciences and the first successful attempt since the 1970s era Apollo mission to paint a picture of the outermost reaches of Earth’s atmosphere.

    See the full article here .

    Please help promote STEM in your local schools.

    STEM Icon

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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.

  • richardmitnick 10:53 am on January 22, 2018 Permalink | Reply
    Tags: , , , , Eos, Marine geodesy, Megathrust zone, ,   

    From Eos: “Modeling Megathrust Zones” 

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    Rob Govers

    A recent paper in Review of Geophysics built a unifying model to predict the surface characteristics of large earthquakes.

    The Sendai coast of Japan approximately one year after the 2011 Tohoku earthquake. The harbor moorings and the quay show significant co-seismic subsidence. The dark band along the quay wall resulted from post-seismic uplift. Credit: Rob Govers.

    The past few decades have seen a number of very large earthquakes at subduction zones. Researchers now have an array of advanced technologies that provide insights into the processes of plate movement and crustal deformation. A review article recently published in Reviews of Geophysics pulled together observations from different locations worldwide to evaluate whether similar physical processes are active at different plate margins. The editors asked one of the authors to describe advances in our understanding and where additional research is still needed.

    What are “megathrust zones” and what are the main processes that occur there?

    A megathrust zone is a thin boundary layer between a tectonic plate that sinks into the Earth’s mantle and an overriding plate. The largest earthquakes and tsunamis are produced here. High friction in the shallow part of the megathrust zone effectively locks parts of the interface during decades to centuries. Ongoing plate motion slowly brings the shallow interface closer to failure, i.e., an earthquake. Other parts of the megathrust zone are mechanically weaker. They consequently attempt to creep at a rate that is required by plate tectonics, but are limited by being connected to the locked part of the interface.

    What insights have been learned from recent megathrust earthquakes at different margins?

    High magnitude earthquakes in Indonesia (2004), Chile (2010) and Japan (2011) were recorded by new networks utilizing Global Positioning System technology, which is capable of measuring ground displacements with millimeter accuracy. This complemented seismological observations of megathrust slip during these earthquakes. The crust turned out to deform significantly during and after these earthquakes. These observations indicated that slip on weak parts of the megathrust zone may be responsible, likely in combination with the more classical stress relaxation in the Earth’s mantle. In regions where megathrust earthquakes are anticipated, crustal deformation observations allowed researchers to identify parts of the megathrust zone that are currently locked. In our review article, we integrate these perspectives into a general framework for the earthquake cycle.

    How have models been used to complement observations and better understand these processes?

    Mechanical models are needed to tie the surface observations to their causative processes that take place from a few to hundreds of kilometers deep into the Earth, which is beyond what is directly accessible by drilling. Many of the published models focus on a single earthquake along a specific megathrust zone. We wondered what deep earth processes are common to these regions globally and built a unifying model to predict its surface expressions. Our model roughly reproduced the observed surface deformation, but it also became clear that some regional diversity would be required to match the data shortly after a major earthquake.

    What have been some of the recent significant scientific advances in understanding plate boundaries?

    Creep on weak parts of the megathrust zone is a very significant contributor to the surface measurements after an earthquake. Mantle relaxation is also relevant. We demonstrate that the surface deformation of these processes may give a biased impression of low friction on the megathrust zone. Creep on the megathrust zone downdip of a major earthquake may be responsible for observations that were puzzling thus far; in an overall context of convergence and compression, tension was observed in the overriding plate shortly after recent major earthquakes.

    What are some of the unresolved questions where additional research or modeling is needed?

    Marine geodesy is an exciting new field that aims to monitor deformation of the sea floor that already yielded important constraints on the deformation of the Japan megathrust. Measurements along various margins will tell whether all megathrusts are locked all the way up to the seafloor. A longstanding question is how observations on geological time scales of mountain building and deformation of the overriding plate are linked to the observations of active deformation. We think that the multi-earthquake cycle model that we present in this review article is a first step towards that goal.

    See the full article here .

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  • richardmitnick 4:09 pm on January 8, 2018 Permalink | Reply
    Tags: , , Eos, ERUPT,   

    From Eos: “Working Together Toward Better Volcanic Forecasting” 

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    A National Academies report highlights challenges and opportunities in volcano science.

    Ecuador’s Tungurahua volcano became active again in 1999, after a hiatus of some 80 years, and it continues to spew ash and shake the ground today. The most recent major eruption occurred in 2014. Better understanding of volcanic processes could lead to better forecasting of such eruptions. A 2017 report summarizes the current state of volcano science and issues three grand challenges for addressing key questions and setting research priorities. Credit: Sebastián Crespo Photography/Moment/Getty Images.

    Michael Manga

    On average, more than 60 volcanoes erupt every year. Although volcanic eruptions can be amazing natural phenomena, they can also have devastating effects on the landscape, atmosphere, and living beings, and these effects can extend over great distances. Data from many types of instruments, combined with a basic understanding of how volcanoes work, can provide an important means of safeguarding lives and property by detecting the signs of an impending eruption and forecasting its size and duration.

    In 2016, NASA, the National Science Foundation, the U.S. Geological Survey, and the National Academies of Sciences, Engineering, and Medicine commissioned a committee to summarize our understanding of how volcanoes work. The committee’s tasks included reporting on new research and observations that will improve scientists’ ability to forecast eruptions and inform monitoring and early warning. Their consensus report, titled “Volcanic Eruptions and Their Repose, Unrest, Precursors, and Timing” (ERUPT), was released in 2017. The report summarizes opportunities to better understand volcanic eruptions and make more useful forecasts of volcano behavior.

    These opportunities are possible because new measurements can better reveal where magma is stored and how it moves. New mathematical models are being developed for the processes that govern eruptions. And technological advances have enabled expanded monitoring from space and on the ground to fill important data gaps. Together, these improvements will lead to more useful forecasts of the timing, size, and consequences of eruptions.

    Questions and Priorities

    The report identifies outstanding questions and research priorities for several aspects of volcanoes: how magma is stored, rises through the crust, and then erupts; new opportunities to improve forecasting; and the interaction between volcanoes and other Earth systems. It also discusses ways to strengthen volcano science.

    Three grand challenges summarize key questions, research priorities, and new approaches highlighted throughout the report:

    forecast the size, duration, and hazard of eruptions by integrating observations with quantitative models of magma dynamics
    quantify the life cycles of volcanoes globally and overcome the biases inherent in assuming a few well-studied volcanoes represent the many
    develop a coordinated volcano science community to maximize scientific returns from any volcanic event

    The report notes that developing models of volcanic systems that can inform forecasting requires the integration of data and methodologies from multiple disciplines. These disciplines include remote sensing, geophysics, geochemistry, geology, atmospheric science, mathematical modeling, and statistics.

    The report also identifies opportunities to move from forecasting dominated by pattern recognition to forecasting based on physics- and chemistry-based models that assimilate monitoring data. This would be a profound paradigm shift but could yield great rewards for forecasting.

    Monitoring Change: Conclusions from ERUPT

    At the report’s core is a simple theme: Determining the life cycle of volcanoes matters.

    This life cycle is key to interpreting precursors and unrest; revealing the processes that govern the initiation, magnitude, and longevity of eruptions; and understanding how magmatic systems evolve during the quiescence between eruptions. Our current understanding is biased by the modest number of comprehensively monitored volcanoes, the types of eruptions that have been studied, and the small (but growing) number of volcanoes with well-established histories of their full life cycles. Satellites and expanded ground-based monitoring networks can fill some of the data gaps, as can extension of observations to the oceans.

    Authors of the report agree that on the ground, a useful goal is to have at least one seismometer per volcano, complemented by more extensive ground-based monitoring at a smaller number of high-priority volcanoes. From space, achieving daily measurements of deformation and passive degassing at all volcanoes on land would ensure global and continuous coverage. Ideally, degassing measurements would monitor carbon dioxide emissions, as well as sulfur dioxide.

    High-resolution maps of thermal emissions and topography and the way they change over time are useful for understanding a spectrum of volcanic processes and Earth system responses to eruptions, the report notes. It also stresses that geological studies, augmented by mapping, scientific drilling, and geophysical imaging of volcanic systems, are necessary to understand volcanism over longer periods of time.

    Myriad Opportunities

    Capitalizing on the new expanded capabilities in volcano monitoring requires that the volcano science community be prepared to quickly monitor or respond to any eruption, the report notes. Such preparations involve strengthening multidisciplinary research, domestic and international partnerships, and training networks. Emerging technologies, including inexpensive sensors, drones, and new microanalytical geochemical methods, provide previously unimagined opportunities.

    Volcano science often advances substantially following well-studied eruptions. A combination of enhanced monitoring, advancing experimental and mathematical models, and integration of research and monitoring will help the volcano science community understand and forecast volcanic eruptions and maximize what we can learn when volcanoes do erupt.

    Copies of the ERUPT report are available without charge from the National Academies.

    See the full article here .

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  • richardmitnick 12:55 pm on December 29, 2017 Permalink | Reply
    Tags: Addition by Subtraction: Raising the Bar for Satellite Imagery, , , , , , Eos, Himawari-8 Advanced Himawari Imager Japan Meteorological Agency, NOAA GOES-16, When it comes to forecaster analysis of complex satellite imagery less can be more   

    From Eos: “Addition by Subtraction: Raising the Bar for Satellite Imagery” 

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    Zhanqing Li

    When it comes to forecaster analysis of complex satellite imagery, less can be more, and a new technique aims to simplify imagery interpretation by suppressing the background noise.

    An example DEBRA applied to a dust storm descends from Mongolia into China on 21 April 2016 at 0800 UTC, as viewed by Himawari-8 Advanced Himawari Imager. Areas of dust are enhanced in yellow, with brightness proportional to DEBRA’s quantitative confidence factor. For an animated version see Miller et al., 2017, Supporting Information Movie S1. Credit: S. D. Miller, Colorado State University

    A picture being worth a thousand words is not always such a good thing! When a complex environmental scene contains too much information, it can be hard for analysts operating in time-critical environments to digest it all.

    The rich spatial, spectral, and temporal resolution offered by next-generation geostationary satellites such as the Himawari-8 Advanced Himawari Imager and the GOES-16 Advanced Baseline Imager, comes with an underlying challenge—how best to sip from this proverbial firehose of data.

    Himawari-8 Advanced Himawari Imager, Japan Meteorological Agency

    Sensor Unit for Himawari 8 Japan Meteorological Agency

    NOAA GOES-16

    Simple attempts to distill the information into colorful graphical displays and enhance a certain feature of interest can be helpful, but sometimes they can do more harm than good. These techniques rely upon the existence of ‘spectral fingerprints’ to isolate the parameter of interest. Problems arise when the fingerprint is not unique, and other parts of the image produce false alarms, causing confusion.

    Miller et al. [2017] [Journal of Geophysical Research] present an elegant new way of separating the wheat from the chaff—reducing the chances of those troublesome false alarms happening to begin with—by accounting for them in advance. The Dynamic Enhancement Background Reduction Algorithm (DEBRA), is a versatile technique applied here to the notoriously diffiucult problem of detecting dust storms from satellite-based multispectral imaging radiometers.

    A chief concern among forecasters has been that there are far too many dust-detection products, many of which are difficult to interpret. DEBRA shows promise in alleviating these frustrations. It accounts for land surfaces that masquerade as dust and adjusts the sensitivity of its detection tests accordingly—enhancing the important signals where present, while suppressing the noise to improve the overall detection accuracy and clarity of display. The result is a numerical gauge of confidence in the presence of lofted dust above various surfaces, making it useful for downstream quantitative applications.

    DEBRA can also be communicated as visually intuitive imagery, where the only colors involved pertain to the feature of interest—the rest of the scene is portrayed as gray scale, preserving the meteorological context. The final enhanced picture may no longer be worth a thousand words, as they say, but its added value to end-users speaks volumes.

    See the full article here .

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  • richardmitnick 2:07 pm on December 28, 2017 Permalink | Reply
    Tags: , , , Eos, , , , The Curious Case of the Ultradeep 2015 Ogasawara Earthquake   

    From Eos: “The Curious Case of the Ultradeep 2015 Ogasawara Earthquake” 

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    Terri Cook

    The intensity distribution across Japan on the Japanese seven-point scale from the 680-kilometer-deep earthquake near the Ogasawara Islands. Credit: Japan Meteorological Agency

    On 30 May 2015, a powerful earthquake struck west of Japan’s remote Ogasawara (Bonin) island chain, which lies more than 800 kilometers south of Tokyo. Although it caused little damage, the magnitude 7.9 quake was noteworthy for being the deepest major earthquake ever recorded—it occurred more than 100 kilometers below any previously observed seismicity along the subducting Pacific Plate—and the first earthquake felt in every Japanese prefecture since observations began in 1884.

    The 680-kilometer-deep earthquake was also notable for its unusual ground motion. Instead of producing a band of high-frequency (>1 hertz) seismic waves concentrated along northern Japan’s east coast, as is typical for deep subduction-related earthquakes in this region, this event generated strong, low-frequency waves that jolted a broad area up to 2,000 kilometers from the epicenter. To explain this uncharacteristic wavefield, Furumura and Kennett [Journal of Geophysical Research] analyzed ground motion records from across the country and compared the results to observations from a much shallower, magnitude 6.8 earthquake that occurred within the Pacific slab in the same area in 2010.

    The results indicated that the peculiar ground motion associated with the 2015 earthquake was due to its great source depth as well as its location outside of the subducting slab. The team found that the ultradeep event was missing high-frequency components and generated milder ground motions at regional distances, whereas the 2010 earthquake included the high-frequency components but was narrowly focused.

    After contrasting three-dimensional numerical simulations of seismic wave propagation from both events, the researchers concluded that waves originating from a deep source outside of the slab can develop a distinctive, low-frequency wavefield as they interact with continental crust and the region’s subducting slabs. Because this wavefield is usually concealed by higher-frequency, slab-guided waves, the few existing examples of this phenomenon will likely provide valuable information on local crustal structure and, in the case of the 2015 Ogasawara event, the morphology of the Pacific Plate.

    See the full article here .


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    Quake-Catcher Network

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

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

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


    BOINC WallPaper

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

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

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

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

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

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

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

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

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


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

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

    The primary project partners include:

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

    The Earthquake Threat

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

    Part of the Solution

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

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

    System Goal

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

    Current Status

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

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

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


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

    For More Information

    Robert de Groot, ShakeAlert National Coordinator for Communication, Education, and Outreach

    Learn more about EEW Research

    ShakeAlert Fact Sheet

    ShakeAlert Implementation Plan

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  • richardmitnick 12:27 pm on December 27, 2017 Permalink | Reply
    Tags: , , , , , Eos, , Scientists Discover Stromboli-Like Eruption on Volcanic Moon, ,   

    From Eos: “Scientists Discover Stromboli-Like Eruption on Volcanic Moon” 

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    JoAnna Wendel

    NASA’s New Horizons mission captured this composite image of an eruption on Jupiter’s moon Io while en route to Pluto in 2007. The erupting volcano is Tvashtar, in the northern hemisphere. New evidence suggests that Io can produce Stromboli-type eruptions, events never before observed on Io. The new data could help scientists figure out the makeup of Io’s interior. Credit: NASA/JPL/University of Arizona​

    NASA/New Horizons spacecraft

    Twenty years ago, “something huge, powerful, and energetic happened at the surface of Io,” said Ashley Davies, a volcanologist at NASA’s Jet Propulsion Laboratory in Pasadena, Calif. Davies and his colleagues think they’ve discovered a type of eruption never before spotted on one of the most volcanically active bodies in the solar system.

    The researchers stumbled on the eruptive evidence in data from NASA’s Galileo orbiter mission, which explored the Jupiter system from 1995 to 2003. They think the data reflect a Strombolian eruption, a violent event named for Italy’s energetic Stromboli Volcano.

    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 [Nicolas Turner, Bruce Houghton, Jacopo Taddeucci, Jost von der Lieth, Ullrich Kueppers, Damien Gaudin, Tullio Ricci, Karl Kim, and Piergiorgio Scalato 27 September 2017] 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

    But wait, you ask, didn’t Galileo plunge into Jupiter’s atmosphere at the end of its mission, way back in 2003?

    NASA/Galileo 1989-2003

    Well, yes. But the orbiter, at that point, had collected so much data about the Jovian system and its Galilean moons (Ganymede, Io, Callisto, and Europa) that scientists still haven’t waded through it all, even 14 years later.

    Davies presented the unpublished research on 13 December at the American Geophysical Union’s 2017 Fall Meeting in New Orleans, La.

    Serendipitous Data

    Io’s surface is constantly gushing lava—every million years or so, the entire moon’s surface completely regenerates. From towering lava fountains that can reach 400 kilometers high to violently bubbling lava lakes that burst through freshly cooled crust, these oozing lava fields can stretch many thousands of square kilometers.

    On this 3,600-kilometer-wide moon, eruptions take place “on a scale that simply isn’t seen on Earth today but was once common in Earth’s past,” Davies said. The scale, frequency, and intensity of Io’s eruptions make it a perfect analogue of early Earth, he continued, back when our blue planet was just a barren hellscape of lava.

    A video of an Io eruption captured by New Horizons in 2007. Credit: NASA/Johns Hopkins University Applied Physics Laboratory

    Davies found evidence for the eruption he reported at Fall Meeting in data from Galileo’s Near Infrared Mapping Spectrometer (NIMS), which took pictures of the moon in the infrared wavelengths. This instrument allowed researchers to measure the thermal emissions, or heat, coming off the volcanically active moon.

    Stromboli Eruption

    While looking through the NIMS temperature data, Davies and his colleagues spotted a brief but intense moment of high temperatures that cooled oddly quickly. This signal showed up as a spike in heat from a region in the southern hemisphere called Marduk Fluctus. First, the researchers saw a heat signal jump to 4–10 times higher than background, or relatively normal, levels. Then just a minute later, the signal dropped about 20%. Another minute later, the signal dropped another 75%. Twenty-three minutes later, the signal had plummeted to the equivalent of the background levels.

    This signature resembled nothing Davies had seen before from Io. The lava flows and lava lakes are familiar: Their heat signals peter out slowly because as the surface of a lava flow cools, it creates a protective barrier of solid rock over a mushy, molten inside. Heat from magma underneath conducts through this newly formed crust and radiates from Io’s surface as it cools, which can take quite a long time.

    This new heat signature, on the other hand, represents a process never before seen on Io, Davies said: something intense, powerful, and—most important—fast.

    There’s only one likely explanation for what the instruments saw, explained Davies, whose volcanic expertise starts here on Earth. Large, violent eruptions like those seen at Stromboli are capable of spewing huge masses of tiny particles into the air, which cool quickly. See for yourself in this video of Stromboli erupting:

    As chance would have it, Galileo was likely in the right place at the right time to see the signatures of such an eruption on Io.

    Composition Questions

    Why do scientists care about an eruption on a moon nearly 630 million kilometers away?

    The temperature of Io’s lava dictates what kind of material makes up the moon, Davies said. For instance, if the rising magma erupts at temperatures of 1,800 or 1,900 K, it’s probably composed of komatiite, a rock extremely low in silicon. This rock is rarely found on Earth today, although scientists think it was commonly found during the Archaen eon 2.5–3.8 billion years ago, Earth’s early volcanic days. However, if the magma erupts at 1,400 or 1,500 K, that means it’s primarily made of basalt.

    The lava’s composition and temperature, in turn, can tell scientists what’s going on in the moon’s interior. Scientists aren’t yet sure how the push and pull from Jupiter’s gravity affect Io’s innards. Some have hypothesized that the grinding from the gravitational pull heats Io’s interior enough to produce a subsurface magma ocean.

    “Instead of being a completely fluid layer, Io’s magma ocean would probably be more like a sponge with at least 20% silicate melt within a matrix of slowly deformable rock,” said Christopher Hamilton, a planetary volcanologist at the University of Arizona’s Lunar and Planetary Science Laboratory in a prior press release about the push and pull of tidal forces on Io. Hamilton was not involved in this research.

    To help refine such hypotheses, scientists need the composition of melt and how hot it gets, Davies explained. But figuring out the precise heat of Io’s lava is tricky because regardless of its starting temperature, it cools relatively quickly. So even if the lava is made of komatiite, scientists may not be able to catch the signal before it cools to a temperature resembling that of basalt.

    The good news about large, Stromboli-type eruptions is that they expose vast areas of lava at incandescent temperatures. “So what we end up with is an event, if you can capture it, that will show a lot of lava at the temperature it erupted,” Davies said.

    Current and future probes can then home in on Marduk Fluctus for more detailed surveys to reveal such precise temperature data, Davies explained. However, until such future instruments launch, scientists still have mountains of Galileo data to get through.

    From Drone Peers into Open Volcanic Vents Further references with links:

    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.

    See the full article here .

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  • richardmitnick 11:42 am on December 27, 2017 Permalink | Reply
    Tags: , , , , Comparing the Accuracy of Geomagnetic Field Models, , Eos,   

    From Eos: “Comparing the Accuracy of Geomagnetic Field Models” 

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    Delores J. Knipp

    Improved accuracy and optimization of models could benefit many applications.

    The figure shows bias of the magnitude error distributions for the Tsyganenko- 2004 (TS04) model by comparing the residual error for TS04 against a validation set. The color scale denotes the number of observation points at that location in comparison space. The X-axis shows the logarithm of the observed magnetic field magnitude. Positive values on the Y-axis imply model over-prediction of the magnetic field magnitude, while negative values imply model under-prediction of the magnetic field magnitude. Here, most of the comparisons (bright colors) show small model-observations differences at locations where the observed field values is ~100 nT, which is typical of geosynchronous orbit magnetic field values. Credit: Brito and Morley, 2017, Figure 5d.

    Improving models of the geomagnetic field is important to radiation belt studies, determining when satellites are on the same magnetic field line, and mapping from the ionosphere to the magnetotail or vice versa, to name just a few applications. Brito and Morley [2017] [Space Weather] present a method for comparing the accuracy of several versions of the Tsyganenko empirical magnetic field models and for optimizing the empirical magnetic field model using in situ magnetic field measurements. The study was carried out for intervals of varied geomagnetic activity selected by the Geospace Environment Modeling Challenge for the Quantitative Assessment of Radiation Belt Modeling Focus Group. The authors describe a method for improving the results of various Tsyganenko magnetic field models, especially with respect to outliers, using a new cost function, various metrics and Nelder-Mead optimization.

    Importantly, this model evaluation was based on points in the magnetosphere that were not used for fitting. Thus, the results provide an independent validation of the method. The model, known as TS04, produced the best results after optimization, generating a smaller error in 57.3% of the points in the tested data set when compared to the standard (unoptimized) inputs. The results of this study include a set of optimized parameters that can be used to evaluate the models studied in this paper. These optimized parameters are included as supplementary material so that the broader scientific community can use the optimized magnetic field models immediately, and without any additional code development, using any standard implementation of the magnetic field models tested in the study.

    See the full article here .

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