Abstract: Lamont-Doherty Cooperative Seismographic Network (LCSN) contributes to outreach in ways that are unique to its structure. It is unusual in using a variety of station keepers (college & university faculty, secondary school teachers, museums, nature conservancies etc.) to engage a wide variety of audiences and to reach out to large numbers of the general public. It also provides professional development and improved awareness among station operators who are not professional seismologists. All of this is an example of involving the community to extend seismic observations and thereby makes science accessible to the public. The records obtained from the stations are used to teach the students seismogram interpretation in the classroom as class exercises. The community is served by providing the general public and news media information about the local earthquakes. The LCSN now consists of 41 broadband seismographic stations in New York, New Jersey, Connecticut, Pennsylvania, Delaware, Maryland, New Hampshire and Vermont operated by 48 cooperating partners, with Lamont-Doherty Earth Observatory (LDEO) in Palisades, NY serving as the lead institution. The broadband stations of LCSN are distributed in diverse environments such as a 45 m deep natural cave (Howe Caverns, Cobleskill, NY), middle of the most dynamic city in the world (Central Park in Manhattan), and relatively quiet mountain sites at Adirondacks. The LCSN is also participating in the Advanced National Seismic System (ANSS) led by the U.S. Geological Survey for monitoring earthquakes in the Northeastern United States. The earthquakes that occur in the northeast U.S. are automatically detected and located in near-real time by using ANSS Quake Management System (AQMS), and are promptly reviewed by duty seismologists at the data collection center at LDEO. Earthquake information is reported in timely fashion in 24/7 operations together with NEIC in Golden, Colorado.
Slidecast:
https://vimeo.com/277556195
Abstract: Since it began monitoring earthquakes in northern California almost 130 years ago, the University of California Berkeley Seismological Laboratory (BSL) has been striving to produce the highest quality and most complete seismic data possible in the most modern way. This goal continues to influence choices and investments in instrumentation, installation, telemetry, expertise and manpower. The Berkeley Digital Seismic Network (BDSN), the current incarnation of the BSL’s seismic monitoring system, began in the mid-1980s with the installation of broadband (BB) instrumentation, and in the early 1990s a fully digitally telemetered network . The BDSN has grown from 3 high-quality, high dynamic range, BB installations to almost 50 stations, with almost 100 more stations expected as earthquake early warning funding supports seismic network buildout. In addition to three component BB seismometers and digital accelerometers, many stations also record C-GPS data, that are transmitted continuously to the BSL. Data from BDSN stations and other seismic stations in Northern California are available at the Northern California Earthquake Data Center (ncedc.org) using web serivces (http://service.ncedc.org/) from the DART (Data Available in Real Time) or from NCEDC archives. The BSL also participates in earthquake monitoring in Northern California, as part of the Northern California Seismic System. Data quality is important to the BSL, in terms of completeness, instrument response, and waveform content. To ensure completeness, we retrieve data from remote sites when telemetry allows. We also develop and apply tools to evaluate data for the latter two tasks. Our main effort is to complete the evaluation, without disturbing the data. Recently, we have investigated the responses of our aging STS-1 and STS-2 seismometers. We update results from STS-2 analysis. In addition, we demonstrate a technique to non-invasively estimate the response parameters of horizontal STS-1 seismometers.
Slidecast:
https://vimeo.com/277556564
Abstract: Tsunami warning Centers (TWC’s) must issue warnings based on imperfect and limited data. Uncertainties increase in the near field, where a tsunami reaches the closest coastal populations to the causative earthquake in a half hour or less. In the absence of a warning, the usual advice is “When the ground shakes so severely that it’s difficult to stand, move uphill and away from the coast.” But, what if the shaking is not severe? If, for example, the earthquake ruptures slowly (producing very little perceived shaking) this advice will fail. TWC’s must therefore warn the closest coastal populations to the causative earthquake, where over 80% of the Tsunami based casualties typically occur, as soon possible after earthquake rupture begins. The NWS Tsunami Warning Centers (TWCs) currently issue local Tsunami Warnings for the US West Coast, Hawaii, and the Puerto Rico – Virgin Island region within 2-4 minutes after origin time. Coastal GNSS networks complement seismic monitoring networks, and enable unsaturated estimates of Mw (from Peak Ground Displacement) within 2-3 minutes of earthquake onset time, even for larger Mw 8 to 9 events with much longer rupture durations. NASA/JPL, SIO, USGS, CWU, UCB and UW, with funding and guidance from NASA, and leveraging the USGS funded ShakeAlert development, have been working with the National Weather Service TWC’s to incorporate real-time GNSS and seismogeodetic data into their operations. These data will soon provide unsaturated estimates of moment magnitude, Centroid Moment Tensor solutions, coseismic crustal deformation, and fault slip models within a few minutes after earthquake initiation. The sea floor deformation associated with the earthquake slip can then be used as an initial condition for an automatically generated tsunami propagation and coastal inundation model for coastal warnings.
Slidecast:
https://vimeo.com/277560738
Abstract: Two key factors influence the ground motion level an earthquake can cause at a given site. Firstly, are the inherent characteristics of the earthquake such as magnitude and rupture mechanism besides the location parameters such as distance to the source and depth. Secondly, soil dynamic properties such as fundamental periods and shear wave velocity. From these two key factors, currently it is only possible to determine dynamic properties of the soil before an earthquake occurs. The knowledge of such properties makes a huge difference, as this enables decision makers to take countermeasures through an earthquake resistant design of dwellings and buildings. In this research the N-NE area of Managua city was surveyed. Fundamental periods of the soils were determined with the spectral quotient method. Moreover design spectrum were computed based on the Nicaraguan Building Code (RNC-07) and using information from shear wave velocity profiles through one-dimensional waves propagation. Response spectra were computed based on the excitation of interpolation method. Transfer functions from microtremors shown that the soils fundamental periods are in the range of To1=0.07 to 0.15 s and To2=0.15 to 0.45 s. Shear wave velocity profiles at selected sites in the area were used for seismic microzonation. In general the area can be classified as type C soil (NEHRP 2003). By comparing response spectra with the design spectra obtained following the RNC-07 we found that design spectral accelerations are understimated for the area. Therefore, we propose design spectrum for this area computed from seismic amplification factors determined from one-dimensional wave propagation. Through this research we concluded that is mandatory to perform amplification factors determination in order to compute a realistic design spectrum at a given site.
Slidecast:
https://vimeo.com/277558509
Abstract: In an effort to better understand the seismogenesis of earthquake events and to monitor earthquake activity, a statewide seismic monitoring program, known as TexNet ( http://www.beg.utexas.edu/texnet ), has been funded by the 84th Texas Legislature to deploy seismic stations in Texas. The goal of TexNet is to provide authenticated data to evaluate the location, frequency, and likely causes of natural and induced seismicity. A better understanding of these seismic events will help stakeholders avoid operational procedures that may lead to the occurrence of induced earthquakes. On September of 2016 the first TexNet seismic station was deployed. Up to the end of 2017, 22 new, permanent 3-component broadband seismic stations have been installed. Along with 17 existing stations operated by various networks [US, N4, IM], they make up the backbone of the TexNet seismic monitoring network. These stations, together with 3 auxiliary stations, i.e., long term deployments of portable stations (20s seismometers), provide the observation of baseline seismicity of Texas. In addition, 33 portable pairs of seismometers and accelerometers are deployed to further examine seismic events, in four areas with dense populations or crucial infrastructure. Ground motion data from a total number of 58 additional seismic stations is available through TexNet hub, in real time as seedlink stream and also FDSNWS. For earthquake events which occurred after January 2017, TexNet publishes information of earthquake locations on its website. Both, raw data and earthquake locations provided through the Texas Seismological Network, is an excellent success story of a recent regional seismic network. TexNet has managed to minimize the uncertainties into earthquake locations and decrease the magnitude of completeness for the State. Also, it provides an excellent opportunity to the scientific community to better understand the seismicity in Texas, and increase the public and industry awareness.
Slidecast:
https://vimeo.com/277556360
Abstract: We propose a method for real-time prediction of duration of strong ground motion for earthquake early warning (EEW). Because the long duration of shaking is often observed on basin structure, prediction of duration is important in EEW in addition to the strength of shaking. Although many of EEW system focus on rapid determination of source characteristics such as event hypocenter and magnitude, subject of EEW itself is the prediction of ground shaking, where hypocenter and magnitude are not necessarily required. Recently innovative methods have been proposed for the real-time prediction of ground motion without source characteristics, where current wavefield is estimated precisely using data assimilation, and then future wavefield is predicted based on physics of wave propagation (Hoshiba and Aoki, 2015; Kodera et al, 2018). Site amplification is an important factor for ground motion as well as source characteristics and path factors, and the site amplification is frequency dependent. Because the frequency dependence should be corrected in real-time for EEW, it is preferable to correct the frequency dependence in time domain. The correction was proposed in Hoshiba (2013) by using IIR filter, in which amplitude characteristics were taken into account but phase was not fully taken because minimum phase system is assumed in the IIR filter. Because of it, it was not easy to reproduce the long duration of ground motion on basin structure. Recently a method to introduce the phase characteristics was discussed in Pilz and Parolai (2016) on minimum phase assumption. In this presentation, we will propose a method to correct phase characteristics by changing the minimum phase IIR filter to mixed phase system. The introduction of the mixed phase makes it possible to reproduce the long duration of ground motion on basins, and leads to precise prediction of duration of shaking in EEW.
Slidecast:
https://vimeo.com/277559706
