Seismologists from Kazakhstan, Russia, and the United States have rescued the Soviet-era archive of nuclear explosion seismograms recorded at Borovoye in northern Kazakhstan during the period 1966–1996. The signals had been stored on about 8000 magnetic tapes, which were held at the recording observatory. After hundreds of man-years of work, these digital waveforms together with significant metadata are now available via the project URL, namely http://www.ldeo.columbia.edu/res/pi/Monitoring/Data/ as a modern open database, of use to diverse communities.

Methods for detecting, associating and locating infrasound events recorded on the global International Monitoring System (IMS) infrasound network are presented. By using likelihood arguments, and reducing the use of empirically determined parameters, our techniques enable us to formally quantify the false alarm rate at both station and network levels, and to calculate confidence areas for event localization. We outline a new association technique that uses graph theory for associating arrivals at multiple spatially separated stations, and perform Monte Carlo simulations to quantify the performance of the scheme under different scenarios. The detection, association and location techniques are applied to 10 large events in the Reviewed Event Bulletin of the Comprehensive Nuclear Test Ban Treaty Organization. Out of 10 events, a total of seven were automatically detected and associated. By analysing the three missed events, we identify improvements that might be made to improve the algorithms.

Automating the detection and location of events using the International Monitoring (IMS) System infrasound network is a significant challenge. Any algorithm must reliably detect nuclear tests in the atmosphere with a minimum number of false alarms. Here, we report on the application of probabilistic techniques for detection, association, and location of infrasound events to data from the IMS network. We compare our results with the SEL3 automatic event detections obtained by the CTBTO.

This Research is about Monitoring Research Review: Ground-Based Nuclear Explosion Monitoring Technologies which presents a preliminary model of the three-dimensional seismic structure of the Iran region.

: This project took advantage of Soviet-era digital seismic recordings, all of them made at the Borovoye Geophysical Observatory in Kazakhstan, of ground motion from numerous underground nuclear explosions that occurred in Eurasia over a period of three decades, from 1966 to 1995. We have prepared these recordings in a modern format, to make them usable by the seismic monitoring community for numerous ongoing and future studies of Earth structure, attenuation characteristics, and explosion source physics including source representation by body force equivalents and associated source spectra. To produce the newly-formatted signals required major efforts at Los Alamos National Laboratory to remove glitches in the original records, and at the Lamont-Doherty Geophysical Observatory to obtain instrument responses. Three different recording systems operated at Borovoye: the KOD system from 1973 to 1990; the SS system from 1973 to 1990; and the TSG system from 1974 to 1995. Each system included channels of low-gain and high-gain recording; and each system included vertical, north/south, and east/west channels. In this project, particular attention was paid to data from the KOD and SS systems, which had not previously been deglitched and instrument-corrected. We have prepared waveforms from nuclear explosions at the following five test sites: Balapan (1269 traces), Degelen (1146 traces), and Murzhik (160 traces), all in Kazakhstan on the Semipalatinsk Test site; Novaya Zemlya (461 traces) in Russia; and Lop Nor (120 traces) in China; and also from many Peaceful Nuclear Explosions (552 traces) in Russia. Although the dynamic range of specific channels is limited by the low number of bits in the recording system, the scientific content of the signals across the many different channels approaches that for modern recording systems. The improved Borovoye archive now provides masignals that modern monitoring networks (which d

Abstract : We are in the second year of a three-year project to generate in modern form an easily usable archive of digital seismograms derived from regional waveforms recorded at the Borovoye Observatory (BRV), northern Kazakhstan, over a thirty-year period going back to 1966 and spanning the time when state-of-the-art sensors and dataloggers were introduced at this site by several different western groups. The BRV seismograms, which include multichannel regional signals from 350 underground nuclear test explosions carried out in Eurasia, were made generally available to western scientists in 2001, but only as copies of the bits in the original digital waveforms. These copies contain large numbers of glitches and did not include instrument responses for approximately two-thirds of the events. In the first two years of this project, we are focusing on basic processing of the damaged waveforms to make them more easily usable by the removal of glitches and the inclusion of instrument responses (including absolute gains as well as poles and zeroes).

AbstractEarthquakes and explosions generate seismic waveforms that have different characteristics. However, the challenge of confidently differentiating between these two signatures is complex, and requires the integration of physical and statistical techniques. This article reviews the methods for constructing discrimination features from diverse physical observations. These discrimination features are appropriate for many statistical classification frameworks. Under the null hypothesis an event is an explosion, we discuss strategies for constructing P-values which can be interpreted as standardized discrimination features. We develop standardized discriminants for both teleseismic simple propagation path in the mantle and regional complicated propagation path in the crust events, following the trend toward characterizing increasingly smaller single-point explosions. Copyright © 2010 John Wiley & Sons, Inc.

There is a need to improve the understanding of the scaling and physics involved in regional recordings of epicentral infrasound from small earthquakes. This need stems from a wish to use infrasound presence and characteristics to improve depth discriminants. Current regional depth discriminants rely on recording the Rg seismic phase or intermediate period surface waves. These phases are sensitive to upper crustal structural details, but are often disrupted by horizontal changes in structure and topography. A number of studies have used single infrasound array data to argue that small earthquakes (M<4) generate infrasound signals. Wide spatial separation of infrasound arrays coupled with the time variation of atmospheric models make the association of infrasound signals from small earthquakes with seismic observations non-unique. This is because event association is often dependent on a single backazimuth estimate within a relatively wide range of arrival times. We propose to address this non-uniqueness, as well as assess smaller magnitude events, by deploying a total of six infrasound arrays in and around the Intermountain seismic belt in Utah. The University of Utah (UU) is the regional seismic network operator responsible for the location and characterization of earthquakes in the region and will integrate the six proposed infrasound arrays into the daily network operations. These arrays will provide the data needed to independently locate the infrasound sources using crossing backazimuth estimates for unique association with the seismic sources. Models of infrasound generation by earthquakes will be developed using a collection of earthquake scaling relations dependent on depth, magnitude and mechanism that are currently used for strong-ground motion assessment for earthquake hazards. Special attention to earthquake depth estimation, including synthetic modeling of seismograms and analysis of the Rg phase, will provide an assessment of both the depth estimate and its variance. The infrasound and ground motion observations made during the course of this study will be used to refine the source excitation model for infrasound using two different approaches, including the application of the Rayleigh integral. The application of this physical based approach to infrasound generation is intended to lead to a possible infrasound based depth discriminant that could be integrated into the Event Classification Matrix (ECM) (Anderson, 2007). In a related effort, preliminary analysis of infrasound from the Wells earthquake sequence is reported in Stump et al. (2009, these Proceedings), which describes the first deployment of infrasound gauges in Utah. 2009 Monitoring Research Review: Ground-Based Nuclear Explosion Monitoring Technologies

The Wells, Nevada, earthquake of February 21, 2008, generated a complex seismo‐acoustic wavefield. Epicentral infrasound was recorded at 5 seismo‐acoustic arrays in Nevada, Utah, and Wyoming. In addition to epicentral infrasound, the earthquake triggered a secondary source of infrasound at the BGU array in Utah, which was also triggered by subsequent aftershocks. By applying simple constraints on the propagation of seismic and infrasound waves, we show that the secondary source is an isolated peak (‘Floating Island’) that appears to efficiently generate infrasound through the interaction with seismic surface waves. This hypothesized source location is broadly consistent with crosswind directions extracted from the Ground‐to‐Space (G2S) atmospheric model (for the appropriate time and source/receiver locations), although modeling the propagation of infrasound predicts this source location to be within the so‐called ‘zone‐of‐silence’. In contrast to epicentral infrasound, secondary infrasound associated with the Wells, Nevada, earthquake sequence appears to be local to each array (i.e., not observed at multiple arrays). Secondary infrasonic arrivals observed at BGU are much higher in amplitude than epicentral arrivals, highlighting the importance of being able to clearly identify and separate epicentral and secondary arrivals for infrasonic event discrimination.

In ground-based nuclear explosion monitoring, the depth of an event is an important consideration for event identification. However, without a station near the epicenter, seismic depth determination of small, shallow events is difficult. A current capability for the identification of shallow sources is the presence of the seismic phase, Rg. However, Rg is often not observed seismically, as it is very sensitive to the details of the structure of the upper crust and is disrupted by horizontal changes in structure and topography. Infrasound signals can be generated by near-source pumping of the atmosphere from shallow sources. Therefore, an infrasound detection is generally an indicator of a shallow (or surface) source, and has the potential to be used as a surrogate for Rg. As a first step towards constructing an infrasonic depth discriminant, we are constructing a large dataset of shallow earthquakes and explosions with well-constrained depths and associated infrasound signals at multiple arrays. By correcting for the effects of stratospheric and thermospheric winds on infrasonic amplitudes, we are exploring a multiple linear regression approach for separating effects of depth, source mechanism, magnitude and distance (predictor variables) on observed infrasonic amplitudes (dependent variable). This empirical approach will be complemented by the development of physical models that tie with the observations. To highlight our approach, we focus on infrasonic and seismic observations from the Wells, Nevada earthquake sequence. We demonstrate the importance of separating epicentral and secondary infrasonic arrivals, and report on our preliminary findings. 2009 Monitoring Research Review: Ground-Based Nuclear Explosion Monitoring Technologies

In this paper, we present an integrated set of algorithms for the automatic detection, association, and location of low-frequency acoustic events using regional networks of infrasound arrays. Here, low-frequency acoustic events are characterized by transient signals, which may arise from a range of natural and anthropogenic sources, examples of which include (but are not limited to) earthquakes, volcanic eruptions, explosions, rockets and bolides. First, we outline a new technique for detecting infrasound signals that works successfully in the presence of correlated noise. We use an F-statistic, sequentially adapted to ambient noise conditions, in order to obtain detections at a given statistical significance while accounting for real background noise. At each array, individual arrivals are then grouped together based on measured delay-times and backazimuths. Each signal is identified as either a first or later arrival. First arrivals at spatially separated arrays are then associated using a grid-search method to form events. Preliminary event locations are calculated from the geographic means and spreads of grid nodes associated with each event. We apply the technique to regional infrasound networks in Utah and Washington State. In Utah, over a period of approximately 1 month, we obtain a total of 276 events recorded at three arrays in a geographic region of 6 x 4 degrees. For four ground-truth explosions in Utah, the automatic algorithm detects, associates, and locates the events within an average offset of 5.4 km to the actual explosion locations. In Washington State, the algorithm locates numerous events that are associated with a large coalmine in Centralia, Washington. An example mining-explosion from Centralia is located within 8.2 km of the mine. The methodology and results presented here provide an initial framework for assessing the capability of infrasound networks for regional infrasound monitoring, in particular by quantifying detection thresholds and localization errors.