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Cataloging the 1811-1812 New Madrid, central U.S., earthquake sequence

The three principal New Madrid, central U.S., mainshocks of 1811-1812 were followed by extensive aftershock sequences that included numerous felt events. Although no instrumental data are available for the sequence, historical accounts provide information that can be used to estimate magnitudes and locations for the large aftershocks as well as the mainshocks. Several detailed eyewitness accounts of the sequence provide sufficient information to identify times and rough magnitude estimates for a number of aftershocks that have not been analyzed previously. I also use three extended compilations of felt events to explore the overall sequence productivity. Although one generally cannot estimate magnitudes or locations for individual events, the intensity distributions of recent, instrumentally recorded earthquakes in the region provide a basis for estimation of the magnitude distribution of 1811-1812 aftershocks. The distribution is consistent with a b-value distribution. I estimate Mw 6-6.3 for the three largest identifiable aftershocks, apart from the so-called dawn aftershock on 16 December 1811.

Seismological Research Letters↗

Three-dimensional long-period groundmotion simulations in the upper Mississippi embayment

We employed a 3D velocity model and 3D wave propagation code to simulate long-period ground motions in the upper Mississippi embayment. This region is at risk from large earthquakes in the New Madrid seismic zone (NMSZ) and observational data are sparse, making simulation a valuable tool for predicting the effects of large events. We undertook these simulations to estimate the magnitude of shaking likely to occur and to investigate the influence of the 3D embayment structure and finite-fault mechanics on ground motions. There exist three primary fault zones in the NMSZ, each of which was likely associated with one of the main shocks of the 1811-12 earthquake triplet. For this study, three simulations have been conducted on each major segment, exploring the impact of different epicentral locations and rupture directions on ground motions. The full wave field up to a frequency of 0.5 Hz is computed on a 200 ?? 200 ?? 50-km 3 volume using a staggered-grid finite-difference code. Peak horizontal velocity and bracketed durations were calculated at the free surface. The NMSZ simulations indicate that for the considered bandwidth, finite-fault mechanics such as fault proximity, directivity effect, and slip distribution exert the most control on ground motions. The 3D geologic structure of the upper Mississippi embayment also influences ground motion with indications that amplification is induced by the sharp velocity contrast at the basin edge.

Seismological Research Letters↗

Low-altitude aerial color digital photographic survey of the San Andreas Fault

Ever since 1858, when Gaspard-Félix Tournachon (pen name Félix Nadar) took the first aerial photograph (Professional Aerial Photographers Association 2009), the scientific value and popular appeal of such pictures have been widely recognized. Indeed, Nadar patented the idea of using aerial photographs in mapmaking and surveying. Since then, aerial imagery has flourished, eventually making the leap to space and to wavelengths outside the visible range. Yet until recently, the availability of such surveys has been limited to technical organizations with significant resources. Geolocation required extensive time and equipment, and distribution was costly and slow. While these situations still plague older surveys, modern digital photography and lidar systems acquire well-calibrated and easily shared imagery, although expensive, platform-specific software is sometimes still needed to manage and analyze the data. With current consumer-level electronics (cameras and computers) and broadband internet access, acquisition and distribution of large imaging data sets are now possible for virtually anyone. In this paper we demonstrate a simple, low-cost means of obtaining useful aerial imagery by reporting two new, high-resolution, low-cost, color digital photographic surveys of selected portions of the San Andreas fault in California. All pictures are in standard jpeg format. The first set of imagery covers a 92-km-long section of the fault in Kern and San Luis Obispo counties and includes the entire Carrizo Plain. The second covers the region from Lake of the Woods to Cajon Pass in Kern, Los Angeles, and San Bernardino counties (151 km) and includes Lone Pine Canyon soon after the ground was largely denuded by the Sheep Fire of October 2009. The first survey produced a total of 1,454 oblique digital photographs (4,288 x 2,848 pixels, average 6 Mb each) and the second produced 3,762 nadir images from an elevation of approximately 150 m above ground level (AGL) on the southeast leg and 300 m AGL on the northwest leg. Spatial resolution (pixel size or ground sample distance) is a few centimeters. Time and geographic coordinates of the aircraft were automatically written into the exchangeable image file format (EXIF) data within each jpeg photograph. A few hours after acquisition and validation, the photographs were uploaded to a publicly accessible Web page. The goal was to obtain quick-turnaround, low-cost, high-resolution, overlapping, and contiguous imagery for use in planning field operations, and to provide imagery for a wide variety of land use and educational studies. This work was carried out in support of ongoing geological research on the San Andreas fault, but the technique is widely applicable beyond geology.

California↗

Displaying seismic deaggregation: The importance of the various sources

Seismic hazard deaggregation has become a standard part of probabilistic seismic hazard assessment (PSHA). The first product of PSHA is calculation of the likely severity of ground motion at a given range of annual probability levels, and this is extremely important for seismic design of structures to be built at the site under examination. However, for full analysis of proposed structural designs, engineers also need to examine scenario events to produce detailed time histories. To select such scenarios, a deaggregation of the hazard is performed, whereby the details of sources that contribute to the annual frequency of exceeding specified levels of ground motion, or P exc , are identified. A common format for such a deaggregation is shown in Figure 1 . This relates to the 475-year peak ground acceleration (pga) at Wellington, New Zealand (41.28°S 174.77°E), and shows the distribution in magnitude and distance of sources that contribute to P exc . Return period is approximately the reciprocal of P exc . Stiff soil site conditions ( Standards New Zealand 2004 ) were assumed. The analysis in Figure 1 used the interim version of the updated seismic hazard model for New Zealand ( Stirling et al. 2007 ), with the attenuation function developed by McVerry et al. (2007). Based on a Poisson time dependence model, a return period of 475 years corresponds to a 10% probability of exceedance in 50 years. From Figure 1 , it is apparent that for this site the main contribution to ground motion of this severity is from earthquakes of magnitude about 7.6 less than 10 km from the site (blue), and there is another strong contribution from larger events in the distance range 10 to 20 km (red). These correspond to the Wellington and Wairarapa faults, respectively (see Table 1 ). There are other events less than 10 km from the site and small contributions from other sources. At this site the major contributions are from specific faults nearby, which are readily identified. At sites where there is significant background seismicity, however, the plot will be much more complicated and not so easy to interpret. Figure 1 deaggregates probabilistic pga at the site; other parameters are also commonly deaggregated in the same way, in particular response spectral acceleration at a variety of natural periods. But the figure has a major shortcoming in that it represents only one return period; to obtain a full appreciation of the various contributing sources it is necessary to perform a succession of analyses to cover the full range of return periods.

Seismological Research Letters↗

Field survey of the Samoa tsunami of 29 September 2009

On 29 September 2009, a strong earthquake took place south of the Samoa Islands in the southcentral Pacific. It triggered a local tsunami, which caused considerable damage and 189 fatalities on the Samoa Islands and in the northern Tonga archipelago. We present here the results of a tsunami survey conducted by an International Tsunami Survey Team in the Samoa Islands on 4-10 October 2009 and in northern Tonga on 25–27 November 2009.

Manono, Manu'a Islands, Motu O Manu, Niuafo'ou, Ni↗

Temporal variations in Global Seismic Stations ambient noise power levels

Recent concerns about time-dependent response changes in broadband seismometers have motivated the need for methods to monitor sensor health at Global Seismographic Network (GSN) stations. We present two new methods for monitoring temporal changes in data quality and instrument response transfer functions that are independent of Earth seismic velocity and attenuation models by comparing power levels against different baseline values. Our methods can resolve changes in both horizontal and vertical components in a broad range of periods (∼0.05 to 1,000 seconds) in near real time. In this report, we compare our methods with existing techniques and demonstrate how to resolve instrument response changes in long-period data (>100 seconds) as well as in the microseism bands (5 to 20 seconds). High quality broadband data recorded by the GSN are fundamental to characterizing a wide range of Earth science issues including: the size and rupture of large earthquakes ( e.g. , Tsai et al. 2005 ); imaging the interior of the Earth ( e.g. , Van der Hilst et al. 1997 ); tracking global climate variation ( Aster et al. 2008 ); and monitoring calving glaciers (Ekström et al. 2003 , 2006a ). Recent studies based on theoretical Earth models ( Ekström et al. 2006b ; Davis and Berger 2007 ) suggest that broadband seismometer gain levels can vary with time. This has also been confirmed, for the STS-1 sensor, experimentally ( Yuki and Ishihara 2002 ). It therefore has become necessary to systematically check for temporal changes in amplitude at GSN stations. Many of these changes are frequency-dependent in nature and not a priori predictable ( Ekström et al. 2006b ). Robust methods that can be applied to a large number of stations in a broad range of frequency bands are necessary.

Seismological Research Letters↗

Method for calculating self-noise spectra and operating ranges for seismographic inertial sensors and recorders

Understanding the performance of sensors and recorders is prerequisite to making appropriate use of them in seismology and earthquake engineering. This paper explores a critical aspect of instrument performance, the “self” noise level of the device and the amplitude range it can usefully record. Self noise limits the smallest signals, while instrument clipping level creates the upper limit (above which it either cannot produce signals or becomes unacceptably nonlinear). Where these levels fall, and the “operating range” between them, determines much of the instrument's viability and the applications for which it is appropriate. The representation of seismic-instrument self-noise levels and their effective operating ranges (cf., dynamic range) for seismological inertial sensors, recorders (data acquisition units, or DAUs), and integrated systems of sensors and recorders (data acquisition systems, or DASs) forces one to address an unnatural comparison between transient finite-bandwidth signals, such as earthquake records, and the instrument's self noise, an effectively stationary signal of infinite duration. In addition to being transient, earthquakes and other records of interest are characterized by a peak amplitude and generally a narrow, peaked spectral shape. Unfortunately, any power spectrum computed for such transient signals is ill defined, since the maximum of that spectrum depends strongly upon signal and record durations. In contrast, the noise floor of an instrument is approximately stationary and properly described by a power spectral density (PSD) or its root (rPSD). Put another way, earthquake records have units of amplitude ( e.g. , m/s 2 ) while PSDs have units of amplitude-squared per hertz ( e.g. , (m/s 2 ) 2 /Hz) and the rPSD has units of amplitude per root of hertz ( e.g. , (m/s 2 )/Hz 1/2 ). Thus, this incompatability is a conflict between earthquake (amplitude) and PSD (spectral density) units that requires one to make various assumptions before they can be compared. For purposes of instrument operational performance, we provide a means of evaluating signal and noise and the range between them in a manner representative of time-domain instrument performance. We call these “operating range diagrams” (ORDs), plots of instrument self noise and clipping level; the “operating range” is the range between these values. For frequency-domain performance we elect to show self noise as an rPSD that may be compared to another instrument's noise or to ambient Earth noise ( e.g. , Peterson 1993); however, to limit the number of arbitrary choices required to merge transient and stationary signals we do not compare the rPSD to transient signals in the frequency domain. Our solution for a time-domain comparison is not new but rather builds upon the consensus of the first and second Guidelines for Seismometer Testing workshops (Hutt et al. 2009) and long established practice in acoustics. We propose this method as a standard for characterizing seismic instruments, and it has been endorsed by the second workshop (Hutt et al. 2009, 2010) and the Advanced National Seismic System (ANSS) Working Group (2008) and recent ANSS procurement specifications.

Seismological Research Letters↗

8 March 2010 Elazığ-Kovancilar (Turkey) Earthquake: observations on ground motions and building damage

An earthquake of M W = 6.1 occurred in the Elazığ region of eastern Turkey on 8 March 2010 at 02:32:34 UTC. The United States Geological Survey (USGS) reported the epicenter of the earthquake as 38.873°N-39.981°E with a focal depth of 12 km. Forty-two people lost their lives and 137 were injured during the event. The earthquake was reported to be on the left-lateral strike-slip east Anatolian fault (EAF), which is one of the two major active fault systems in Turkey. Teams from the Earthquake Engineering Research Center of the Middle East Technical University (EERC-METU) visited the earthquake area in the aftermath of the mainshock. Their reconnaissance observations were combined with interpretations of recorded ground motions for completeness. This article summarizes observations on building and ground damage in the area and provides a discussion of the recorded motions. No significant observations in terms of geotechnical engineering were made.

Seismological Research Letters↗

88 hours: The U.S. Geological Survey National Earthquake Information Center response to the March 11, 2011 Mw 9.0 Tohoku earthquake

The M 9.0 11 March 2011 Tohoku, Japan, earthquake and associated tsunami near the east coast of the island of Honshu caused tens of thousands of deaths and potentially over one trillion dollars in damage, resulting in one of the worst natural disasters ever recorded. The U.S. Geological Survey National Earthquake Information Center (USGS NEIC), through its responsibility to respond to all significant global earthquakes as part of the National Earthquake Hazards Reduction Program, quickly produced and distributed a suite of earthquake information products to inform emergency responders, the public, the media, and the academic community of the earthquake's potential impact and to provide scientific background for the interpretation of the event's tectonic context and potential for future hazard. Here we present a timeline of the NEIC response to this devastating earthquake in the context of rapidly evolving information emanating from the global earthquake-response community. The timeline includes both internal and publicly distributed products, the relative timing of which highlights the inherent tradeoffs between the requirement to provide timely alerts and the necessity for accurate, authoritative information. The timeline also documents the iterative and evolutionary nature of the standard products produced by the NEIC and includes a behind-the-scenes look at the decisions, data, and analysis tools that drive our rapid product distribution.

Tohoku↗

Developing seismogenic source models based on geologic fault data

Calculating seismic hazard usually requires input that includes seismicity associated with known faults, historical earthquake catalogs, geodesy, and models of ground shaking. This paper will address the input generally derived from geologic studies that augment the short historical catalog to predict ground shaking at time scales of tens, hundreds, or thousands of years (e.g., SSHAC 1997). A seismogenic source model, terminology we adopt here for a fault source model, includes explicit three-dimensional faults deemed capable of generating ground motions of engineering significance within a specified time frame of interest. In tectonically active regions of the world, such as near plate boundaries, multiple seismic cycles span a few hundred to a few thousand years. In contrast, in less active regions hundreds of kilometers from the nearest plate boundary, seismic cycles generally are thousands to tens of thousands of years long. Therefore, one should include sources having both longer recurrence intervals and possibly older times of most recent rupture in less active regions of the world rather than restricting the model to include only Holocene faults (i.e., those with evidence of large-magnitude earthquakes in the past 11,500 years) as is the practice in tectonically active regions with high deformation rates. During the past 15 years, our institutions independently developed databases to characterize seismogenic sources based on geologic data at a national scale. Our goal here is to compare the content of these two publicly available seismogenic source models compiled for the primary purpose of supporting seismic hazard calculations by the Istituto Nazionale di Geofisica e Vulcanologia (INGV) and the U.S. Geological Survey (USGS); hereinafter we refer to the two seismogenic source models as INGV and USGS, respectively. This comparison is timely because new initiatives are emerging to characterize seismogenic sources at the continental scale (e.g., SHARE in the Euro-Mediterranean, http://www.share-eu.org/; EMME in the Middle East, http://www.emme-gem.org/) and global scale (e.g., GEM, http://www.globalquakemodel.org/; Anonymous 2008). To some extent, each of these efforts is still trying to resolve the level of optimal detail required for this type of compilation. The comparison we provide defines a common standard for consideration by the international community for future regional and global seismogenic source models by identifying the necessary parameters that capture the essence of geological fault data in order to characterize seismogenic sources. In addition, we inform potential users of differences in our usage of common geological/seismological terms to avoid inappropriate use of the data in our models and provide guidance to convert the data from one model to the other (for detailed instructions, see the electronic supplement to this article). Applying our recommendations will permit probabilistic seismic hazard assessment codes to run seamlessly using either seismogenic source input. The USGS and INGV database schema compare well at a first-level inspection. Both databases contain a set of fields representing generalized fault three-dimensional geometry and additional fields that capture the essence of past earthquake occurrences. Nevertheless, there are important differences. When we further analyze supposedly comparable fields, many are defined differently. These differences would cause anomalous results in hazard prediction if one assumes the values are similarly defined. The data, however, can be made fully compatible using simple transformations.

Seismological Research Letters↗

Some possible causes of and corrections for STS-1 response changes in the Global Seismographic Network

The Global Seismographic Network (GSN) (Figure 1) plays a key role in providing seismic data for global earthquake monitoring ( e.g. , Benz et al. 2005), earthquake science ( e.g. , Tsai et al. 2005), and studies of Earth structure ( e.g. , Dalton et al. 2008). One of the key GSN design goals is to "provide high fidelity digital recordings of all teleseismic ground motions (adequate to resolve at or near ambient noise up to the largest teleseismic signals over the bandwidth from free oscillations (10 -4 Hz) to teleseismic body waves (up to approximately 15 Hz))" (GSN ad hoc Design Goals Subcommittee 2002). To help meet this goal, Streckeisen STS-1 seismometers were deployed at 80 GSN stations. Some of the GSN sensors have been deployed for more than 25 years. Several recent studies (Davis et al. 2005; Ekström et al. 2006; Davis and Berger 2007) have examined the question of overall calibration of the GSN. Ekström et al. (2006) indicated that a number of sites showed anomalous responses and suggested a gradual decay in the sensitivity. We have investigated the anomalous responses at several GSN sites. At least some of the problems observed by Ekström et al. (2006) may be attributed to humid air leaking into the feedback electronics of the STS-1 seismometers, which produces lower than normal sensitivities near the long-period corner of the instrument (360 seconds period). It appears that even though the feedback electronics boxes are designed to be sealed, water vapor can penetrate their interior after they have been exposed to highly humid seismometer vault air for extended periods. Highly humid air was also found to be present inside some STS-1 bell-jars (especially horizontal instruments) after loss of vacuum, resulting in corrosion and leakage between electrical conductors in connectors.

Seismological Research Letters↗

What is that mysterious booming sound?

The residents of coastal North Carolina are occasionally treated to sequences of booming sounds of unknown origin. The sounds are often energetic enough to rattle windows and doors. A recent sequence occurred in early January 2011 during clear weather with no evidence of local thunder storms. Queries by a local reporter (Colin Hackman of the NBC affiliate WETC in Wilmington, North Carolina, personal communication 2011) seemed to eliminate common anthropogenic sources such as sonic booms or quarry blasts. So the commonly asked question, “What's making these booming sounds?” remained (and remains) unanswered.

Seismological Research Letters↗

Verifying a computational method for predicting extreme ground motion

In situations where seismological data is rare or nonexistent, computer simulations may be used to predict ground motions caused by future earthquakes. This is particularly practical in the case of extreme ground motions, where engineers of special buildings may need to design for an event that has not been historically observed but which may occur in the far-distant future. Once the simulations have been performed, however, they still need to be tested. The SCEC-USGS dynamic rupture code verification exercise provides a testing mechanism for simulations that involve spontaneous earthquake rupture. We have performed this examination for the specific computer code that was used to predict maximum possible ground motion near Yucca Mountain. Our SCEC-USGS group exercises have demonstrated that the specific computer code that was used for the Yucca Mountain simulations produces similar results to those produced by other computer codes when tackling the same science problem. We also found that the 3D ground motion simulations produced smaller ground motions than the 2D simulations.

Seismological Research Letters↗