Survey National Earthquake Information Center Research Articles

Noise Constraints on Global Body-Wave Measurement Thresholds

ABSTRACT Intermediate sized earthquakes (≈M4–6.5) are often measured using the teleseismic body-wave magnitude (mb). mb measurements are especially critical at the lower end of this range when teleseismic waveform modeling techniques (i.e., moment tensor analysis) are difficult. The U.S. Geological Survey National Earthquake Information Center (NEIC) determines the location and magnitude of all M 5 and greater earthquakes worldwide within 20 min of the rupture time, and therefore accurate mb magnitude estimates are essential to fulfill its mission. To better understand how network geometry and noise levels affect the global response capabilities, we developed a method to spatially estimate the minimum measurable mb. To do this, we compare expected mb amplitudes at every station to the station’s background noise level. We find that using NEIC’s current network geometry and these idealized thresholds, NEIC can potentially estimate mb magnitudes down to M 4.5 globally. Low-latitude regions in the Southern Hemisphere present the biggest opportunity to improve monitoring capabilities. However, logistically they also present the biggest hurdles for network operators. Finally, to test the resiliency of the network we removed the 20 most important stations and found the mb threshold remains mb 4.5. However, the region where only mb 4.5 and greater can be estimated increases and is again restricted to the Southern Hemisphere.

Global Characteristics of Observable Foreshocks for Large Earthquakes

AbstractForeshocks are the only currently widely identified precursory seismic behavior, yet their utility and even identifiability are problematic, in part because of extreme variation in behavior. Here, we establish some global trends that help identify the expected frequency of foreshocks as well the type of earthquake most prone to foreshocks. We establish these tendencies using the global earthquake catalog of the U.S. Geological Survey National Earthquake Information Center with a completeness level of magnitude 5 and mainshocks with Mw≥7.0. Foreshocks are identified using three clustering algorithms to address the challenge of distinguishing foreshocks from background activity. The methods give a range of 15%–43% of large mainshocks having at least one foreshock but a narrower range of 13%–26% having at least one foreshock with magnitude within two units of the mainshock magnitude. These observed global foreshock rates are similar to regional values for a completeness level of magnitude 3 using the same detection conditions. The foreshock sequences have distinctive characteristics with the global composite population b-values being lower for foreshocks than for aftershocks, an attribute that is also manifested in synthetic catalogs computed by epidemic-type aftershock sequences, which intrinsically involves only cascading processes. Focal mechanism similarity of foreshocks relative to mainshocks is more pronounced than for aftershocks. Despite these distinguishing characteristics of foreshock sequences, the conditions that promote high foreshock productivity are similar to those that promote high aftershock productivity. For instance, a modestly higher percentage of interplate mainshocks have foreshocks than intraplate mainshocks, and reverse faulting events slightly more commonly have foreshocks than normal or strike-slip-faulting mainshocks. The western circum-Pacific is prone to having slightly more foreshock activity than the eastern circum-Pacific.

MLAAPDE: A Machine Learning Dataset for Determining Global Earthquake Source Parameters

Abstract The Machine Learning Asset Aggregation of the Preliminary Determination of Epicenters (MLAAPDE) dataset is a labeled waveform archive designed to enable rapid development of machine learning (ML) models used in seismic monitoring operations. MLAAPDE consists of more than 5.1 million recordings of 120 s long three-component broadband waveform data (raw counts) for P, Pn, Pg, S, Sn, and Sg arrivals. The labeled catalog is collected from the U.S. Geological Survey National Earthquake Information Center’s (NEIC) Preliminary Determination of Epicenters bulletin, which includes local to teleseismic observations for earthquakes ∼M 2.5 and larger. Each arrival in the labeled dataset has been manually reviewed by NEIC staff. An accompanying Python module enables users to develop customized training datasets, which includes different time-series lengths, distance ranges, sampling rates, and/or phase lists. MLAAPDE is distinct from other publicly available datasets in containing local (14%), regional (36%), and teleseismic (50%) observations, in which local, regional, and teleseismic distance are 0°–3°, 3°–30°, and 30°+, respectively. A recent version of the dataset is publicly available (see Data and Resources), and user-specific versions can be generated locally with the accompanying software. MLAAPDE is an NEIC supported, curated, and periodically updated dataset that can contribute to seismological ML research and development.

Rapid Characterization of the February 2023 Kahramanmaraş, Türkiye, Earthquake Sequence

Abstract The 6 February 2023 Mw 7.8 Pazarcık and subsequent Mw 7.5 Elbistan earthquakes generated strong ground shaking that resulted in catastrophic human and economic loss across south-central Türkiye and northwest Syria. The rapid characterization of the earthquakes, including their location, size, fault geometries, and slip kinematics, is critical to estimate the impact of significant seismic events. The U.S. Geological Survey National Earthquake Information Center (NEIC) provides real-time monitoring of earthquakes globally, including rapid source characterization and impact estimates. Here, we describe the seismic characterization products generated and made available by the NEIC over the two weeks following the start of the earthquake sequence in southeast Türkiye, their evolution, and how they inform our understanding of regional seismotectonics and hazards. The kinematics of rupture for the two earthquakes was complex, involving multiple fault segments. Therefore, incorporating observations from rupture mapping was critical for characterizing these events. Dense local datasets facilitated robust source characterization and impact assessment once these observations were obtained and converted to NEIC product input formats. We discuss how we may improve the timeliness of NEIC products for rapid assessment of future seismic hazards, particularly in the case of complex ruptures.

Estimating Coseismic Deformation of Southwestern Puerto Rico from the 7 January 2020 Mw 6.4 Earthquake: Constraints from Campaign and Continuous GPS

ABSTRACT The Puerto Rico–Virgin Islands (PRVI) block lies within the Northern Caribbean Plate Boundary Zone—a zone accommodating stresses between the larger North America and Caribbean plates. Data from Global Positioning System (GPS) sites throughout the PRVI block have been used to confirm the existence of a distinct microblock in the southwest. It is no coincidence that this portion of the PRVI block is the epicentral region of the 7 January 2020 Mw 6.4 earthquake and the ensuing seismic sequence. Prior to the mainshock, the southwestern Puerto Rico (SWPR) region exhibited most of the onland seismic activity. The 2020–2021 SWPR earthquake seismic sequence has been characterized by having an atypical aftershock decay distribution occurring along multiple faults. As a result, fault parameters of the 7 January 2020 mainshock have been poorly defined by conventional seismic methods. Here, we present results from campaign and continuous GPS sites in SWPR, and compare GPS-derived displacements to those computed from the U.S. Geological Survey National Earthquake Information Center (NEIC) focal mechanism. We conclude that irrespective of which nodal plane is used, the observed coseismic displacements from GPS differ from those predicted using a simple elastic model and the NEIC focal mechanism. We infer based on these observations that the complex mainshock rupture resulted in a suboptimal double-couple solution.

Detecting and Locating Aftershocks for the 2020 Mw 6.5 Stanley, Idaho, Earthquake Using Convolutional Neural Networks

Abstract Our study is to build an aftershock catalog with a low magnitude of completeness for the 2020 Mw 6.5 Stanley, Idaho, earthquake. This is challenging because of the low signal-to-noise ratios for recorded seismograms. Therefore, we apply convolutional neural networks (CNNs) and use 2D time–frequency feature maps as inputs for aftershock detection. Another trained CNN is used to automatically pick P-wave arrival times, which are then used in both nonlinear and double-difference earthquake location algorithms. Our new one-month-long catalog has 4644 events and a completeness magnitude (Mc) 1.9, which has over seven times more events and 0.9 lower Mc than the current U.S. Geological Survey National Earthquake Information Center catalog. The distribution and expansion of these aftershocks improve the resolution of two north-northwest-trending faults with different dip angles, providing further support for a central stepover region that changed the earthquake rupture trajectory and induced sustained seismicity.

Modeling Seismic Network Detection Thresholds Using Production Picking Algorithms

Abstract Estimating the detection threshold of a seismic network (the minimum magnitude earthquake that can be reliably located) is a critical part of network design and can drive network maintenance efforts. The ability of a station to detect an earthquake is often estimated by assuming the spectral amplitude for an earthquake of a given size, assuming an attenuation relationship, and comparing the predicted amplitude with the average station background noise level. This approach has significant uncertainty because of unknown regional attenuation and complications in computing small event power spectra, and it fails to account for the specific capabilities of the automatic seismic phase picker used in monitoring. We develop a data-driven approach to determine network detection thresholds using a multiband phase picking algorithm that is currently in use at the U.S. Geological Survey National Earthquake Information Center. We apply this picking algorithm to cataloged earthquakes to determine an empirical relationship of the observability of earthquakes as a function of magnitude and distance. Using this relationship, we produce maps of detection threshold using station spatial configuration and station noise levels. We show that quiet, well-sited stations significantly increase the detection capabilities of a network compared with a network composed of many noisy stations. Because our method is data driven, it has two distinct advantages: (1) it is less dependent on theoretical assumptions of source spectra and models of regional attenuation, and (2) it can easily be applied to any seismic network. This tool allows for an objective approach to the management of stations in regional seismic networks.

Leveraging Deep Learning in Global 24/7 Real-Time Earthquake Monitoring at the National Earthquake Information Center

AbstractMachine-learning algorithms continue to show promise in their application to seismic processing. The U.S. Geological Survey National Earthquake Information Center (NEIC) is exploring the adoption of these tools to aid in simultaneous local, regional, and global real-time earthquake monitoring. As a first step, we describe a simple framework to incorporate deep-learning tools into NEIC operations. Automatic seismic arrival detections made from standard picking methods (e.g., short-term average/long-term average [STA/LTA]) are fed to trained neural network models to improve automatic seismic-arrival (pick) timing and estimate seismic-arrival phase type and source-station distances. These additional data are used to improve the capabilities of the NEIC associator. We compile a dataset of 1.3 million seismic-phase arrivals that represent a globally distributed set of source-station paths covering a range of phase types, magnitudes, and source distances. We train three separate convolutional neural network models to predict arrival time onset, phase type, and distance. We validate the performance of the trained networks on a subset of our existing dataset and further extend validation by exploring the model performance when applied to NEIC automatic pick data feeds. We show that the information provided by these models can be useful in downstream event processing, specifically in seismic-phase association, resulting in reduced false associations and improved location estimates.

Integration of coseismic deformation into WebGIS for near real-time disaster evaluation and emergency response

Earthquakes are one of the destructive natural disasters. Immediate emergency response in the first few hours is important for life rescue. The near real-time ground deformation maps generated after earthquakes are crucial for hazard assessments, which normally take a couple of hours or longer to be generated using conventional ways. In this study, we propose a near real-time coseismic ground deformation map generation system with the aim of assisting rapid seismic hazard evaluations and emergency responses. This framework adopts the source parameters published by seismological agencies and uses the empirical equations to generate the near real-time coseismic ground deformation maps. The source parameters of an earthquake, such as the focal mechanism, are programmatically accessed from the United States Geological Survey National Earthquake Information Center (USGS-NEIC) in a nearly real-time manner. The ground deformation estimated using empirical equations is integrated as self-adapting spatial data fusion and visualized on an interactive WebGIS platform. We develop the WebGIS platform, namely QuickDeform at https://www.insar.com.cn , and successfully applied the system to several recent large magnitude earthquakes. We find that the proposed framework functions robustly and proficiently to automatically generate the seismic deformation map within several minutes after the occurrence of an earthquake. The generated deformation map shows good agreement when compared to the data from real earthquakes. QuickDeform can be used as a volunteered geographic information platform for crowdsourcing disaster data for rescue and model validation.

Global Earthquake Response with Imaging Geodesy: Recent Examples from the USGS NEIC

The U.S. Geological Survey National Earthquake Information Center leads real-time efforts to provide rapid and accurate assessments of the impacts of global earthquakes, including estimates of ground shaking, ground failure, and the resulting human impacts. These efforts primarily rely on analysis of the seismic wavefield to characterize the source of the earthquake, which in turn informs a suite of disaster response products such as ShakeMap and PAGER. In recent years, the proliferation of rapidly acquired and openly available in-situ and remotely sensed geodetic observations has opened new avenues for responding to earthquakes around the world in the days following significant events. Geodetic observations, particularly from interferometric synthetic aperture radar (InSAR) and satellite optical imagery, provide a means to robustly constrain the dimensions and spatial complexity of earthquakes beyond what is typically possible with seismic observations alone. Here, we document recent cases where geodetic observations contributed important information to earthquake response efforts—from informing and validating seismically-derived source models to independently constraining earthquake impact products—and the conditions under which geodetic observations improve earthquake response products. We use examples from the 2013 Mw7.7 Baluchistan, Pakistan, 2014 Mw6.0 Napa, California, 2015 Mw7.8 Gorkha, Nepal, and 2018 Mw7.5 Palu, Indonesia earthquakes to highlight the varying ways geodetic observations have contributed to earthquake response efforts at the NEIC. We additionally provide a synopsis of the workflows implemented for geodetic earthquake response. As remote sensing geodetic observations become increasingly available and the frequency of satellite acquisitions continues to increase, operational earthquake geodetic imaging stands to make critical contributions to natural disaster response efforts around the world.

GLASS3: A Standalone Multiscale Seismic Detection Associator

Abstract The automated global real‐time association of phase picks into seismic sources comes with unique challenges when simultaneously monitoring at local, regional, and global scales. High spatial variability in seismic station density, transitory seismic data availability, and time‐varying noise characteristics of individual stations must be considered in the design of an associator that is fast and accurate with a low false association rate. These challenges are particularly apparent at the U.S. Geological Survey National Earthquake Information Center (NEIC), which monitors seismicity in near‐real time on local, regional, and global scales using seismic data from roughly 2100 real‐time seismic stations. To fully leverage this large dataset, NEIC developed a standalone self‐configuring seismic phase associator, GLobal ASSociator 3 (GLASS3) that simultaneously processes variably scaled 3D association webs, each with a unique set of nucleation criteria (e.g., nucleation stack threshold). GLASS3 has many useful features for real‐time monitoring including its computational efficiency, instantaneous pick processing, and on‐the‐fly configurability such as the creation and removal of targeted association webs and updates to supporting station metadata. GLASS3 runs both as part of a real‐time event processing system and as a configurable standalone associator that can be applied to a large variety of seismic problems. Here, we describe the GLASS3 algorithm and demonstrate (including input data and configuration files) its use in associating phase‐ambiguous picks on multiple scales.

Surface Deformation of North‐Central Oklahoma Related to the 2016Mw 5.8 Pawnee Earthquake from SAR Interferometry Time Series

ABSTRACT The 3 September 2016 M w 5.8 Pawnee earthquake shook a large area of north‐central Oklahoma and was the largest instrumentally recorded earthquake in the state. We processed Synthetic Aperture Radar (SAR) from the Copernicus Sentinel‐1A and Sentinel‐1B and Canadian RADARSAT‐2 satellites with interferometric SAR analysis for the area of north‐central Oklahoma that surrounds Pawnee. The interferograms do not show phase discontinuities that would indicate surface ruptures during the earthquake. Individual interferograms have substantial atmospheric noise caused by variations in radar propagation delays due to tropospheric water vapor, so we performed a time‐series analysis of the Sentinel‐1 stack to obtain a more accurate estimate of the ground deformation in the coseismic time interval and the time variation of deformation before and after the earthquake. The time‐series fit for a step function at the time of the Pawnee shows about 3 cm peak‐to‐peak amplitude of the coseismic surface deformation in the radar line of sight with a spatial pattern that is consistent with fault slip on a plane trending east‐southeast. This fault, which we call the Sooner Lake fault, is parallel to the west‐northwest nodal plane of the U.S. Geological Survey National Earthquake Information Center moment tensor solution. We model the fault plane by fitting hypoDD‐relocated aftershocks aligned in the same trend. Our preferred slip model on this assumed fault plane, allowing only strike‐slip motion, has no slip shallower than 2.3 km depth, an area of moderate slip extending 7 km along strike between 2.3 and 4.5 km depth (which could be due to aftershocks and afterslip), and larger slip between 4.5 and 14 km depth extending about 12 km along strike. The large slip below the 4.5 km depth of our relocated hypocenter indicates that the coseismic rupture propagated down‐dip. The time‐series results do not show significant deformation before or after the earthquake above the high atmospheric noise level within about 40 km of the earthquake rupture.

Rapid Characterization of the 2015Mw 7.8 Gorkha, Nepal, Earthquake Sequence and Its Seismotectonic Context

Earthquake response and related information products are important for placing recent seismic events into context and particularly for understanding the impact earthquakes can have on the regional community and its infrastructure. These tools are even more useful if they are available quickly, ahead of detailed information from the areas affected by such earthquakes. Here we provide an overview of the response activities and related information products generated and provided by the U.S. Geological Survey National Earthquake Information Center in association with the 2015 M 7.8 Gorkha, Nepal, earthquake. This group monitors global earthquakes 24 hrs/day and 7 days/week to provide rapid information on the location and size of recent events and to characterize the source properties, tectonic setting, and potential fatalities and economic losses associated with significant earthquakes. We present the timeline over which these products became available, discuss what they tell us about the seismotectonics of the Gorkha earthquake and its aftershocks, and examine how their information is used today, and might be used in the future, to help mitigate the impact of such natural disasters.

Rapid Seismological Quantification of Source Parameters of the 25 April 2015 Nepal Earthquake

ABSTRACT The 25 April 2015 M w 7.9 Nepal earthquake is used to explore rapid seismological quantification methods to determine point-source parameters (seismic moment, focal mechanism, radiated energy, and source duration) and rupture directivity parameters (fault length and rupture velocity). Given real-time access to global seismic data, useful results can be obtained from W -phase, energy estimation, cut-and-paste, and backprojection analyses within 20–30 min of origin time or even faster if regional data were openly available (which is not the case at present for stations in China and India). This information can augment ground-shaking prediction procedures such as ShakeMap, which is currently provided by the U.S. Geological Survey National Earthquake Information Center. For such procedures to achieve their full potential, open access to calibrated high-quality ground-motion recordings at local, regional, and global stations is critical, and this should be embraced internationally.

Rapid Estimates of the Source Time Function and Mw using Empirical Green's Function Deconvolution

The U.S. Geological Survey National Earthquake Information Center (NEIC) uses a variety of classical network‐averaged magnitudes (e.g., m b and M s) and waveform modeling procedures to determine the moment magnitude ( M w) of an earthquake from teleseismic observations. Initial magnitude estimates are often inaccurate because of poor azimuthal control (sampling of the focal sphere) and/or intrinsic limitation of each method to a specific range of event size. To provide faster and more accurate estimates of the moment magnitude, source duration, and source complexity, NEIC is exploring the use of a variation of the empirical Green’s function (EGF) deconvolution procedure. This approach uses a predicted focal mechanism derived from the Global Centroid Moment Tensor Catalog to compute teleseismic P ‐wave synthetic seismograms, which are then deconvolved from observed P and SH waveforms to determine station‐specific M w, source time function, and a network‐averaged M w. Our EGF approach is validated using broadband waveforms from 246 earthquakes in the magnitude range M w 6.0–9.1. Within approximately 13 min of earthquake origin time, our procedure using teleseismic P waves only computes an M w that lies within ±0.25 of the final W ‐phase M w in the magnitude range 6–8. Using later arriving teleseismic SH phases results in an M w that lies within ±0.12 of the W ‐phase M w. For magnitude 8 or larger earthquakes, we underestimated the moment magnitude by up to 0.8 magnitude units, primarily due to the initial P phase not containing the total seismic moment release. Long‐period phases such as the W ‐phase and surface waves that better characterize total moment release can also be incorporated in the processing.

Precise relative earthquake location using surface waves

AbstractEarthquake locations provide a fundamental tool for seismological investigations. While dense seismic networks can provide robust locations, accuracy and precision of these locations suffer outside dense networks. This is particularly true in offshore areas, where location analysis relies heavily on distant seismic observations. We present a method for estimating precise relative seismic source epicentroid locations using surface waves. Several reasons, including lower velocities and strength of the signal at distance, make use of surface waves for event location appealing. We focus on the Panama Fracture Zone region and relocate 81 strike‐slip earthquakes to produce tectonically consistent epicentroid locations. The resulting pattern of earthquakes more clearly delineates recently active regional structures than original body‐wave locations. The mean shift between the US Geological Survey National Earthquake Information Center epicenter and our epicentroids is about 14 km (the median is about 11 km), and typical origin time changes are generally less than ±2 s. We find that north of 6.5°N, the plate boundary motion is split across two roughly north‐south striking structures, the Panama and Balboa Fracture zones. For the last 36 years, slip along these two structures roughly matches slip along the Panama Fracture Zone to the south (from 4.5°N to 6.25°N), but the Balboa Fracture zone has roughly three times the moment than the northern Panama Fracture Zone. Our analyses show that observed Rayleigh‐wave signal‐to‐noise ratios for moderate‐to‐large shallow earthquakes are suitable for applying the procedure and that Rayleigh‐wave observations form a self‐consistent set of constraints on the relative location of earthquake centroids.

Finite-Fault Source Inversion Using Teleseismic P Waves: Simple Parameterization and Rapid Analysis

We examine the ability of teleseismic P waves to provide a timely image of the rupture history for large earthquakes using a simple, 2D finite‐fault source parameterization. We analyze the broadband displacement waveforms recorded for the 2010 M w∼7 Darfield (New Zealand) and El Mayor‐Cucapah (Baja California) earthquakes using a single planar fault with a fixed rake. Both of these earthquakes were observed to have complicated fault geometries following detailed source studies conducted by other investigators using various data types. Our kinematic, finite‐fault analysis of the events yields rupture models that similarly identify the principal areas of large coseismic slip along the fault. The results also indicate that the amount of stabilization required to spatially smooth the slip across the fault and minimize the seismic moment is related to the amplitudes of the observed P waveforms and can be estimated from the absolute values of the elements of the coefficient matrix. This empirical relationship persists for earthquakes of different magnitudes and is consistent with the stabilization constraint obtained from the L‐curve in Tikhonov regularization. We use the relation to estimate the smoothing parameters for the 2011 M w 7.1 East Turkey, 2012 M w 8.6 Northern Sumatra, and 2011 M w 9.0 Tohoku, Japan, earthquakes and invert the teleseismic P waves in a single step to recover timely, preliminary slip models that identify the principal source features observed in finite‐fault solutions obtained by the U.S. Geological Survey National Earthquake Information Center (USGS/NEIC) from the analysis of body‐ and surface‐wave data. These results indicate that smoothing constraints can be estimated a priori to derive a preliminary, first‐order image of the coseismic slip using teleseismic records.

88 Hours: The U.S. Geological Survey National Earthquake Information Center Response to the 11 March 2011 Mw 9.0 Tohoku Earthquake

Online material : Timeline movie 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. The NEIC operates a 24/7 service dedicated to the rapid determination of the location and size of all significant earthquakes worldwide and to the immediate dissemination of this information to concerned national and international agencies, scientists, critical facilities, and the general public. Within its 24/7 operations, the NEIC is constantly staffed by at least two geophysicists who are responsible for reviewing and reporting all magnitude 5 or larger events within 20 minutes of origin time. These analysts also field incoming calls from the …

Rapid source characterization of the 2011 M w 9.0 off the Pacific coast of Tohoku Earthquake

On March 11th, 2011, a moment magnitude 9.0 earthquake struck off the coast of northeast Honshu, Japan, generating what may well turn out to be the most costly natural disaster ever. In the hours following the event, the U.S. Geological Survey National Earthquake Information Center led a rapid response to characterize the earthquake in terms of its location, size, faulting source, shaking and slip distributions, and population exposure, in order to place the disaster in a framework necessary for timely humanitarian response. As part of this effort, fast finite-fault inversions using globally distributed body- and surface-wave data were used to estimate the slip distribution of the earthquake rupture. Models generated within 7 hours of the earthquake origin time indicated that the event ruptured a fault up to 300 km long, roughly centered on the earthquake hypocenter, and involved peak slips of 20 m or more. Updates since this preliminary solution improve the details of this inversion solution and thus our understanding of the rupture process. However, significant observations such as the up-dip nature of rupture propagation and the along-strike length of faulting did not significantly change, demonstrating the usefulness of rapid source characterization for understanding the first order characteristics of major earthquakes.

Source Inversion of the W-Phase: Real-time Implementation and Extension to Low Magnitudes

We assess the use and reliability of a source inversion of the W-phase in real-time operations at the U.S. Geological Survey National Earthquake Information Center. The three-stage inversion algorithm produces rapid and reliable estimates of moment magnitude and source mechanism for events larger than M_w 7.0 within 25 minutes of the earthquake origin time, often less, and holds great promise for vastly improving our response times to such earthquakes worldwide. The method also produces stable results (within ±0.2 units of Global Centroid Moment Tensor project estimates) for earthquakes as small as M_w 5.8 when using stations out to distances of 90°. These applications extend the use of W-phase far beyond the higher magnitude events for which the inversion was originally intended, facilitating its use as a complementary approach to traditional body- and surface-wave methods for assessing the source properties of an earthquake. Kanamori and Rivera (2008) introduced the use of W-phase as a reliable method to rapidly assess the source properties (M_w and mechanism) of earthquakes greater than ~M_w 7.5. They showed that the W-phase inversion method has important real-time applications for tsunami warning purposes (and indeed for the calculation of earthquake moment), particularly for very large earthquakes such as the 2004 Sumatra–Andaman Islands event for which traditional methods may suffer due to the clipping of seismograms and/or because they do not deliver accurate results quickly enough to be useful for tsunami warning.