Estimation Of Source Parameters Research Articles

Surface displacements, deformations and gravity changes due to underground heat source

Abstract Thermo-elastic strains and stresses play a considerable role in the stress state of the lithosphere and its dynamics, especially at pronounced positive geothermal anomalies. Topography has a significant effect on ground deformation. Two methods for including the topographic effects in the thermo-viscoelastic model are described. First we use an approximate methodology which assumes that the main effect of topography is due to the distance from the source to the free surface and permits to have an analytical solution very attractive for solving the inverse problem. A numerical solution (for 2D plain strain case) is also computed using finite element method (FEM). The numerical method allows to include the local shape of the topography in the modeling. In the numerical model the buried magmatic body is represented by a finite volume thermal source. The temperature distribution is computed by the higher-degree FEM. For analytical as well as numerical model solution only the forces of thermal origin are considered. The results show that for the volcanic areas with prominent topography, its effect on the perturbation of the thermo-viscoelastic solution (deformation and total gravity anomaly) can be quite significant. In consequence, neglecting the topography could give erroneous results in the estimated source parameters.

The 1952 Kern County, California earthquake: A case study of issues in the analysis of historical intensity data for estimation of source parameters

Seismic intensity data based on first-hand accounts of shaking give valuable insight into historical and early instrumental earthquakes. Comparing an observed intensity distribution to intensity-prediction models based on modern calibration events allows the magnitude to be estimated for many historic earthquakes. Magnitude estimates can also potentially be refined for earthquakes for which limited instrumental data are available. However, the complicated nature of macroseismic data and the methods used to collect and interpret the data introduce significant uncertainties. In this paper, we illustrate these challenges and possible solutions using the 1952 Kern County, California, earthquake as a case study. Published estimates of its magnitude vary from MW 7.2–7.5, making it possibly the second largest in California during the 20th century. We considered over 1100 first-hand reports of shaking, supplemented with other data, and inferred the magnitude in several ways using intensity prediction equations, yielding a preferred intensity magnitude MI 7.2 ± 0.2, where the uncertainty reflects our judgement. The revised intensity distribution reveals stronger shaking on the hanging wall, south of the surface expression of the White Wolf fault, than on the footwall. Characterizing the magnitude and shaking distribution of this early instrumental earthquake can help improve estimation of the seismic hazard of the region. Such reinterpreted intensities for historic earthquakes, combined with U.S. Geological Survey (USGS) Did You Feel It? data for more recent events, can be used to produce a uniform shaking dataset with which earthquake hazard map performance can be assessed.

The 2011 Sikkim earthquake ([formula omitted] 6.9) of the Himalaya: Estimates of earthquake source parameters and representability of attenuation characteristics

The empirical accelerograms of the September 18, 2011, Sikkim earthquake (MW=6.9) have been used in the present study to estimate its source parameters and to identify a representative relation for the attenuation of peak ground acceleration with distance. The spectra of high energy packets observed in the SH waves (approximated by transverse components of accelerograms) has been modeled using Brune’s model. A two-step procedure has been adopted for this purpose. The estimated source parameters of the 2011 Sikkim earthquake have been found to be as - corner frequency (fc): 0.09 Hz, seismic moment (M0): (2.43 ± 0.5) × 1026 dyne-cm, stress drop (Δσ): 50.4 ± 9.28 bars, and the moment magnitude (MW): 6.87 ± 0.05. These estimated values have been found to be consistent with those of reported values obtained using different data sets and procedures. The high-frequency earthquake ground motions are governed by stress drop at the source. Therefore a value of stress drop estimated here is useful for the simulation of earthquake strong ground motions in the region. The attenuation characteristics of observed peak ground acceleration as a function of distance have been compared with those of obtained using five empirical relations. It has been found that a relation given by McGuire (1978) represents the attenuation characteristics of peak ground acceleration is relatively better. This relation may be used for estimating the peak ground acceleration of similar magnitude for future earthquakes in the region. This relation is also useful for the simulation of earthquake strong ground motions in the region using envelope technique. The outcome of the present study is useful for the estimation of the seismic hazard of the Sikkim region of the Himalaya.

Computational source term estimation of the Gaussian puff dispersion

The hazardous or toxic chemical releases have a detrimental impact on public safety. Estimating source parameters is of particular importance in aiding emergency response and post-assessment. Source term estimation from sensor measurements with a given Gaussian puff dispersion model is a typical inverse problem, which can be transformed into an optimization problem. In this paper, we employed the particle swarm optimization, the Nelder–Mead method, and their hybrid method to solve the optimization problem. Furthermore, we proposed a three-dimensional neighborhood topology which considerably improves performance of the particle swarm optimization. We implemented all these algorithms in JAVA on an embedded system to make a preliminary estimation of the accidental puff release. Numerical experiments with synthetic datasets show that the particle swarm optimization maintains a balance between computation time, accuracy, robustness, and implementation complexity. In contrast, the hybrid algorithm has an advantage in computation time at the expense of more sophisticated implementation.

Source Detection and Bearing Estimation Using Sparse Antenna Arrays

The capabilities of unequally spaced sparse linear antenna arrays for solving the source detection and parameter estimation problems are studied. A novel detection and estimation probability (DEP) characteristic for a qualitative description of the capabilities of a sparse antenna array is proposed and a technique for its computation is given. The problem of finding the maximum length of a sparse array with a fixed number N of elements, for which the acceptable characteristics of the signal source detection are preserved, is considered. It is shown that the DEP with a slight increase in the signal-to-noise ratio (SNR) remains the same as for the standard N-element antenna array with a half wavelength spacing, but the accuracy of bearing estimation increases proportionally to the size of the array. For example, the DEP is retained when the array length is increased more than one hundred times and the SNR is increased by 1–2 dB.

Inversion of Surface Deformation Data for Rapid Estimates of Source Parameters and Uncertainties: A Bayesian Approach

AbstractNew satellite missions (e.g., the European Space Agency's Sentinel‐1 constellation), advances in data downlinking, and rapid product generation now provide us with the ability to access space‐geodetic data within hours of their acquisition. To truly take advantage of this opportunity, we need to be able to interpret geodetic data in a prompt and robust manner. Here we present a Bayesian approach for the inversion of multiple geodetic data sets that allows a rapid characterization of posterior probability density functions (PDFs) of source model parameters. The inversion algorithm efficiently samples posterior PDFs through a Markov chain Monte Carlo method, incorporating the Metropolis‐Hastings algorithm, with automatic step size selection. We apply our approach to synthetic geodetic data simulating deformation of magmatic origin and demonstrate its ability to retrieve known source parameters. We also apply the inversion algorithm to interferometric synthetic aperture radar data measuring co‐seismic displacements for a thrust‐faulting earthquake (2015 Mw 6.4 Pishan earthquake, China) and retrieve optimal source parameters and associated uncertainties. Given its robustness and rapidity in estimating deformation source parameters and uncertainties, our Bayesian framework is capable of taking advantage of real‐time geodetic measurements. Thus, our approach can be applied to geodetic data to study magmatic, tectonic, and other geophysical processes, especially in rapid‐response operational settings (e.g., volcano observatories). Our algorithm is fully implemented in a MATLAB®‐based software package (Geodetic Bayesian Inversion Software) that we make freely available to the scientific community.

Mass Eruption Rates of Tephra Plumes During the 2011–2015 Lava Fountain Paroxysms at Mt. Etna From Doppler Radar Retrievals

Real-time estimation of eruptive source parameters during explosive volcanic eruptions is a major challenge in terms of hazard evaluation and risk assessment as these inputs are essential for tephra dispersal models to forecast the impact of ash plumes and tephra deposits. In this aim, taking advantage of the 23.5 cm wavelength Doppler radar (VOLDORAD 2B) monitoring Etna volcano, we analyzed 47 paroxysms produced between 2011 and 2015, characterized by lava fountains generating tephra plumes that reached up to 15 km a.s.l. Range gating of the radar beam allows the identification of the active summit craters in real-time, no matter the meteorological conditions. The radar echoes help to mark (i) the onset of the paroxysm when unstable lava fountains, taking over Strombolian activity, continuously supply the developing tephra plume, then (ii) the transition to stable fountains (climax), and (iii) the end of the climax, therefore providing paroxysm durations. We developed a new methodology to retrieve in real-time a Mass Eruption Rate (MER) proxy from the radar echo power and maximum Doppler velocity measured near the emission source. The increase in MER proxies is found to precede by several minutes the time variations of plume heights inferred from visible and X-Band radar imagery. A calibration of the MER proxy against ascent models based on observed plume heights leads to radar-derived climax MER from 2.96 × 104 to 3.26 × 106 kg s−1. The Total Erupted Mass (TEM) of tephra was computed by integrating over beam volumes and paroxysm duration, allowing quantitative comparisons of the relative amounts of emitted tephra among the different paroxysms. When the climactic phase can be identified, it is found to frequently release 76% of the TEM. Calibrated TEMs are found to be larger than those retrieved by satellite and X-band radar observations, deposit analyses, ground-based infrared imagery, or dispersion modeling. Our methodology, potentially applicable to every Doppler radar, provides mass load parameters that represent a powerful all-weather tool for the quantitative monitoring and real-time hazard assessment of tephra plumes at Etna or any other volcano with radar monitoring.

Determination of source, path and site parameters based on non-linear inversion of accelerometric data in Greece

Source, propagation path and site conditions are the factors affecting seismic ground motion. Consequently, recordings acquired at a seismic station are formed by the convolution of these three factors. In this work S-wave acceleration Fourier spectra of earthquakes recorded at local and regional scale, by the ITSAK accelerometric network for the period 2010–2016, are modeled as a product of source, propagation path (including geometric and anelastic attenuation) and site effects. The data set consists of 136 crustal earthquakes occurred in the broader Aegean area, with magnitudes 4.2 ≤ Mw ≤ 6.5 and epicentral distances 20 km ≤ R ≤ 350 km, recorded at 112 broadband accelerometric stations installed at sites with various geologic conditions. Based on this data set, an iterative Gauss–Newton inversion method to solve the non-linear problem and retrieve the different terms of source, propagation path and site, is applied. This method uses an initial input model trying to find the best and at the same time a stable solution for the inverted parameters, which are, moment magnitude (Mw), corner frequency (fc), attenuation quality factor (Qs = Qofα), slope of the geometric attenuation (1/Rγ) and site transfer function (S(f)). The initial values of the starting model can be either known from other studies or inferred within a reasonable range. Depending on the level of knowledge on these input parameters, the associated standard deviation can be adjusted (large values for unknown parameters or small values for parameters which are well constrained). Results of the analyses exhibit satisfactory agreement of estimated source parameters with those proposed by seismological centers in Greece and propagation path properties similar to the ones determined in relevant previous studies for the same region. In addition, the site transfer functions obtained by the non-linear inversion are comparable with those calculated for the same sites using either standard spectral ratio or horizontal-to-vertical spectral ration (HVSR—receiver function) techniques. The aforementioned results are encouraging for reliable earthquake source parameters, propagation path properties and site effect assessment, in areas of intermediate to high seismicity.

The Seismic Network of Chile

Research Article| February 14, 2018 The Seismic Network of Chile S. Barrientos; S. Barrientos aFacultad de Ciencias Físicas y Matemáticas, Universidad de Chile, Beauchef 850, Santiago, Chile, sbarrien@csn.uchile.cl Search for other works by this author on: GSW Google Scholar National Seismological Center (CSN) Team National Seismological Center (CSN) Team Search for other works by this author on: GSW Google Scholar Author and Article Information S. Barrientos aFacultad de Ciencias Físicas y Matemáticas, Universidad de Chile, Beauchef 850, Santiago, Chile, sbarrien@csn.uchile.cl National Seismological Center (CSN) Team Publisher: Seismological Society of America First Online: 14 Feb 2018 Online Issn: 1938-2057 Print Issn: 0895-0695 © Seismological Society of America Seismological Research Letters (2018) 89 (2A): 467–474. https://doi.org/10.1785/0220160195 Article history First Online: 14 Feb 2018 Cite View This Citation Add to Citation Manager Share Icon Share Facebook Twitter LinkedIn MailTo Tools Icon Tools Get Permissions Search Site Citation S. Barrientos, National Seismological Center (CSN) Team; The Seismic Network of Chile. Seismological Research Letters 2018;; 89 (2A): 467–474. doi: https://doi.org/10.1785/0220160195 Download citation file: Ris (Zotero) Refmanager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentBy SocietySeismological Research Letters Search Advanced Search ABSTRACT Chile is frequently affected by large and potentially tsunamigenic and damaging earthquakes as a result of rapid convergence of the Nazca plate beneath the South America plate. Ten M 8 or larger earthquakes have occurred along the Chilean coast in the past century, the largest of which was the 1960 M 9.5 Valdivia earthquake. After the 2010 M 8.8 Maule earthquake, Chile began installing a modern real‐time network of digital broadband/strong‐motion and Global Positioning System (GPS) stations to better prepare for future and expected large damaging earthquakes. The network was designed to provide fast and accurate estimates of earthquake source parameters of potentially devastating earthquakes for emergency response applications, and was also capable of comprehensive characterization of Chilean seismicity necessary for long‐term hazard assessment and mitigation activities. Beginning in 2013, the National Seismological Center (CSN) of the University of Chile was mandated by the Chilean government to implement a network of 65 permanent real‐time broadband and strong‐motion stations and 130 Global Navigation Satellite Systems (GNSS) monuments and receivers. These integrated sensor systems were designed to provide accurate automatic earthquake locations and magnitudes necessary for tsunami warning and impact assessment. In near‐real‐time applications, the GPS stations become critical for determination of fault finiteness of M∼7 or larger earthquakes. Operations of these systems also provide new insights into long‐term deformation and associated spatiotemporal variations in seismicity, which are necessary in long‐term earthquake hazards assessment and mitigation. In addition to the real‐time system described above, 297 strong‐motion offline instruments complement the network for engineering purposes. Broadband data in real time are publicly available through the Incorporated Research Institutions for Seismology Data Management Center (IRIS‐DMC) under networks C and C1. Strong‐motion data for recorded accelerations larger than 2%g are available through the CSN webpage. You do not have access to this content, please speak to your institutional administrator if you feel you should have access.

Determination of site effect and anelastic attenuation at Kathmandu, Nepal Himalaya region and its use in estimation of source parameters of 25 April 2015 Nepal earthquake Mw = 7.8 and its aftershocks including the 12 May 2015 Mw = 7.3 event

The destructive Mw = 7.8 Nepal earthquake happened in Nepal Himalaya, 80 km NW of Kathmandu city on 25 April 2015. A number of aftershocks in which one of them is Mw = 7.3 which occurred on 12 May 2015 are observed around the Kathmandu city of Nepal. In this paper, strong motion data of Nepal earthquake and its eight aftershocks having magnitude range 5.3–7.3, recorded at Kathmandu station is used to determine site effects and attenuation factor. Kathmandu city, capital of Nepal, is situated in a valley which consists of sediments of more than 300 m depth. Hence strong motion data recorded at Kathmandu station is strongly affected by site effect and anelastic attenuation. In this work, S-phase spectra recorded at Kathmandu station are corrected for site effect and anelastic attenuation to compute the source parameters of the events. The site effects and anelastic attenuation are estimated from inversion of strong motion data by using the inversion technique suggested by Joshi (Bull Seismol Soc Am 96:2165–2180, 2006a). The shear wave quality factor (Q β (f)) is computed at Kathmandu station by using the inversion scheme as Q β (f) = 68f0.58. The site effects and attenuation factor obtained by inversion technique are used to correct the spectrum for site effect and anelastic attenuation. The corrected source spectrum is compared with theoretical (Brune in J Geophys Res 78:4997–5009, 1970) spectrum to estimate various source parameters. Both horizontal component (North–South and East–West) are utilized to estimate the source parameters of 25 April 2015 Mw = 7.8 Nepal earthquake and its aftershocks. The best-fit theoretical spectrum provides final values of source parameters, i.e., stress drop, seismic moment, and source radius as 48.7 bars, 5.96 × 1027 dyne cm and 37.75 km, respectively, for the 25 April 2015 Mw = 7.8 earthquake and 1.40 × 1027 dyne cm, 44.7 bars, and 23.90 km, respectively, for the 12 May 2015 Mw = 7.3 earthquake.

Real-time 3-D space numerical shake prediction for earthquake early warning

In earthquake early warning systems, real-time shake prediction through wave propagation simulation is a promising approach. Compared with traditional methods, it does not suffer from the inaccurate estimation of source parameters. For computation efficiency, wave direction is assumed to propagate on the 2-D surface of the earth in these methods. In fact, since the seismic wave propagates in the 3-D sphere of the earth, the 2-D space modeling of wave direction results in inaccurate wave estimation. In this paper, we propose a 3-D space numerical shake prediction method, which simulates the wave propagation in 3-D space using radiative transfer theory, and incorporate data assimilation technique to estimate the distribution of wave energy. 2011 Tohoku earthquake is studied as an example to show the validity of the proposed model. 2-D space model and 3-D space model are compared in this article, and the prediction results show that numerical shake prediction based on 3-D space model can estimate the real-time ground motion precisely, and overprediction is alleviated when using 3-D space model.

Theoretical Solution and Applications of Ocean Bottom Pressure Induced by Seismic Seafloor Motion

AbstractSeismic signals captured by ocean bottom pressure sensors, which are designed to record tsunami waves, are largely ignored. In this paper, we derive a simple theoretical solution of the ocean bottom pressure as a function of prescribed seafloor motion. All the assumptions are clearly stated and analyzed. The solution is checked by comparing the seafloor displacement and pressure from three M7+ earthquakes, recorded by ocean bottom seismometers and pressure gauges located off the Japanese coast. We then show two applications. First, using the seafloor displacement data recorded by an ocean bottom seismometer, the pressure amplitude recorded by the associated pressure gauge is corrected, and vice versa. Second, pressure recordings from Deep Ocean Assessment and Reporting of Tsunamis during the 2011 Tohoku earthquake are converted to seafloor displacements, which are then utilized to estimate the earthquake focal mechanism. Thus, we demonstrate that seismic signals recorded by pressure sensors have great potential for fast estimate of earthquake source parameters.

Episodic inflation and complex surface deformation of Akutan volcano, Alaska revealed from GPS time-series

Akutan is one of the most active volcanoes in the Aleutian island arc. Studies involving seismic, GPS, and InSAR data have observed activity and deformation on the island since 1996. In this study we inverted measurements of volcanic deformation, observed using three components of motions at 12 continuous GPS sites to define magma source parameters using Mogi point source, Okada dislocation, and Yang spheroid and ellipsoid models. In order to analyze the evolution of this magma source we split the GPS data into five consecutive time periods, and one period that incorporates all available data. These time periods were designed around two inflation events in 2008 and 2014, when a sudden and significant increase in vertical velocity was observed. Inversion of these time periods independently allowed us to create a magma volume time-series that is related to the physical migration of magma defined by the estimated source parameters. The best fit model parameters resulting from these inversions describes magma storage in the form of an oblate spheroid centered on the northeastern rim of the caldera of Akutan volcano, extending from a depth of 7km to 8km, with a length of ~3.5km, a strike of ~N165°E, and a dip of ~63° from the horizontal to the southwest. Our model results were compared with seismic studies and found to support previous interpretations of episodic inflation beneath Akutan volcano with complicated magma storage at intermediate depths. The inflation event observed in 2008 was estimated to be the result of an injection of magma of ~0.08km3 that was followed in 2014 by an additional increase in volume of ~0.06km3. No periods of deflation were observed in the GPS data after these events, and we believe the total volume of magma accumulated in this region, ~0.2km3, remains in a shallow storage system beneath Akutan Volcano.

Minimization of model representativity errors in identification of point source emission from atmospheric concentration measurements

Estimation of an unknown atmospheric release from a finite set of concentration measurements is considered an ill-posed inverse problem. Besides ill-posedness, the estimation process is influenced by the instrumental errors in the measured concentrations and model representativity errors. The study highlights the effect of minimizing model representativity errors on the source estimation. This is described in an adjoint modelling framework and followed in three steps. First, an estimation of point source parameters (location and intensity) is carried out using an inversion technique. Second, a linear regression relationship is established between the measured concentrations and corresponding predicted using the retrieved source parameters. Third, this relationship is utilized to modify the adjoint functions. Further, source estimation is carried out using these modified adjoint functions to analyse the effect of such modifications. The process is tested for two well known inversion techniques, called renormalization and least-square. The proposed methodology and inversion techniques are evaluated for a real scenario by using concentrations measurements from the Idaho diffusion experiment in low wind stable conditions. With both the inversion techniques, a significant improvement is observed in the retrieval of source estimation after minimizing the representativity errors.

Performance analysis of distributed source parameter estimator (DSPE) in the presence of modeling errors due to the spatial distributions of sources

In this paper, the direction of arrival (DOA) localization of spatially distributed sources impinging on a sensor array is considered. The performance of the Distributed Source Parameter Estimator (DSPE) is studied in the presence of model errors due to the angular distribution shapes of the sources. Taking into account the coherently distributed source model proposed in Valaee et al.[1], we propose a definition of angular dispersion which makes DSPE robust to the angular distribution shapes of sources, and establish closed-form expressions of the DOA estimation bias and mean square error (MSE) due to both the model errors and the effects of a finite number of snapshots. The analytical results are validated by numerical simulations and allow to analyze the performance of DSPE for coherently distributed sources. The results also show the advantage of DSPE for the localization of spatially distributed sources even if the source angular distribution shape is not exactly known.

Gas emission source term estimation with 1-step nonlinear partial swarm optimization–Tikhonov regularization hybrid method

Abstract Source term identification is very important for the contaminant gas emission event. Thus, it is necessary to study the source parameter estimation method with high computation efficiency, high estimation accuracy and reasonable confidence interval. Tikhonov regularization method is a potential good tool to identify the source parameters. However, it is invalid for nonlinear inverse problem like gas emission process. 2-step nonlinear and linear PSO (partial swarm optimization)–Tikhonov regularization method proposed previously have estimated the emission source parameters successfully. But there are still some problems in computation efficiency and confidence interval. Hence, a new 1-step nonlinear method combined Tikhonov regularization and PSO algorithm with nonlinear forward dispersion model was proposed. First, the method was tested with simulation and experiment cases. The test results showed that 1-step nonlinear hybrid method is able to estimate multiple source parameters with reasonable confidence interval. Then, the estimation performances of different methods were compared with different cases. The estimation values with 1-step nonlinear method were close to that with 2-step nonlinear and linear PSO–Tikhonov regularization method. 1-step nonlinear method even performs better than other two methods in some cases, especially for source strength and downwind distance estimation. Compared with 2-step nonlinear method, 1-step method has higher computation efficiency. On the other hand, the confidence intervals with the method proposed in this paper seem more reasonable than that with other two methods. Finally, single PSO algorithm was compared with 1-step nonlinear PSO–Tikhonov hybrid regularization method. The results showed that the skill scores of 1-step nonlinear hybrid method to estimate source parameters were close to that of single PSO method and even better in some cases. One more important property of 1-step nonlinear PSO–Tikhonov regularization method is its reasonable confidence interval, which is not obtained by single PSO algorithm. Therefore, 1-step nonlinear hybrid regularization method proposed in this paper is a potential good method to estimate contaminant gas emission source term.

Seismic source spectral properties of crack‐like and pulse‐like modes of dynamic rupture

AbstractEarthquake source properties such as seismic moment and stress drop are routinely estimated from far‐field body wave amplitude spectra. Some quantitative but model‐dependent relations have been established between seismic spectra and source parameters. However, large variability is seen in the parameter estimates, and it is uncertain how the variability is partitioned among real variability in the source parameters, observational error, and modeling error due to complexity of earthquake behaviors. Earthquake models with dynamic weakening have been found to exhibit two different modes of rupture: expanding‐crack and self‐healing pulse modes. Four representative models are generated to model the transition from crack‐like to pulse‐like. Pulse‐like rupture leads to development of a second corner frequency, and the intermediate spectral slope is approximately 2 in most cases. The focal‐sphere‐averaged lower P and S wave corner frequencies are systematically higher for pulse‐like models than crack models of comparable rupture velocity. The slip‐weighted stress drop ΔσE exceeds the moment‐based stress drop ΔσM for pulse‐like ruptures, with the ratio ranging from about 1.3 to 1.65, while they are equal for the crack‐like case. The variations in rupture mode introduce variability of the order of a factor of 2 in standard (i.e., crack model‐based) spectral estimates of stress drop. The transition from arresting‐ to growing‐pulse rupture is accompanied by a large (factor of ∼1.6) increase in the radiation ratio. Thus, variations in rupture mode may account for the portion of the scatter in observational spectral estimates of source parameters.

Broadband Ground Motion Simulation of the 2004 and 1977 Vrancea, Romania, Earthquakes Using Empirical Green’s Function Method

We estimated the parameters of strong motion generation areas and simulated broadband ground motions for the moderate October 27, 2004 (M w 5.8) and damaging March 4, 1977 (M w 7.4) Vrancea (Romania) intermediate-depth subduction earthquakes using the empirical Green’s function method. The method allows the simulation of ground motions in a broadband frequency range by summing up the subevent records, corresponding to small magnitude events in the near-source areas, which are assumed to follow the source-scaling relationship and the omega-square source spectral model. We first estimated the strong motion generation area that reproduces near-source ground motions in a broadband frequency range of 0.3–10 Hz for the 2004 earthquake, by fitting the synthetic acceleration, velocity, and displacement waveforms to the observed data. The source properties of the obtained strong motion generation area are in agreement with the predictions made using an empirical source scaling relationship for crustal earthquakes, implying a stress drop of approximately 10 MPa for the 2004 earthquake. We then modeled the strong motion generation area for the 1977 damaging earthquake using the 2004 earthquake as an empirical Green’s function and constructing a source model based on its estimated source parameters. To simulate the unique record at Bucharest, capital city of Romania, the rupture was assumed to have propagated from the northeast bottom of the strong motion generation area having a stress drop of 50 MPa. Broadband ground motion simulations were further compared in terms of the modified Mercalli intensity values, calculated from the peak ground accelerations and peak ground velocities of synthetic waveforms, with the observed Medvedev–Sponheuer–Karnik intensity values. Our estimates of the source properties for the 2004 and 1977 Vrancea intermediate-depth earthquakes support the size-dependent stress drop.

Evaluation of deep moonquake source parameters: Implication for fault characteristics and thermal state

AbstractWhile deep moonquakes are seismic events commonly observed on the Moon, their source mechanism is still unexplained. The two main issues are poorly constrained source parameters and incompatibilities between the thermal profiles suggested by many studies and the apparent need for brittle properties at these depths. In this study, we reinvestigated the deep moonquake data to reestimate its source parameters and uncover the characteristics of deep moonquake faults that differ from those on Earth. We first improve the estimation of source parameters through spectral analysis using “new” broadband seismic records made by combining those of the Apollo long‐ and short‐period seismometers. We use the broader frequency band of the combined spectra to estimate corner frequencies and DC values of spectra, which are important parameters to constrain the source parameters. We further use the spectral features to estimate seismic moments and stress drops for more than 100 deep moonquake events from three different source regions. This study revealed that deep moonquake faults are extremely smooth compared to terrestrial faults. Second, we reevaluate the brittle‐ductile transition temperature that is consistent with the obtained source parameters. We show that the source parameters imply that the tidal stress is the main source of the stress glut causing deep moonquakes and the large strain rate from tides makes the brittle‐ductile transition temperature higher. Higher transition temperatures open a new possibility to construct a thermal model that is consistent with deep moonquake occurrence and pressure condition and thereby improve our understandings of the deep moonquake source mechanism.

An Improved GLRT for Image-Based Point Source Detection and Estimation

This work revisits the problem of detecting and localizing point sources in a scene using an imaging array and suggests two improvements over traditional approaches. First, the importance of covariance matrix estimation is discussed and several estimators are compared. In particular, the so-called shrinkage estimator is shown to produce better estimates of the covariance matrix and consequently provides improved detection performance over the commonly used naive estimator. We also develop an iterative algorithm for obtaining maximum likelihood estimates of the point source parameters. By using these estimates in forming the detection statistic, further improvements are demonstrated over previously used estimators.