Empirical Green’s Function Research Articles

Strong variation of near-surface seismic anisotropy in Taiwan and its geological implications

We report on the near-surface (< 500 m) seismic structure (Vp, Vs, and Vs anisotropy) of Taiwan using the empirical Green's functions of body waves between vertical station pairs at 60 borehole sites. The near-surface anisotropy in metamorphic rocks and Miocene or older sedimentary strata are mostly categorized as orogeny-parallel anisotropy (OPA), and sites exhibiting stress-aligned anisotropy (SAA) are located in areas with late Quaternary sedimentary deposits or in alluvial coastal plains. The results show that there is a significant variation of the anisotropy strength even within the same geological unit. Since all the major geological units of Taiwan are well sampled by borehole arrays, and drilling data for 52 sites are available, this provides a unique opportunity to investigate the geological implications of strong variations in near-surface anisotropy. The investigation indicates that (1) near-surface anisotropy caused by structural fabric is generally stronger than that resulting from the alignment of stress-induced open cracks, (2) SAA strength in sedimentary rocks, igneous rocks, and gravel sediments is generally higher than that in fine-grained sediments, and (3) the sites with the strongest OPA (> 30%) are located in mountain ranges and the mean OPA strength of these sites is significantly higher than that of foothills, suggesting that foliated metamorphic rocks lead to stronger OPA than do dipping sedimentary strata. The results also suggest that the fluid-saturation of micro-cracks is not a necessary condition for the occurrence of the SAA mechanism in the near-surface depth range.

What Was the Level of Ground Motion across Europe during the Great A.D. 365 Crete Earthquake?

Abstract Historical and archeological data report that an earthquake was felt over the whole eastern Mediterranean on 21 July A.D. 365. The impact of the tsunami it generated, which may have caused several thousands of fatalities, has been widely studied, whereas the impact of the seismic waves has hardly been explored. Here, we present simulations of the ground motion caused by the A.D. 365 event at 316 sites now instrumented by seismological stations throughout Europe. The simulation approach is based on the modeling of a series of rupture scenarios coupled with empirical Green’s functions (EGFs) obtained at the stations from a recent Mw 6.4 earthquake. The broadband and remarkably also the accelerometric records in urbanized areas can be exploited at distances as far as ∼2000 km. Then, we use three empirical models to estimate the macroseismic intensity across Europe from the simulated peak ground accelerations and peak ground velocities. The presence of stations in thick sedimentary basins (lower Danube valley, Po plain, urban accelerometric network in the alpine valley of Grenoble) shows that local basin amplification effects can dominate acceleration values at frequencies favorable to human earthquake perception (~0.5–1 Hz), even for basins located at more than 1500 km from the earthquake. Thus, our simulations indicate that the A.D. 365 earthquake was likely felt by the populations as far as the Po plain and as the city of Grenoble, about 1800 km away, and presumably in other large European basins such as the Pannonian basin. It is possible that the perception of the earthquake up to such distances contributed to its “universal” character perpetuated in archival sources. At closer distances (300–500 km), the simulated intensity levels indicate that the earthquake probably caused no damage.

Beyond Correlations: Deep Learning for Seismic Interferometry.

Passive seismic interferometry is a vastly generalized blind deconvolution question, where different paths through the Earth correspond to different channels called Green's functions; the sources are completely incoherent and not shared by the channels, and the question is to estimate paths (channels) that are not present in the dataset. SI, turning noise to signal, has numerous applications, from monitoring industrial activities to crustal structure investigation. No standard method of signal processing will solve SI. Instead, domain scientists resort to a simple cross-correlation operation, a.k.a. correlogram, which can retrieve the Green's function directly, but only under restrictive assumptions of ergodicity (energy equipartitioning) of the random process generating the seismic source. However, in practice, correlograms are not equal to the empirical Green's function, because these assumptions are generally far from being satisfied in realistic situations. In the framework of supervised learning, we propose to train deep neural networks (NNs) to overcome two limitations of correlation-based SI: the temporal limitation of passive recordings and the spatial limitation of the random source distribution. Deep NNs are trained to implicitly find the relationship between the empirical Green's functions and the correlograms and then used to extract the correct Green's functions from ambient noise. The input of the network is correlograms (a virtual shot gather), and the desired output is the empirical Green's function (the active shot gather). The NN can often retrieve Green's functions from 5-min passive recordings with acceptable accuracy in our synthetic example. Although an exact estimation of the source locations may not be necessary, a prior knowledge of the source directionality (through a preliminary beamforming step) is helpful when training the NN to mitigate the challenges associated with inhomogeneous source distributions (directional wave fields). In this work, all the numerical examples are based on the retrieval of P-wave reflections in the exploration scale and are conducted on synthetic data. We use a modified ResNet in our numerical experiments.

Processing Ambient Noise Data Using Phase Cross‐Correlation and Application Toward Understanding Spatiotemporal Environmental Effects

AbstractTypical use of ambient noise interferometry focuses on longer period (&gt;1 s) waves for exploration of subsurface structure and other applications, while very shallow structure and some environmental seismology applications may benefit from use of shorter period (&lt;1 s) waves. We explore the potential for short‐period ambient noise interferometry to determine shallow seismic velocity structures by comparing two methodologies, the conventional amplitude‐based cross‐correlation and linear stacking (TCC‐Lin) and a more recently developed phase cross‐correlation and time‐frequency phase‐weighted‐stacking (PCC‐PWS) method with both synthetic and real data collected in a heterogeneous karst aquifer system. Our results suggest that the PCC‐PWS method is more effective in extracting short‐period wave velocities than the TCC‐Lin method, especially when using data collected in regions containing complex shallow structures such as the karst aquifer system investigated here. In addition to the different methodologies for computing the cross correlation functions, we also examine the relative importance of signal‐to‐noise ratio and number of wavelengths propagating between station pairs to determine data/solution quality. We find that the lower number of wavelengths of 3 has the greatest impact on the network‐averaged group velocity curve. Lastly, we test the sensitivity of the number of stacks used to create the final empirical Green's function, and find that the PCC‐PWS method required about half the number of cross‐correlation functions to develop reliable velocity curves compared to the TCC‐Lin method. This is an important advantage of the PCC‐PWS method when available data collection time is limited.

The 2016 Menyuan Earthquake: The Largest Self‐Arrested Crustal Earthquake Ever Observed

AbstractThe 2016 Mw 5.9 Menyuan earthquake occurred near the Haiyuan fault system in the northeastern Tibetan plateau. Although some kinematic properties of this event have been investigated, more dynamic properties still need to be clarified. First, we use the empirical Green's function method to obtain this event's apparent source time functions (ASTFs), which present a bell shape with a duration of 3s and corresponding smooth spectra. We then conduct dynamic rupture simulations, which are well constrained by the seismic and geodetic observations, to explore more in‐depth source properties. The results show that the characteristics of ASTFs can be explained by the self‐arresting rupture model, which implies that the rupture propagation of this event may spontaneously terminate before reaching the barriers. This result suggests that the initial conditions when this earthquake nucleated may have controlled the rupture process. Our work contributes to understanding the stopping mechanism of some moderate earthquake ruptures.

Characteristics of the Oceanic Ambient Seismic Noise Around Tristan da Cunha in the South Atlantic From OBS Data

AbstractIt has long been recognized that specific ambient seismic noise is generated within the ocean. Therefore, ocean bottom seismometers have advantages to reveal the noise characteristics directly in the deep sea. We use the seismic recordings around Tristan da Cunha collected by 20 OBSs and two island stations to investigate the ambient noise sources in the middle of the South Atlantic. We analyzed the power spectral density, ambient noise cross‐correlations, and correlations with wave heights model. While primary microseisms (∼10–20 s) in this region are deficient, the secondary microseisms are strong and dominate the ambient noise at periods of ∼1–10 s, with the peak broadening to shorter periods (1–3 s). The secondary microseisms are strongly correlated with the local wave heights, especially at shorter periods (∼1–3 s), suggesting that the microseisms are affected mostly by local wave interactions. We observed clear Empirical Green's functions at periods of ∼3–10 s, indicating the existence of distant sources of secondary microseisms. Results of asymmetry analysis of cross‐correlations suggest the prominent direction of the distant source should be located to the Southwest and show barely seasonal variations. The correlations with wave heights indicate a possible source region in the southeast Pacific Ocean. Therefore, besides the dominating local wave‐wave interactions, the secondary microseisms around Tristan region are affected simultaneously by persistent distant sources from the deep basin in the Southeast Pacific Ocean, which might be related to the intense wave‐wave interactions caused by the blocking effect of the Drake Passage on ocean currents and waves.

Shallow Volcano‐Tectonic Structures on the Island of Hawai'i Imaged by Multimode Rayleigh Wave Ambient Noise Tomography

AbstractSeismic tomography of shield volcanoes can be used to better understand its structure, formation, and evolution. Previous tomographic studies on the Island of Hawai'i used body waves from earthquakes and active sources and had limited resolution in the shallow crust. In this study, we obtained the empirical Green Functions (EGFs) and empirical Green Tensors (EGTs) from cross‐correlating and stacking of multiyear seismic ambient noise recorded on the island. The EGFs/EGTs contained fundamental mode and first higher mode Rayleigh waves. The different modes were separated with a new algorithm and their group velocities were measured. Using the group arrival times, we inverted for two‐dimensional group velocity maps, which provide, for the first time, a full coverage of the Island of Hawai'i. From the group velocity maps, we inverted for a three‐dimensional shear wave velocity model, which shows strong lateral variations and yields new insights into the structure and growth of the volcanoes on the island: Kı̄lauea's East Rift Zone has prominent high velocities at all depths, whereas the current rift zones of Mauna Loa are characterized by intermediate to high velocities only at depths greater than 1 km below ground surface, which may be attributed to their relatively short history and less developed state. The flanks of the volcanoes, some cut by fault zones, displayed low velocities at over a range of depths, generally interpreted as consisting of extrusive rocks, which could be further shattered by faulting.

Slip model with supershear rupture velocity and stress drop for an M4.5 aftershock of the 2019 Ridgecrest, California, earthquake sequence

SUMMARY We use records from 24 stations with epicentral distances under 50 km to invert for slip and rupture time of an M4.5 aftershock of the 2019 Ridgecrest, California, earthquake sequence. Slip was determined by inverting source time functions (STFs), which were obtained at each station by decomposing a main shock, in this case an M4.5 aftershock, into a series of subevents using an empirical Green's function (eGf) as a template. The technique is iterative in the time domain with a positivity constraint. The STFs are characterized by a single pulse with durations that were longer in the southeast direction (about 1.0 s) and shorter in the northwest direction (about 0.6 s) suggesting rupture directivity to the northwest. We inverted the STFs for slip using a tomographic algorithm from that uses a high-frequency approximation to ray theory for the forward problem. The tomographic algorithm solves for slip and rupture time on a grid of points, which provides a better strategy for elucidating directivity than a model that uses subfaults. We solve for the strike-slip intensity on a near-vertical plane striking northwest, similar to the M7.1. After nine iterations, the slip model reduces the chi-squared estimate of fit by 68 per cent. Most of the slip is to the northwest, with a narrow well-defined peak in slip about 0.3 km NW of the origin. The peak is fairly symmetrical and about 1.5 km across its base. The model shows significant directivity to the northwest as suggested by the azimuthal variation of the STF pulse widths. Rupture velocity increases from nucleation to the peak in slip, becomes supershear, and then slows to about 3.2 km s−1, but there is little slip beyond 0.8 s contour in the forward direction. It appears that the peak in slip contributed stress to accelerate the rupture to the northwest. Low-level, parabolic-shaped slip patterns are seen to the northwest, which could be where the rupture front is dying out. Similar, but fainter curves facing the southeast suggests some bilateral rupture but the rupture to the northwest was stronger. Static stress drop was calculated using a formula for an elastic half-space giving a maximum of 35 bars at the peak in slip, but smoothing controls the absolute value. The average over a presumed fault plane is about 1.4 bars, much less than the peak. Slip and stress drop are highly heterogeneous.

Weighted stacking of ambient noise correlations based on the coherency of 3C data

Seismic interferometry (SI) is widely used in imaging subsurface structures at different scales by extracting empirical Green's functions (EGFs) of surface wave propagation from ambient noise. The EGFs may be misestimated, however, because the anisotropic distribution of noise sources violates the SI's basic assumption of energy equipartitioning. A common solution is to stack all short-duration noise cross-correlation functions (NCFs) over a long period of time to attenuate the effect of anisotropic noise sources. The effectiveness of the common method is limited by the time of observation, and it may even be counterproductive. The influence of anisotropic noise sources may be reinforced if these sources possess strong energy. To obtain reliable EGFs, we develop a new weighted stack method named the components-coherency-weighted stack (CCWS). We calculate the coherency of different components of noise recorded by a single station to scan the azimuth of the main source in one segment. We select the segments according to the azimuth for NCF computation and then stack the NCFs with a weight relevant to the coherency. We first test the method on simulated data containing strong azimuthal noise sources and show that our method yields high quality EGFs. The method is then used for two real data examples at a regional scale of hundreds of kilometers and an engineering scale of tens of meters. Two examples confirm the ability of our approach to improve the EGFs and its applicability at different scales.

Nonsystematic Rupture Directivity of Geothermal Energy Induced Microseismicity in Helsinki, Finland

AbstractThe rupture behavior of microseismicity in fluid‐injection settings with low fault stresses is generally believed to be controlled by the pore pressure, including a tendency of the larger induced earthquakes to rupture into the perturbed volume toward the injection well, implying a degree of predictability. Here, we examine directivity patterns to identify fault planes and rupture directions of the 21 largest earthquakes (local magnitudes, 1.3–1.9) recorded during the 2018 St1 Deep Heat geothermal project near Helsinki, Finland. We use the Empirical Green's Function technique to retrieve per‐seismic‐station corner frequencies, earthquake durations, and directivity trends. After combining the directivity trends with focal mechanisms calculated using principle component analysis, we resolve rupture planes and rupture directions of 10 events. In contrast to studies of induced events at other sites, we find that one event rupture toward, two rupture away, and the remaining rupture parallel to the well. Furthermore, we find that the events prefer mode II failures rather than mode III. These observations provide new constraints for mechanical models of rupture growth in pore‐pressure dominated settings.

Time-domain source parameter estimation ofMw 3–7 earthquakes in Japan from a large database of moment-rate functions

SUMMARYTime-domain analyses of seismic waveforms have revealed diverse source complexity in large earthquakes (Mw &amp;gt; 7). However, source characteristics of small earthquakes have been studied by assuming a simple rupture pattern on the frequency domain. This study utilizes high-quality seismic network data from Japan to systematically address the source complexities and radiated energies of Mw 3–7 earthquakes on the time domain. We first determine the apparent moment-rate functions (AMRFs) of the earthquakes using the empirical Green's functions. Some of the AMRFs show multiple peaks, suggesting complex ruptures at multiple patches. We then estimate the radiated energies (ER) of 1736 events having more than ten reliable AMRFs. The scaled energy (eR = ER/M0) does not strongly depend on the seismic moment (M0), focal mechanisms, or depth. The median value of eR is 3.7 × 10−5, which is comparable to those of previous studies; however, eR varies by approximately one order of magnitude among earthquakes. We measure the source complexity based on the radiated energy enhancement factor (REEF). The values of REEF differ among earthquakes, implying diverse source complexity. The values of REEF do not show strong scale dependence for Mw 3–7 earthquakes, suggesting that the source diversity of smaller earthquakes is similar to that of larger earthquakes at their representative spatial scales. Applying a simple spectral model (e.g. the ω2-source model) to complex ruptures may produce substantial estimation errors in source parameters.

Source parameter analysis using distributed acoustic sensing – an example with the PoroTomo array

SUMMARY In this study, I demonstrate that distributed acoustic sensing (DAS) raw strain rate data can directly be used to estimate spectral source parameters through an Empirical Green's Function (EGF) deconvolution analysis. Previously, DAS had been widely used in passive seismology to image the subsurface and analyze ground motion variations by converting strain or strain rate to particle velocity or acceleration prior to analysis. In this study, spectral analysis is applied to the PoroTomo joint DAS and seismic Nodal array in the Brady Hot Springs geothermal field to obtain source parameters for two M4 earthquakes via EGF analysis, where nearly collocated smaller events are used as an EGF to remove path and site effects. The EGF workflow is applied to raw DAS strain rate data without conversion to particle velocities and raw Nodal seismic data. The DAS and Nodal results are very consistent with similar features of spectral ratios, corner frequencies and moment ratios for the same event pairs. The uncertainty due to stacked spectral measurement is much lower on the DAS array, suggesting better stability of spectral shape measurement, possibly due to the much denser spatial sampling. The uncertainty due to model fitting is similar between DAS and Nodal arrays with slightly lower uncertainty on the DAS array. These observations demonstrate potential for directly using the strain rate measurements from DAS arrays for earthquake source characterizations.

Characterized source model of the M7.3 2016 Kumamoto earthquake by the 3D reciprocity GFs inversion with special reference to the velocity pulse at KMMH16

The 2016 Kumamoto earthquakes caused severe damage centering on the Mashiki residential area. The velocity waveforms at station KMMH16 in Mashiki, during the M7.3 mainshock, show large pulses. We found that severe damage in Mashiki may be the result of the strong westward velocity pulse. The question raised is how the near-fault ground motions with strong velocity pulse at KMMH16 were generated during the mainshock. We focus on the characterized source model with Strong Motion Generation Areas (SMGA). Empirical Green’s function (EGF) method is widely used for source modeling in this case. However, in case that the target site is located just near the fault in nodal plane of source mechanism (like KMMH16), mechanism of the EGF event should perfectly fit mechanism of the mainshock, which is a rare case. Therefore, instead of using EGFs, we used theoretical 3D Green’s functions. Our approach is a nonlinear source inversion. This method requires calculation of waveforms and comparison with observations for many source models. To accelerate these calculations, we use pre-calculated GFs by the reciprocity method in the JIVSM velocity structure model. By comparison with aftershock records, we validated this structure for periods as short as 1.5 s. Target sites are limited to sites close to the fault: KMM005, KMM006, KMMH14, and KMMH16. First, we look for an initial SMGA source model by the grid search method applied to relatively long-period (> 3 s) waveforms and coarse grid of source parameters. Then, we tune that source model to fit observed short-period waveforms with the simplex search method. Necessary physical constraints for the range of the source parameters are applied here. The important point in our inversion scheme is to describe the Kostrov-like slip velocity functions inside each SMGAs by using two triangles. The resulting source model agrees well with other inversion results. We found that the observed westward pulse at KMMH16 is the result of the constructive interference of two pulses from SMGA1 and SMGA2, located in Hinagu fault and southwestern segment of Futagawa fault.Graphical

Estimation of broadband ground motion characteristics considering source parameter uncertainty and undetermined site condition in densely populated areas of Pingwu

Three destructive earthquakes occurred in Pingwu and Songpan, Sichuan Province, China, between August 16 and 23, 1976. Due to the seismic monitoring capability at that time, the ground motion characteristics of these earthquakes are very vague. Realistc and reliable strong ground motion input plays an important role in seismic building design and urban-scale earthquake damage simulation. This study reproduces the main broadband ground motion characteristics of the 1976 Ms7.2 Songpan earthquake in densely populated areas of Pingwu. The empirical Green’s function method and finite difference method are used to simulate high-frequency and low-frequency ground motion, respectively, and the broadband ground motion is obtained by superposition within the frequency range. In addition, in combination with the “Recipe” source parameter scheme, various uncertainties in the source parameters are considered, including the source mechanism, source depth, asperity parameters, etc. We obtain 36 kinds of broadband ground motion at six typical locations in the Pingwu area. Moreover, we test the rationality of the obtained broadband ground motion by ground motion prediction equations(GMPEs), and the broadband ground motions are consistent with the local ground motion characteristics. The results show broadband ground motions obtained from the scenario earthquake in this paper can meet the destructive capacity of earthquakes of this magnitude. The hybrid method can effectively compensate for the lack of long-period components of the original empirical Green function method. This research also proves that the peak ground acceleration (PGA) of ground motion is mainly contributed by high-frequency ground motion components. Long-period ground motion contributes most to the peak ground velocity (PGV), and about twice the contribution of high-frequency ground motion. Concerning the Chinese seismic intensity scale (GB/T 17742-2020) and China Seismic Ground Motion Parameter Zoning Map (GB18306-2015), the basic fortification intensity in the Pingwu area is VIII. In this paper, the seismic intensity of PWN is VI-VII, indicating that the buildings at this location are less likely to be damaged after the earthquake. The seismic intensity of other regions is VII-IX and buildings are more likely to be damaged during the earthquake at these locations. There are many mountains and valleys in the Pingwu area, and the probability of landslides, debris flows, and other disasters after an earthquake is very high, and we should give special attention to the impact of secondary disasters caused by earthquakes. It is necessary to prevent dammed lakes and other disasters caused by landslides and debris flows.

Combining seismic signal dynamic inversion and numerical modeling improves landslide process reconstruction

Abstract. Landslides present a significant hazard for humans, but continuous landslide monitoring is not yet possible due to their unpredictability. In recent years, numerical simulation and seismic inversion methods have been used to provide valuable data for understanding the entire process of landslide movement. However, each method has shortcomings. Dynamic inversion based on long-period seismic signals gives the force–time history of a landslide using an empirical Green's function but lacks detailed flowing characteristics for the hazards. Numerical simulation can simulate the entire movement process, but results are strongly influenced by the choice of modeling parameters. Therefore, developing a method for combining those two techniques has become a focus for research in recent years. In this study, we develop such a protocol based on analysis of the 2018 Baige landslide in China. Seismic signal inversion results are used to constrain and optimize the numerical simulation. We apply the procedure to the Baige event and, combined with a field geological survey, show it provides a comprehensive and accurate method for dynamic process reconstruction. We found that the Baige landslide was triggered by detachment of the weathered layer, with severe top fault segmentation. The landslide process comprised four stages: initiation, main slip, blocking, and deposition. Multi-method mutual verification effectively reduces the inherent drawbacks of each method, and multi-method joint analysis improves the rationality and reliability of the results. The approach outlined in this study could help us to better understand the landslide dynamic process.

Simulation of strong earthquake characteristics of a scenario earthquake (MS7.5) based on the enlightenment of 2022 MS6.9 earthquake in Menyuan

The Menyuan area is an important transportation hub in the Hexi Corridor. The Menyuan MS6.9 earthquake that occurred on January 8, 2022 had a major impact on the local infrastructure and transportation of this region. Due to the high possibility of similar strong earthquakes occurring in this area in the future, preliminary assessment of the seismic intensity characteristics of destructive earthquakes in this region is essential for effective disaster control. This paper uses the empirical Green′s function (EGF) method as a numerical simulation tool to predict the ground motion intensity of Datong Autonomous County under the action of the scenario earthquake (MS7.5). Seismic records of aftershocks of the 2016 Menyuan MS6.4 earthquake were used as Green’s functions for this simulation. The uncertainties associated with various source parameters were considered, and 36 possible earthquake scenarios were simulated to obtain 72 sets of horizontal ground motions in Datong County. The obtained peak ground acceleration (PGA) vs. time histories of the horizontal ground motion were screened using the attenuation relationships provided by the fifth-edition of China's Seismic Ground Motion Parameter Zoning Map and the NGA-West2 dataset. Ultimately, 32 possible acceleration-time histories were selected for further analysis. The screened PGA values ranged from 78.8 to 153 cm/s2. The uncertainty associated with the initial rupture point was found to greatly affect the results of the earthquake simulation. The average acceleration spectrum of the selected acceleration-time history exceeded the expected spectrum of a intermediate earthquake, which means that buildings in Datong County might sustain some damage should the scenario earthquake occur. This research can provide reliable ground motion input for urban earthquake damage simulation and seismic design in Datong County. Growing the dataset of small earthquakes recorded in this region will facilitate the large-scale simulation of ground motions under different earthquake scenarios.

Shear wave velocities in the upper crust of the Quadrilátero Ferrífero, Minas Gerais: Rayleigh-wave tomography

We applied a combination of ambient seismic noise and classical earthquake-receiver techniques to characterize the shallow crustal shear-wave velocities in the Quadrilátero Ferrífero (QF), Minas Gerais state, SE Brazil, to a depth of about 4 km. Ambient seismic noise was recorded by up to 26 stations. To improve the signal of the extracted empirical Green's function (EGF), we correlated short time windows of 10 min with 70% overlapping before stacking. To test the accuracy of the retrieved EGF signals, we compared the results obtained from ambient seismic noise correlation with results from an earthquake occurred near FABR station. After measuring dispersion using frequency-time analysis (FTAN), we applied strict quality criteria (e.g., eliminating paths with residuals larger than two standard deviations, or lengths smaller than 3 wavelengths). The Fast Marching Surface wave Tomography (FMST) method was used to obtain group velocity maps. Then, the local dispersion curves were inverted to obtain a 3D Vs model. The resulting 3D model shows low velocity anomalies in the middle of the QF, compared with high velocities in the Archean part of the São Francisco Craton to the west. The low velocity metasedimentary layer in the QF is about 1.5 km thick.

Upper-lithospheric structure of northeastern Venezuela from joint inversion of surface-wave dispersion and receiver functions

Abstract. We use 1.5 years of continuous recordings from an amphibious seismic network deployment in the region of northeastern South America and the southeastern Caribbean to study the crustal and uppermost mantle structure through a joint inversion of surface-wave dispersion curves determined from ambient seismic noise and receiver functions. The availability of both ocean bottom seismometers (OBSs) and land stations makes this experiment ideal to determine the best processing methods to extract reliable empirical Green's functions (EGFs) and construct a 3D shear velocity model. Results show EGFs with high signal-to-noise ratio for land–land, land–OBS and OBS–OBS paths from a variety of stacking methods. Using the EGF estimates, we measure phase and group velocity dispersion curves for Rayleigh and Love waves. We complement these observations with receiver functions, which allow us to perform an H-k analysis to obtain Moho depth estimates across the study area. The measured dispersion curves and receiver functions are used in a Bayesian joint inversion to retrieve a series of 1D shear-wave velocity models, which are then interpolated to build a 3D model of the region. Our results display clear contrasts in the oceanic region across the border of the San Sebastian–El Pilar strike-slip fault system as well as a high-velocity region that corresponds well with the continental craton of southeastern Venezuela. We resolve known geological features in our new model, including the Espino Graben and the Guiana Shield provinces, and provide new information about their crustal structures. Furthermore, we image the difference in the crust beneath the Maturín and Guárico sub-basins.

Ambient sound directionality and rapid estimation of empirical Green’s functions in a coastal ocean

Noise interferometry offers an opportunity for passive ocean remote sensing through retrieval of empirical Green’s functions (EGFs) from cross-correlations of ambient sound. At ranges of tens of ocean depths, obtaining stable and accurate EGF estimates usually requires noise averaging periods of hours or days. Decreasing the necessary averaging times without compromising the EGF accuracy is critically important for operational applications. Using data acquired in the Shallow Water 2006 experiment on the continental shelf off New Jersey, it has been found that occasionally averaging periods as short as a few minutes are sufficient. The phenomenon is observed for various receiver pairs but does not occur simultaneously in all azimuthal directions. Short averaging periods give EGFs in a broader frequency band and with a richer mode content. These are better suited to monitor physical processes in the water column. The conditions conducive to rapid EGF emergence are studied using in situ temperature measurements, meteorological information, and the acoustic data acquired with a horizontal line array. Strong intermittency is observed in the horizontal directionality of ambient sound. For various receiver pairs, EGFs are found to emerge rapidly when ambient sound directionality favors propagation in the direction from one receiver to the other.

Evidence for Short Temporal Atmospheric Variations Observed by Infrasonic Signals: 2. The Stratosphere

AbstractThis study uses infrasound detections from a repetitive source to estimate the effect of the atmosphere's temporal variability on infrasound. While a previous paper focused on infrasound propagation through the troposphere to a distance of 54 km, this study uses stratospheric returns detected 256 km from the source. Based on source‐receiver pairs, the empirical Green's function is calculated every 20 s for 52 events; these allow generating a set of synthetic signals where variations are ascribed to variation in the atmosphere. In addition, observations are compared with numerical simulation results based on realistic atmospheric conditions. Results show that variations of stratospheric infrasound signals are observed over timescales ranging from tens of seconds to minutes and have dominant periods ranging from tens to hundreds of seconds. These results motivate using infrasound to probe short temporal changes in the middle atmosphere and study their underlying phenomena.