The Seismic Experiment for Interior Structure (SEIS): Experiment Data Distribution

The six sensors of SEIS (The Seismic Experiment for Interior Structure) [- one of three primary instruments on NASA's Mars Lander Insight] cover a broad range of the seismic bandwidth, from 0.01 hertz to 50 hertz, with possible extension to longer periods. Data are transmitted in the form of three continuous VBB (Very Broad-Band) components at 2 samples per second (sps), an estimation of the short period (SP) energy content from the SP at 1 sps, and a continuous compound VBB/SP vertical axis at 10 sps. The continuous streams are augmented by requested event data with sample rates from 20 to 100 sps. SEIS data products are downlinked from the spacecraft in raw CCSDS (Consultative Committee for Space Data Systems) packets and converted to both the Standard for the Exchange of Earthquake Data (SEED) format files and ASCII tables (GeoCSV) for analysis and archiving. Metadata are available in dataless SEED and StionXML. Time series data (waveforms) are available in miniseed and GeoCSV. Data are distributed according to FDSN (Federation of Digital Seismograph Networks - http://www.fdsn.org) formats and interfaces. Wind, pressure and temperature data from the Auxiliary Payload Sensor Suite (APSS) will also be available in SEED format, and can be used for decorrelation and diagnostic purposes on SEIS

The Earth's hum variations from a global model and seismic recordings around the Indian Ocean

The Earth's hum is the continuous oscillations of the Earth at frequencies between 2 and 20 mHz in the absence of earthquakes. The hum strongest signal consists mainly of surface waves. These seismic waves can be generated by infragravity waves propagating over a sloping ocean bottom close to the coast. So far, this theory has only been tested quantitatively using European seismic stations. We use seismic data recorded all around the Indian Ocean together with an ocean wave model that provides time‐frequency varying hum sources. We show that seasonal variations of the hum sources are smaller in the southern hemisphere (SH) than the northern hemisphere (NH). Using these sources, we model Rayleigh wave RMS amplitudes in the period band 3.5‐20 mHz, and the good agreement with seismic data on the vertical component confirms the theory of hum generation. Because the Indian Ocean is uniquely connected to the SH oceans but lies partly in NH latitudes, the seasonal pattern of the hum recorded there is particular and shows no significant seasonal variations. At ~10 mHz the hum is strongly influenced by local events, such as the passage of a cyclone close to a seismic station. Plain Language Summary In the absence of earthquake, the solid Earth is continuously vibrating at very low frequencies (2 to 20 mHz). These vibrations, called seismic hum, were discovered in the 1990s and can be recorded by seismic stations everywhere on Earth. They are generated by ocean infragravity waves propagating over a sloping ocean bottom close to the coast. So far, this theory has only been tested quantitatively using European seismic stations. We analyse seismic data recorded all around the Indian Ocean and we model them using hum sources derived from an ocean wave model. The good fit between data and model confirms the theory of hum generation. We further show that the hum recorded in the Indian Ocean is very specific and displays no significant seasonal variations. Finally, we demonstrate that when a cyclone arrives at a coast, it creates hum sources that increase the long period seismic signal recorded by the nearby stations

Detection of microseismic compressional (P) body waves aided by numerical modeling of oceanic noise sources

International audienceAmong the different types of waves embedded in seismic noise, body waves present appealing properties but are still challenging to extract. Here we first validate recent improvements in numerical modeling of microseismic compressional (P) body waves and then show how this tool allows fast detection and location of their sources. We compute sources at 0.2 Hz within typical P teleseismic distances (30-90°) from the Southern California Seismic Network and analyze the most significant discrete sources. The locations and relative strengths of the computed sources are validated by the good agreement with beam-forming analysis. These 54 noise sources exhibit a highly heterogeneous distribution, and cluster along the usual storm tracks in the Pacific and Atlantic oceans. They are mostly induced in the open ocean, at or near water depths of 2800 and 5600 km, most likely within storms or where ocean waves propagating as swell meet another swell or wind sea. We then emphasize two particularly strong storms to describe how they generate noise sources in their wake. We also use these two specific noise bursts to illustrate the differences between microseismic body and surface waves in terms of source distribution and resulting recordable ground motion. The different patterns between body and surface waves result from distinctive amplification of ocean wave-induced pressure perturbation and different seismic attenuation. Our study demonstrates the potential of numerical modeling to provide fast and accurate constraints on where and when to expect microseismic body waves, with implications for seismic imaging and climate studies

Characterization of microseismic noise in Cape Verde

The interaction of ocean waves with either the seafloor or other ocean waves generates primary (PM) and secondary microseisms (SM) that propagate through the crust and mantle, predominantly as Rayleigh waves. The horseshoe geometry and surrounding bathymetry of the Cape Verde archipelago play a significant role in the ambient-noise generation in this region. We analyze the microseisms recorded in the region using two different temporary seismic networks, and we determine the number of signals polarized as Rayleigh waves and their back azimuth (BAZ) as a function of time and frequency. The relative number of polarized signals between PM and SM varies between the stations. At most of the stations, the SM can be divided into two frequency bands. At lower frequencies (0.1-0.2 Hz), the number of SM signals is stable throughout the year, whereas at higher frequencies (0.2-0.3 Hz) this number varies with the season, with more polarized signals during the northern hemisphere spring and summer. In both frequency ranges and at most stations, the BAZ does not vary significantly over the year and points toward sources within the archipelago and outside. We compute the source site effect and show that the local bathymetry around the Cape Verde Islands strongly amplifies local SM sources. Finally, we compare the measured BAZ with source areas derived from an ocean-wave model, which confirms that Cape Verde stations mostly record local sources.info:eu-repo/semantics/publishedVersio

Ocean wave sources of seismic noise

[1] Noise with periods 3 to 10 s, ubiquitous in seismic records, is expected to be mostly generated by pairs of ocean wave trains of opposing propagation directions with half the seismic frequency. Here we present the first comprehensive numerical model of microseismic generation by random ocean waves, including ocean wave reflections. Synthetic and observed seismic spectra are well correlated (r> 0.85). On the basis of the model results, noise generation events can be clustered in three broad classes: wind waves with a broad directional spectrum (class I), sea states with a significant contribution of coastal reflections (class II), and the interaction of two independent wave systems (class III). At seismic stations close to western coasts, noise generated by class II sources generally dominates, but it is intermittently outshined by the intense class III sources, limiting the reliability of seismic data as a proxy for storm climates. The modeled seismic noise critically depends on the damping of seismic waves. At some mid‐ocean island stations, low seismic damping is necessary to reproduce the observed high level and smoothness of noise time series that result from a spatial integration of sources over thousands of kilometers. In contrast, some coastal stations are only sensitive to noise within a few hundreds of kilometers. This revelation of noise source patterns worldwide provides a wealth of information for seismic studies, wave climate applications, and new constraints on the possible directional distribution of wave energy

Observations of S410p and S350p phases at seismograph stations in California

International audienceWe analyze a new set of seismic data from seismograph stations in California. This data set consists of nearly 5000 S receiver functions for 47 seismograph stations. As a rule, the stacked SRFs display a distinct S410p seismic phase (S wave converted to P at the 410 km discontinuity). The wave paths of S410p sample the upper mantle beneath California and the neighboring region of the Pacific. In northernmost California the S410p travel times are close to those of the IASP91 global model. Further south, S410p usually arrives about 2 s earlier than predicted by the IASP91 model. This early arrival can be explained either by an anomalously high Vp/Vs velocity ratio (1.9 in a 125 km thick layer of the upper mantle versus 1.8 in IASP91), by a depression of the 410 km discontinuity of 15 km, or by a combination of both effects with smaller amplitudes. We observe systematically S350p phase which is converted from a negative discontinuity (with a lower S velocity at the lower side) near a depth of 350 km. The observations of S350p are indicative of a low S velocity layer a few tens of kilometers thick atop the 410 km discontinuity beneath southern California and the neighboring oceanic region. Some receiver functions also display S480p phase, which is interpreted as evidence of an intermittent low-velocity layer in the transition zone

The Effect of Water-Column Resonance on the Spectra of Secondary Microseism P-waves

We compile and analyze a dataset of secondary microseismic P-wave spectra that were observed by North American seismic arrays. Two distinct frequency bands, 0.13–0.15Hz and 0.19–0.21Hz, with enhanced P-wave energy characterize the dataset. Cluster analysis allows to classify the spectra and to associate typical spectral shapes with geographical regions: Low frequency dominated spectra (0.13-0.15Hz) are mostly detected in shallower regions of the North Atlantic and the South Pacific, as well as along the Central and South American Pacific coast. High frequency dominated spectra (0.19-0.21Hz) are mostly detected in deeper regions of the North-Western Pacific and the South Pacific. For a selected subset of high quality sources, we compute synthetic spectra from an ocean wave hindcast. These synthetic spectra are able to reproduce amplitude and shape of the observed spectra, but only if P-wave resonance in the water column at the source site is included in the model. Our datasets therefore indicate that the spectral peaks at 0.13-0.15Hz and 0.19-0.21 Hz correspond to the first and second harmonics of P-wave resonance in the water column that occur in shallower ocean depths (<3000m) and in the deep ocean (∼5000m), respectively. This article demonstrates the important effect of water column resonance on the amplitude and frequency of P-waves that are generated by secondary microseisms, and that the amplitude of high quality sources can be predicted from ocean wave hindcasts within a factor of 0.4 − 6

Cape Verde hotspot from the upper crust to the top of the lower mantle

International audienc

Imaging the crust and uppermost mantle structure of Portugal (West Iberia) with seismic ambient noise

International audienceWe present a new high-resolution three-dimensional (3D) shear wave velocity (Vs) model of the crust and uppermost mantle beneath Portugal, inferred from ambient seismic noise tomography. We use broadband seismic data from a dense temporary deployment covering the entire Portuguese mainland between 2010 and 2012 in the scope of the WILAS project. Vertical component data are processed using phase correlation and phase weighted stack to obtain Empirical Green functions (EGF) for 3900 station pairs. Further, we use a random sampling and subset stacking strategy to measure robust Rayleigh wave group velocities in the period range 7-30 s and associated uncertainties. The tomographic inversion is performed in 2 steps: First, we determine group velocity lateral variations for each period. Next, we invert them at each grid point using a new trans-dimensional inversion scheme to obtain the 3D shear wave velocity model. The final 3D model extends from the upper crust (5 km) down to the uppermost mantle (60 km) and has a lateral resolution of ~50 km. In the upper and middle crust, the Vs anomaly pattern matches the tectonic units of the variscan massif and alpine basins. The transition between the Lusitanian Basin and the Ossa Morena Zone is marked by a contrast between moderate and high velocity anomalies, in addition to two arched earthquake lineations. Some faults, namely the Manteigas-Vilariça-Bragança fault and the Porto-Tomar-Ferreira do Alentejo fault, have a clear signature from the upper crust down to the uppermost mantle (60 km). Our 3D shear wave velocity model offers new insights into the continuation of the main tectonic units at depth and contributes to better understanding the seismicity of Portugal