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14 results for “Ambient seismic noise”
Accuracy of the Group Velocity of Love Waves Extracted from Ambient Seismic Noise
<p>Love wave waveforms derived from the empirical Green's functions and Ground Truth earthquake in my manuscript submitted to Journal of Geophysical Research: Solid Earth.</p>
Lateral Variations in Upper Mantle Discontinuities beneath Northeast China Revealed by Seismic Ambient Noise
<div>Data description:</div> <div> </div> <div>CCdata.zip:</div> <div>Re-sampling Cross-Correlation functions (4Hz) which contain three seismic arrays.</div> <div>CEA contains HL, JL, LN and NM networks. </div> <div>NECESSarray contains YP network. NECsaids contains DB network. </div> <div>All the stations are located east of 122E, between 41N and 46N. </div> <div>The cross-correlations are used to retrieved body-wave reflections from mantle transition zone discontinuities.</div> <div> </div> <div>Syntheticdata.zip:</div> <div>contains four parts: rawdata1d, rawdata2d, stackedwaveform-2d, and compare-1d</div> <div> </div> <div>rawdata1d: </div> <div>raw synthetic waveforms calculated by Qseis (Wang, 1999) after data-processings.</div> <div>H is increased from 0 to 30 km. </div> <div>The distance is 100 km. </div> <div> </div> <div>rawdata2d: </div> <div>raw synthetic waveforms calculated by SPECFEM2D (Tromp et al., 2008).</div> <div>Three models with depressed d660 (model 1-3) and with a slab on the d660 (model 4). </div> <div>100 receiver stations (surface), from 305 km to 1295 km in 10 km increments.</div> <div>49 vertical single-force sources (surface), from 320 km to 1280 km in 20 km increments </div> <div> </div> <div>stackedwaveform-2d:</div> <div>The final depth results with different models.</div> <div> </div> <div>compare-1d:</div> <div>The waveforms used to compare the rf and cc.</div> <div> </div> <div>Code:</div> <div>These codes can be used to make the figures of synthetic and NCFs results. </div> <div> </div> <div> </div> <div>NECsaidsDescription.docx:</div> <div>Detailed description about the NECsaids project conducted in northeast China from October, 2010 to September, 2017.</div> <div> </div> <div>station_loc.txt:</div> <div>Coordinate file (station, longitude, latitude) of the stations.</div> <div> </div> <div>Reference</div> <div>Wang, R. (1999). A simple orthonormalization method for stable and efficient computation of Green's functions. Bulletin of the Seismological Society of America, 89(3), 733-741. doi: 10.1785/BSSA0890030733</div> <div>Tromp, J., Komatitsch, D. and Liu, Q. Y. (2008). Spectral-element and adjoint methods in seismology. Commun Comput Phys 3, 1-32.</div>
Ambient noise from the atmosphere within the seismic hum period band: A case study of hurricane landfall
<p>Spectral analysis results, synthetic Green's functions, and seismic modeling results of this study.</p> <p>This work can be found at GitHub: <a href="https://github.com/NickJi98/Atm_Noise_2024_EPSL.git">https://github.com/NickJi98/Atm_Noise_2024_EPSL.git</a></p>
Upper Crustal Structure of the Xinfengjiang Reservoir from Ambient Noise Double Beamforming Tomography and Its Implications for Induced Seismicity
<p>The file "CC.tar.gz" contains the linearly stacked ZZ component cross-correlations for all station pairs.</p> <p>The file "Model.tar.gz" contains the 3-D upper crustal model of the Xinfengjiang Reservoir via ambient noise Double-Beamforming tomograpy.</p>
Imaging subsurface structure of an urban area based on Diffuse-Field Theory concept using seismic ambient noise
<p>Ambient noise data for a small urban area of NER India. The data set constitute all the raw files that were used for figures in the paper by Bora et al.</p>
Seismic ambient noise CCFs at Suwanosejima volcano, Japan
<p>The dailyCCF.tar contains data of daily seismic ambient noise CCFs at Suwanosejima volcano, Japan (April 1, 2017-December 31, 2021). These CCFs have been used to create the results in the accompanying paper "Seismic scattering property changes correlate with ground deformation at Suwanosejima volcano, Japan" by Takashi Hirose, Hideki Ueda, and Eisuke Fujita, submitted to the Journal of Geophysical Research: Solid Earth (https://doi.org/10.1002/essoar.10510785.2).</p>
Quantitatively Monitoring of Seasonal Frozen Ground Freeze-thaw Cycle Using Ambient Seismic Noise Data
<p>This is the electronic supplemental data for the publication entitled </p> <p>"<strong>Quantitatively Monitoring of Seasonal Frozen Ground Freeze-thaw Cycle Using Ambient Seismic Noise Data</strong>"</p> <p>submitted to <strong>Seismological Research Letters (SRL)</strong>. </p> <p>The names of the compressed files represent the experiment number and station number. For example, "1_2" indicates data collected from the second station during the first experiment. Each compressed file contains seismic raw data in the ".SAC" format. The filenames include the UTC end time of data collection. For instance, "453003616.00000001.2021.10.20.06.40.22.000.z.sac" indicates that data collection ended at 06:40:22 on October 20, 2021. Each complete .sac file contains 4 days of data with a sampling interval of 0.002 seconds.</p>
The seismic signature and geothermal potential of the Schwechat Depression in the Vienna Basin, Austria, from ambient noise tomography
<p>This folder contains the cross-correlation functions, the Love and Rayleigh dispersion measurements, the Love and Rayleigh2D group velocity maps, the 3D shear-wave velocity model and a Paraview file for 3D visualization of the Vs model. For further information refer to "C. Esteve, Y. Lu, J. M. Gosselin, R. Kramer, Y. Aiman, G. Bokelmann, 2024, The seismic signature and geothermal potential of the Schwechat Depression in the Vienna Basin, Austria, from ambient noise tomography" published in Geothermics.</p>
Fine seismic imaging of the Lianhuashan fault zone, South China, and tectonic implications – Constrained by ambient noise adjoint tomography
<p>The Rayleigh wave group velocity dispersion and the cross-correlation functions used in the study "Fine seismic imaging of the Lianhuashan fault zone, South China, and tectonic implications – Constrained by ambient noise adjoint tomography".</p>
Data from: A national VS30 model for South Korea to combine nationwide dense borehole measurements with ambient seismic noise analysis
<p>The average shear-wave velocity within the top 30 m from the surface, V<sub>S30</sub>, represents site characteristics including the soil classification and site amplification that are essential information for building codes and seismic design. A novel method to determine a V<sub>S30</sub> model based on a composite analysis of borehole standard penetration test numbers (SPT N) and horizontal-to-vertical (H/V) spectral ambient noise ratios is introduced. A national V<sub>S30</sub> model for South Korea is determined using the method. The shear-wave velocity structures beneath 20 nationwide broadband seismic stations are determined using the H/V analysis. The SPT N data are collected from 175,619 nationwide densely-distributed boreholes. The shear-wave velocity models from SPT N values are calibrated for the local reference velocity models from H/V analysis. A representative relationship between the SPT N values and shear-wave velocities is introduced. A national V<sub>S30</sub> model for South Korea is determined using the calibrated SPT N models at the nationwide boreholes. The V<sub>S30</sub> model is verified by comparisons with local field measurements. The proposed model is consistent with the USGS model based on a surface slope analysis. The V<sub>S30</sub> structure presents high correlation with geological and topographic features. The V<sub>S30</sub> values are low in coastal (low topographic) areas, and high in mountain (high topographic) areas. Apparent linear relationship is observed between V<sub>S30</sub> and topography. The western and southeastern coastal regions may be vulnerable to strong seismic shaking.</p>
Data from: A national VS30 model for South Korea to combine nationwide dense borehole measurements with ambient seismic noise analysis
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Dataset and 3D Vs Model for "Crustal velocity images of north-western Türkiye along the North Anatolian Fault Zone from transdimensional Bayesian ambient seismic noise tomography"
<p>Final 3D Vs model and dispersion data for the paper entitled "Crustal velocity images of north-western Türkiye along the North Anatolian Fault Zone from transdimensional Bayesian ambient seismic noise tomography".</p> <p>In the vel_files folder, there are 10 files for each depth for 1-15 km. The format of each velocity file is as follows:</p> <p>Column Value<br> 1 Lattitude (°)<br> 2 Longitude (°)<br> 3 Vs (km/s)</p> <p>The format of the dispersion data is as follows (See <a href="https://www.eas.slu.edu/eqc/eqc_cps/TUTORIAL/EMPIRICAL_GREEN/example1.html">Computer Programs in Seismology Tutorials - do_mft</a> for more information on the format):</p> <p>Column Value<br> 1 Type of file, MFT96<br> 2 Wave type: R for Rayleigh <br> 3 Dispersion type: U for group velocity<br> 4 Mode: 0 represents the fundamental mode<br> 5 Filter period, T, in seconds<br> 6 Dispersion value, either group or phase<br> 7 Error in dispersion. This is just a place holder since there is no way to estimate an error from a single trace. The group velocity error is determined from the ratio of the filter period to travel time<br> 8 Distance in km<br> 9 Azimuth from the source to the receiver<br> 10 Spectral amplitude. <br> 11 Epicenter latitude <br> 12 Epicenter longitude<br> 13 Station latitude<br> 14 Station longitude<br> 15 control flag<br> 16 control flag<br> 17 Instantaneous period if this is preferred. This differs from the ilter period because the signal spectram is not flat.<br> 18 Comment: keyword<br> 19 Station <br> 20 Component<br> 21 Year<br> 22 Day of year<br> 23 Hour<br> 24 Minute - these identify the event origin time </p>
cross-correlations of seismic ambient noise - Liupan Shan
<p>Stacked cross-correlation functions of the continuous seismic data recorded at the stations around the Liupan Shan area. Data in Text format, named "LPS.stationA_stationB.ZZ".</p> <p>The format of the data is as follows:</p> <p>Lon (stationA) Lat (stationA) Elevation (stationA)</p> <p>Lon (stationB) Lat (stationB) Elevation (stationB)</p> <p>Time (t=0) CF<sub>AB</sub>(t) CF<sub>BA</sub>(t)</p> <p>Time (t=dt) CF<sub>AB</sub>(t) CF<sub>BA</sub>(t)</p> <p>Time (t=2dt) CF<sub>AB</sub>(t) CF<sub>BA</sub>(t)</p> <p>……</p>
CSRM Level 2 dataset: inter-station empirical Green's functions (Z-Z component) in continental China from seismic ambient noise data
<p>This dataset contains the <strong>377,770</strong> inter-station empirical Green's functions and associated Rayleigh wave phase/group velocity dispersion curves that are calculated from continuous seismic ambient noise waveforms of <strong>2513</strong> seismic stations deployed in the continent China. This dataset results from a project of constructing the high-resolution China Seismological Reference Model (<strong>CSRM-1.0</strong>) in the top 100 km of the crust and uppermost mantle in continental China (<a href="https://doi.org/10.1029/2024JB029520">Xiao et al, JGR, 2024</a>) (<a href="https://doi.org/10.5281/zenodo.11098135">model link</a>). </p> <p>本数据库包含了利用中国大陆区域 <strong>2513</strong> 个地震台站记录的连续波形数据计算的 <strong>377,770 </strong>条台站间经验格林函数及其瑞利波相/群速度频散曲线。该数据库源于构建中国大陆区域高精度地壳和上地幔顶部 100 公里三维地震学模型(<strong>CSRM-1.0</strong>)的工作 (<a href="https://doi.org/10.1029/2024JB029520">Xiao et al, JGR, 2024</a>) (<a href="https://doi.org/10.5281/zenodo.11098135">模型链接</a>) 。</p> <p>If you face any problem or issue in the usage of this dataset, please feel free to communicate with the corresponding author Xiao Xiao (<strong>xiaox.seis@gmail.com</strong>). </p>
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