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14 results for “slow slip events”
Simulated Seafloor Pressures for "The Ocean's Impact on Slow Slip Events"
<p>These files in this archive contain the simulated seafloor pressures used in the study of Gomberg et al. (2020). These seafloor pressures were derived from a Regional Ocean Modeling System (ROMS) on the seafloor of the Hikurangi subduction zone off New Zealand [<em>Hadfield et al.</em>, 2007] at offshore sites deployed during the 10-month 2014-2015 Hikurangi Ocean Bottom Investigation of Tremor and Slow Slip (HOBITSS) experiment [<em>Wallace et al.</em>, 2016]. Details of each file are described in the Readme.pdf file.These files in this archive contain the simulated seafloor pressures used in the study of Gomberg et al. (2020). These seafloor pressures were derived from a Regional Ocean Modeling System (ROMS) on the seafloor of the Hikurangi subduction zone off New Zealand [<em>Hadfield et al.</em>, 2007] at offshore sites deployed during the 10-month 2014-2015 Hikurangi Ocean Bottom Investigation of Tremor and Slow Slip (HOBITSS) experiment [<em>Wallace et al.</em>, 2016]. Details of each file are described in the Readme.pdf file.</p>
Source parameters of short-term slow slip events in southcentral Alaska
<p>Source parameters of short-term slow slip events (SSEs) in southcentral Alaska from April 1, 2007, to March 31, 2021. This data set is a CSV format version of Table S5 in our manuscript recently accepted in Geophysical Research Letters (GRL). Please read the GRL paper for the details of the detection method and data we used. The format of this data set is as follows:</p> <p> </p> <p><strong>Okada-Nishimura2023_short-term_SSE_southcentral-Alaska.csv</strong></p> <p>Col 1: event date (yyyymmdd: middle date of duration)</p> <p>Col 2: longitude of the fault center (degree)</p> <p>Col 3: latitude of the fault center (degree)</p> <p>Col 4: depth of the fault center (km)</p> <p>Col 5: length of the fault (km)</p> <p>Col 6: width of the fault (km)</p> <p>Col 7: strike angle of the fault (degree)</p> <p>Col 8: dip angle of the fault (degree)</p> <p>Col 9: rake angle of the slip (degree)</p> <p>Col 10: slip amount (m)</p> <p>Col 11: seismic moment (Nm)</p> <p>Col 12: moment magnitude</p> <p>Col 13: duration (day)</p> <p>Col 14: event category (1: SSEs, 2: potential transient events)</p> <p> </p> <p># Version Info</p> <p>Version 1: Initial submission</p>
Dataset for the paper "Imaging evolution of Cascadia slow‑slip event using high‑rate GPS"
<p>Slip and slip rate files for the preferred model of Itoh, Aoki, and Fukuda (2022, Scientific Reports, doi:10.1038/s41598-022-10957-8).</p> <p>Please see readme.txt for further details. The corresponding author information is also available there.</p> <p>Caution: the dataset has the size of 4.3GB after uncompression/extraction.</p>
Data products for "3D modeling of long-term slow slip events along the flat-slab segment in the Guerrero Seismic Gap, Mexico"
<p>Data products for '3D modeling of long-term slow slip events along the flat-slab segment in the Guerrero Seismic Gap, Mexico' by A. Perez-Silva, D. Li, A.-A. Gabriel and Y. Kaneko</p>
Measurements of fault slip associated with the 2023 Superstition Hills Fault slow slip event
<p>Creepmeter time series, global navigation satellite system (GNSS) measurements, line-of-sight Sentinel-1A interferograms with atmospheric corrections, and field measurements of slip along the Superstition Hills Fault in 2023 due to slow slip.</p>
Supporting Information for "Investigation of Hikurangi subduction zone slow slip events using onshore and onshore geodetic data" PhD thesis
<p>The data sets included here are those inverted using the TDEFNODE (McCaffrey et al., 2009) inversion code in the PhD thesis "Investigation of Hikurangi subduction zone slow slip events using onshore and onshore geodetic data" to obtain geodetic slip models of the 2013-2016 and February-July 2019 periods at the Hikurangi subduction zone.</p> <p> </p> <p><em>The 2013-2016 period captured the 2013 Kāpiti and 2014/2015 Manawatū slow slip events (SSEs), in addition to the 2013 Cook Strait, 2013 Lake Grassmere, and 2014 Eketāhuna earthquakes. The data related to this model are:</em></p> <p><strong>campaign_gps_2013.ts</strong><br> -campaign GPS time series<br> -columns: Year East East_sigma North North_sigma Up Up_sigma<br> -input using TDEFNODE command ts1</p> <p><strong>coseismic_displacements_2013_07_21.ds </strong><br> -coseismic displacements for Cook Strait earthquake (Hamling et al., 2014)<br> -columns: Longitude Latitude Disp_East Disp_North Sigma_East Sigma_North Site Disp_Up Sigma_Up Time1 Time2<br> -input using TDEFNODE command ds2</p> <p><strong>coseismic_displacements_2013_08_16.ds </strong><br> -coseismic displacements for Lake Grassmere earthquake (Hamling et al., 2014)<br> -columns: Longitude Latitude Disp_East Disp_North Sigma_East Sigma_North Site Disp_Up Sigma_Up Time1 Time2<br> -input using TDEFNODE command ds2</p> <p><strong>onshore_gnss_kapiti_manawatu_2013_2016.ts</strong><br> -GNSS time series<br> -columns: Year East East_sigma North North_sigma Up Up_sigma<br> -input using TDEFNODE command ts1</p> <p><strong>LOS_coseismic_2013_08_16.is<br> -</strong>coseismic Line of Sight displacements for Lake Grassmere earthquake (Hamling et al., 2014)<br> -convention: negative displacement equivalent to ground moving towards the satellite<br> -columns: Longitude Latitude LineOfSight_disp sigma Unit_x Unit_y Unit_z<br> -input using TDEFNODE command is1</p> <p> </p> <p><em>Data related to the February-July 2019 SSE model are:</em></p> <p><strong>onshore_gnss_east_coast_sse_2019.ts</strong><br> -GNSS time series<br> -columns: Year East East_sigma North North_sigma Up Up_sigma<br> -input using TDEFNODE command ts4</p> <p><strong>seafloor_displacement_gisborne.ts</strong><br> -seafloor pressure time series<br> -convention: positive change equivalent to seafloor uplift<br> -columns: Year East East_sigma North North_sigma Up Up_sigma<br> -input using TDEFNODE command ts4</p> <p><strong>seafloor_displacement_hawkebay.ts</strong><br> -seafloor pressure time series<br> -convention: positive change equivalent to seafloor uplift<br> -columns: Year East East_sigma North North_sigma Up Up_sigma<br> -input using TDEFNODE command ts4</p> <p><strong>LOS_SSE_2019.is</strong><br> -SSE-related Line of Sight displacement<br> -convention: positive displacement equivalent to ground moving away from satellite<br> -columns: Longitude Latitude LineOfSight_disp sigma Unit_x Unit_y Unit_z<br> -input using TDEFNODE command is1</p> <p> </p> <p>The TDEFNODE manual can be found here:<br> https://robmccaffrey.github.io/TDEFNODE/manual/tdefnode_manual.html</p> <p>The header lines in the time series files (.ts) take the site inter-SSE rates from the model of Wallace et al. (2012).</p> <p> </p> <p><em>References</em></p> <p>Hamling, I. J., D’Anastasio, E., Wallace, L. M., Ellis, S., Motagh, M., Samsonov, S., Palmer, N., and Hreinsdóttir, S. (2014). Crustal deformation and stress transfer during a propagating earthquake sequence: The 2013 Cook Strait sequence, central New Zealand. <em>Journal of Geophysical Research: Solid Earth</em>, <strong>119</strong>(7):6080–6092.</p> <p>McCaffrey, R. (2009). Time-dependent inversion of three-component continuous GPS for steady and transient sources in northern Cascadia. <em>Geophysical Research Letters</em>, <strong>36</strong>(L07304).</p> <p>Wallace, L. M., Barnes, P., Beavan, J., Van Dissen, R., Litchfield, N., Mountjoy, J., Langridge, R., Lamarche, G., and Pondard, N. (2012). The kinematics of a transition from subduction to strike-slip: An example from the central New Zealand plate boundary. <em>Journal of Geophysical Research: Solid Earth</em>, <strong>117</strong>(B2).</p>
Earthquake Cycle Deformation Associated with the 2021 Mw 7.4 Maduo (Eastern Tibet) Earthquake: An Intrablock Rupture Event on a Slow-Slipping Fault from Sentinel-1 InSAR and Teleseismic Data
<p>Coseismic slip models of the 2021 Mw 7.4 Maduo (eastern Tibet) earthquake derived from Sentinel-1 InSAR and teleseismic data.</p> <p>Interseismic eastward and vertical velocity and maximum shear strain rate fields.</p> <p>Citations:</p> <p>Fang, J., Ou, Q., Wright, T. J., Okuwaki, R., Amey, R. M. J., Craig, T. J., et al. (2022). Earthquake cycle deformation associated with the 2021 M<span>W </span>7.4 Maduo (eastern Tibet) earthquake: An intrablock rupture event on a slow-slipping fault from Sentinel-1 InSAR and teleseismic data. Journal of Geophysical Research: Solid Earth, 127, e2022JB024268. <span>https://</span>doi.org/10.1029/2022JB024268</p> <p>Fang, J., Ou, Q., Wright, T. J., Okuwaki, R., Amey, R. M. J., Craig, T. J., et al. (2022). Earthquake cycle deformation associated with the 2021 M<span>W </span>7.4 Maduo (eastern Tibet) earthquake: An intrablock rupture event on a slow-slipping fault from Sentinel-1 InSAR and teleseismic data [Data set]. Zenodo. https://doi.org/10.5281/zenodo.7215161<span>.</span></p>
Data set of manuscript entitled "Spatiotemporal evolution of long- and short-term slow slip events in the Tokai region, central Japan, estimated from a very dense GNSS network during 2013–2016" submitted to the Journal of Geophysical Research: Solid Earth
<p>This data set was used for manuscript entitled “Spatiotemporal evolution of long- and short-term slow slip events in the Tokai region, central Japan, estimated from a very dense Global Navigation Satellite Systems (GNSS) network during 2013–2016” submitted to the Journal of Geophysical Research: Solid Earth. This data set includes 1 figure file, 1 station list and 26 numerical data files. Figure and numerical data are locations of GNSS stations and GNSS time series used in our submitted manuscript, respectively.</p> <p>Figure file maned “location_of_station.png” shows locations of GNSS stations used in our submitted manuscript. Blue dots denote a continuous GNSS network named GEONET was installed by the Geospatial Information Authority of Japan, and red triangles denote continuous GNSS stations constructed by the Japanese University Consortium for GPS Researchers (JUNCO) and operated by the Earthquake Research Institute at the University of Tokyo and allied universities.</p> <p>The coordinates of JUNCO station are collected in a file named “site_junco.bl”. Description of each column is as follows:</p> <p>1. Column 1: Longitude in degree.</p> <p>2. Column 2: Latitude in degree.</p> <p>3. Column 3: Station name.</p> <p>Numerical data is GNSS time series, corresponds to the corrected time series in our submitted manuscript, observed for the period between 1 January 2013 and 31 January 2016. A complete description of data set is found in our submitted manuscript. Description of each column is as follows:</p> <p> </p> <p>1. Column 1: Days since 31 December 2012.</p> <p>2. Column 2: East displacement in cm</p> <p>3. Column 3: North displacement in cm</p> <p>4. Column 4: Vertical displacement in cm</p> <p>5. Column 5: Standard deviation of east displacement in cm</p> <p>6. Column 6: Standard deviation of north displacement in cm</p> <p>7. Column 7: Standard deviation of vertical displacement in cm</p> <p> </p> <p>The numerical data in this data set includes only the 26 JUNCO stations data. Numerical data files are named by the regularity of the combination of the 4 characters station name and extension “.dat”.</p>
Dataset of automated earthquake detections in the Hikurangi Margin (New Zealand) during the 2014 Slow Slip Event
<p>The dataset provided in this repository contains:</p> <p>- Yarce_REST_events.dat: Contains information of 854 events, with event id, origin time (epoch time), latitude, longitude, depth, number of P arrivals, number of S arrivals, total number of arrivals, local magnitude.</p> <p>- Yarce_REST_arrivals.data: Contains the arrival data information of the 854 events in Yarce_REST_events_v2.csv: event id, station, phase (P or S), arrival time.</p>
The role of shear fabric in controlling breakdown processes during laboratory slow slip events
<p>Understanding the physical mechanisms at the origin of slow slip events has been proven a very challenging task. In particular little is known on the role of fault heterogeneity during slow slip. In this study we provide evidence that fault fabric controls slip velocity time histories during slow slip events generated in the laboratory under the specific boundary condition of imposing a stiffness ratio K=k/k<sub>c</sub>~1. We have performed experiments using a double-direct biaxial shear apparatus and two different fault gouges, homogeneous quartz powder and heterogeneous anhydrite/dolomite mixture. We measure fine details of fault slip to resolve the slip velocity time history and volumetric deformation that, coupled with an analysis of the resulting microstructure, allow us to infer the mechanical processes at play. Our results show that slow slip events can be generated for both fault gouges when k~k<sub>c</sub> with similar values of breakdown work. The shear fabric exerts a strong influence during the co-seismic breakdown stage of instabilities. In quartz, where most of the slip occurs on a localized (1 µm) slipping surface, the peak slip velocity is attained near the final stage of friction breakdown and therefore a relevant amount of the mechanical work is absorbed during slip acceleration to peak slip velocity. In anhydrite/dolomite mixture, the peak slip velocity is suddenly reached after a relatively small drop in friction, accompanied by fault dilation, implying that most of the mechanical work is absorbed during slip deceleration. For anhydrite/dolomite mixture these results are likely related to heterogeneous slip distribution along the observed foliation. Taken together these observations suggest that the mechanics of slow slip events depends on shear zone fabric. The slip velocity function contains the necessary dynamic information to characterize the evolution of shear stress.</p> <p>The data are uploaded are structured as follow:</p> <p>1) a .txt file of the datafile that is recorded from the machine (raw data)</p> <p>2) a reduction file (_r) that is used to elaborate the raw data</p> <p>3) a file in .txt format containing the elaborated data (data_rp) </p> <p>The data are analyzed using rawPy that can be found at <a href="https://github.com/marcoscuderi/rawPy">https://github.com/marcoscuderi/rawPy</a></p> <p>For any additional information please do not hesitate to contact the corresponding author Marco Maria Scuderi at marco.scuderi@uniroma1.it.</p>
Simulation Results in the Paper "Propagation of Slow Slip Events on Rough Faults: Clustering, Back Propagation, and Re-rupturing" [Dataset]
<p>Data file "simulations.mat" contains the 5 simulations of slow slip events on flat or rough faults. </p> <table> <tbody> <tr> <td>structure array</td> <td>description</td> <td>reference</td> </tr> <tr> <td>s0</td> <td> 2.5 km long flat fault</td> <td>Fig. 2b</td> </tr> <tr> <td>s1</td> <td>2.5 km long rough fault</td> <td>Fig. 2c</td> </tr> <tr> <td>s2</td> <td>10 km long rough fault</td> <td>Fig. 5</td> </tr> <tr> <td>s3</td> <td>10 km long fractal fault</td> <td>Fig. 7</td> </tr> </tbody> </table> <p>structure array consists of:</p> <p>t: time (s)</p> <p>x: distance (m)</p> <p>v: slip rate (m/s)</p> <p>slip: accumulated slip (m)</p> <p>tau: shear stress (Pa)</p> <p>sigma: normal stress (Pa)</p> <p>notes: description</p> <p> </p> <p>Data file "catalog.mat" contains 3 simulated slow slip events' catalogs on flat and rough faults, c0, c1, and c2, in Fig. 4a, 4b, and 4c, respectively.</p> <p>It consists of:</p> <p>l: rupture length (m)</p> <p>time: time (s)</p> <p>notes: description</p>
Synthetic dataset and prediction files for the paper "Denoising of Geodetic Time Series Using Spatiotemporal Graph Neural Networks: Application to Slow Slip Event Extraction", by Costantino et al. (2024)
<p>Synthetic database used for training and evaluation of SSEdenoiser</p>
Shallow Slow Slip Events Identified Offshore the Osa Peninsula in Southern Costa Rica from GNSS Time Series
<p>Using new continuous GNSS time series from the region, we identify 5 distinct shallow SSEs that occurred immediately offshore and beneath the Osa peninsula: an event detected by one site in 2013, and two events occurring in close succession in both 2018 and 2022 detected by multiple stations, indicating a preliminary recurrence interval of ~4-5 years. While SSEs have been observed to the north at Nicoya, this is their first documentation in southern Costa Rica. Modeled slip distributions of the 2018 and 2022 events indicate that they ruptured the same or overlapping patches of the plate interface, nearly at the trench, updip of historic earthquakes including the 1983 Mw 7.4 Osa event. Immediately offshore, the estimated cumulative slip from the 2018 and 2022 events is sufficient to close the slip deficit from tectonic loading over the recurrence interval, likely influencing the magnitude and spatial slip distribution of future large ruptures.</p>
Shallow Slow Slip Events Identified Offshore the Osa Peninsula in Southern Costa Rica from GNSS Time Series
<p>Using new continuous GNSS time series from the region, we identify 5 distinct shallow SSEs that occurred immediately offshore and beneath the Osa peninsula: an event detected by one site in 2013, and two events occurring in close succession in both 2018 and 2022 detected by multiple stations, indicating a preliminary recurrence interval of ~4-5 years. While SSEs have been observed to the north at Nicoya, this is their first documentation in southern Costa Rica. Modeled slip distributions of the 2018 and 2022 events indicate that they ruptured the same or overlapping patches of the plate interface, nearly at the trench, updip of historic earthquakes including the 1983 Mw 7.4 Osa event. Immediately offshore, the estimated cumulative slip from the 2018 and 2022 events is sufficient to close the slip deficit from tectonic loading over the recurrence interval, likely influencing the magnitude and spatial slip distribution of future large ruptures.</p>
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