Seismic waveforms of fluid-induced seismicity from the 2018 hydraulic stimulation campaign at the OTN-3 well, Helsinki, Finland

This data publication contains seismic waveform data of 507 earthquakes recorded during the St1 Deep Heat project in June and July 2018, where the 6.1 km deep OTN-3 well near Helsinki, Finland, was hydraulically stimulated over 49 days (Kwiatek et al., 2019). The waveforms were recorded on a surrounding seismic monitoring network consisting of 12 stations, deployed at epicentral distances between 0.6 to 8.2 km and at depths between 0.23 to 1.15 km. Each station consists of three-component, 4.5 Hz, Sunfull PSH geophones, sampling at 500 Hz. The 507 earthquakes analysed were chosen from the relocated event catalogue by Leonhardt et al. (2021a). The dataset is supplementary material to the Geophysical Research Letters research article of Holmgren et al. (2022), which applied the Empirical Green’s Function technique to examine microseismic rupture behaviour at the Helsinki site

Consistency test scores for aftershock+mainshock RELM forecasts

Summary Files are transcribed from Zechar et al. (2013) into comma separated values (csv) files. The consistency test scores are shown in the electronic supplement table S4 and the catalog is found in Table 1 of the main text. Reference Zechar, J. D., D. Schorlemmer, M. J. Werner, M. C. Gerstenberger, D. A. Rhoades, and T. H. Jordan (2013). Regional Earthquake Likelihood Models I: First-Order Results, Bulletin of the Seismological Society of America 103 787-798.

Mainshock+aftershock forecasts from Regional Earthquake Likelihood Models (RELM) experiment

Contains mainshock+aftershock forecasts produced by various members of the working group for the development of Regional Earthquake Likelihood Models. These forecasts were obtained from the Collaboratory of the Study of Earthquake Predictability (CSEP) testing center hosted by the Southern California Earthquake Center at the University of Southern California. Forecasts are described by the following publications Helmstetter et al. (2007) with aftershocksKagan et al. (2007)Shen et al. (2007)Bird & Liu (2007)Ebel et al. (2007) with aftershocks Forecasts are stored in tab separated value files with the following fields (the first row of data is shown as an example): LON_0 LON_1 LAT_0 LAT_1 DEPTH_0 DEPTH_1 MAG_0 MAG_1 RATE FLAG -125.4 -125.3 40.1 40.2 0.0 30.0 4.95 5.05 5.8499099999999998e-04 1 References Bird, P., and Z. Liu (2007). Seismic Hazard Inferred from Tectonics: California, Seismological  Research Letters 78 37-48. Ebel, J. E., D. W. Chambers, A. L. Kafka, and J. A. Baglivo (2007). Non-Poissonian Earthquake Clustering and the Hidden Markov Model as Bases for Earthquake Forecasting in California, Seismological  Research Letters 78 57-65. Helmstetter, A., Y. Y. Kagan, and D. D. Jackson (2007). High-resolution Time-independent Grid-based Forecast for M >= 5 Earthquakes in California, Seismological  Research Letters 78 78-86. Kagan, Y. Y., D. D. Jackson, and Y. Rong (2007). A Testable Five-Year Forecast of Moderate and Large Earthquakes in Southern California Based on Smoothed Seismicity, Seismological  Research Letters 78 94-98. Shen, Z.-K., D. D. Jackson, and Y. Y. Kagan (2007). Implications of Geodetic Strain Rate for Future Earthquakes, with a Five-Year Forecast of M5 Earthquakes in Southern California, Seismological  Research Letters 78 116-120

Quadtree aggregations of TEAM forecast model

The Tectonic Earthquake Activity Model (TEAM) is a geodetic-based model using Version 2.1 of the Global Strain Rate Map (GSRM2.1; Kreemer et al., 2014), while the World Hybrid Earthquake Estimates based on Likelihood scores (WHEEL) is a model obtained from a multiplicative log-linear combination of TEAM with the Smoothed Seismicity (KJSS) model of Kagan and Jackson (2011). The forecast model is proposed and described in the following publication: Bayona, J.A., Savran, W., Strader, A., Hainzl, S., Cotton, F. and Schorlemmer, D., 2021. Two global ensemble seismicity models obtained from the combination of interseismic strain measurements and earthquake-catalogue information. Geophysical Journal International, 224(3), pp.1945-1955. Multi-resolution grids are generated using Quadtree. The grids are generated based on earthquake catalog data and strain data points.  Each file in the repository represents a forecast aggregated on a particular grid. The forecast file naming is derived from the criteria used to generate the grid. For example, 'N' stands for number earthquakes, 'SN' stands for Strain data points, and 'L' stands for maximum zoom-level allowed for the grid.  The forecast is represented in the following format:   Tiledepth_mindepth_max5.956.056.156.25 ...'000'0700.0071500.006040.004850.00323 ...

Quadtree aggregations of WHEEL forecast model

World Hybrid Earthquake Estimates based on Likelihood scores (WHEEL) is a model obtained from a multiplicative log-linear combination of TEAM with the Smoothed Seismicity (KJSS) model of Kagan and Jackson (2011). The forecast model is proposed and described in the following publication: Bayona, J.A., Savran, W., Strader, A., Hainzl, S., Cotton, F. and Schorlemmer, D., 2021. Two global ensemble seismicity models obtained from the combination of interseismic strain measurements and earthquake-catalogue information. Geophysical Journal International, 224(3), pp.1945-1955. Multi-resolution grids are generated using Quadtree. The grids are generated based on earthquake catalog data and strain data points.  Each file in the repository represents a forecast aggregated on a particular grid. The forecast files are naming is derived from the criteria used to generate the grid. For example, 'N' stands for number earthquakes, 'SN' stands for Strain data points, and 'L' stands for maximum zoom-level allowed for the grid.  The forecast is represented in the following format: Tiledepth_mindepth_max5.956.056.156.25 ... '000'0.070.00.007150.006930.006280.00573 ..

Two global ensemble M5.95+ seismicity models obtained from the combination of interseismic strain rates and earthquake-catalogue data

Contains two global earthquake-rate forecasts developed by Bayona et al. (2021) to be prospectively evaluated by the Collaboratory for the Study of Earthquake Predictability (CSEP). The Tectonic Earthquake Activity Model (TEAM) is a geodetic-based model using Version 2.1 of the Global Strain Rate Map (GSRM2.1; Kreemer et al., 2014), while the World Hybrid Earthquake Estimates based on Likelihood scores (WHEEL) is a model obtained from a multiplicative log-linear combination of TEAM with the Smoothed Seismicity (KJSS) model of Kagan and Jackson (2011). Earthquake densities are expressed as number of M5.95+ events per unit 0.1o cell per year. The forecasts are stored in tab separated value files, with the following fields (the first row of data is shown as an example): lon_minlon_maxlat_minlat_maxdepth_mindepth_max5.956.05...-180.0-179.9-90.0-89.90.070.04.95e-113.97e-11... Data and forecasts are described in detail in the following publications: Bayona, J.A., Savran, W., Strader, A., Hainzl, S., Cotton, F. and Schorlemmer, D., 2021. Two global ensemble seismicity models obtained from the combination of interseismic strain measurements and earthquake-catalogue information. Geophysical Journal International, 224(3), pp.1945-1955. Kreemer, C., Blewitt, G. and Klein, E.C., 2014. A geodetic plate motion and Global Strain Rate Model. Geochemistry, Geophysics, Geosystems, 15(10), pp.3849-3889. Kagan, Y.Y. and Jackson, D.D., 2011. Global earthquake forecasts. Geophysical Journal International, 184(2), pp.759-776

Mineralogical and geochemical data of two weathering profiles in a Mediterranean and a humid climate region of the Chilean Coastal Cordillera

This publication provides mineralogical and geochemical data of two 6-m-deep weathering profiles formed from granitic rock. They are located in different climate zones (Mediterranean and humid) and are close to the national parks of La Campana and Nahuelbuta in the Chilean Coastal Cordillera. Additional rock samples from adjacent boreholes were used to relate the regolith to the bedrock. The profiles were sampled in February and March 2020 as part of the German Science Foundation (DFG) priority research program SPP-1803 “EarthShape: Earth Surface Shaping by Biota”. The goal of this project is to obtain a holistic view on the interplay of the geosphere and the biosphere under different climatic conditions and to investigate weathering mechanisms. The aim of this publication is to provide the data basis for understanding the weathering processes that control the development of the profiles in relation to different climatic conditions. To this end, we measured the geochemistry with X-ray fluorescence, extracted Fe, Al and Si with oxalate/dithionite, determined the grain sizes by wet sieving and pipetting, measured the magnetic susceptibility, and analysed the mineral content of bulk samples and clay fractions with X-ray diffraction. The data are compiled in one Excel file and all results of the X-ray diffraction measurements are available as RAW- and TXT files

Global and regional long-term M4.95+ seismicity forecasts undergoing prospective evaluation

Contains a stationary M5.95+ seismicity forecast derived from the Global Earthquake Activity Rate (GEAR1) model of Bird et al. (2015) and nineteen time-invariant M4.95+ earthquake forecasts participating in forecast experiments conducted by the Collaboratory for the Study of Earthquake Predictability (CSEP) in California, New Zealand, and Italy.  Ten additional forecast files are included to properly perform comparative tests. Earthquake rates are expressed as number of M4.95+ earthquakes per 0.1o cell per year. Forecasts are stored in tab separated values files with the following fields (the first row is shown as an example): lon_minlon_maxlat_minlat_1depth_0depth_1mag_0mag_1rateflag-125.4-125.340.140.20.030.04.955.055.8499e-041 The data, forecasts, and tests are described in detail in the following publications and the references contained therein: Bayona, J.A., Savran, W.H., Iturrieta, P., Gerstenberger, M.C., Marzocchi, W., Schorlemmer, D., and Werner, M.J., Are Regionally Calibrated Seismicity Models more Informative than Global Models? Insights from California, New Zealand, and Italy. in review. Bayona, J.A., Savran, W.H., Rhoades, D.A. and Werner, M.J., 2022. Prospective evaluation of multiplicative hybrid earthquake forecasting models in California. Geophysical Journal International, 229(3), pp.1736-1753. Bird, P., Jackson, D.D., Kagan, Y.Y., Kreemer, C. and Stein, R.S., 2015. GEAR1: A Global Earthquake Activity Rate Model Constructed from Geodetic Strain Rates and Smoothed SeismicityGEAR1: A Global Earthquake Activity Rate Model Constructed from Geodetic Strain Rates and Smoothed Seismicity. Bulletin of the Seismological Society of America, 105(5), pp.2538-2554. Marzocchi W, Schorlemmer D, Wiemer S. Preface. Ann. Geophys. [Internet]. 2010Nov.5 [cited 2022Sep.16];53(3):III-VIII. Available from: https://www.annalsofgeophysics.eu/index.php/annals/article/view/4851 Rhoades, D.A., Christophersen, A., Gerstenberger, M.C., Liukis, M., Silva, F., Marzocchi, W., Werner, M.J. and Jordan, T.H., 2018. Highlights from the first ten years of the New Zealand earthquake forecast testing center. Seismological Research Letters, 89(4), pp.1229-1237. Savran, W.H., Bayona, J.A., Iturrieta, P., Asim, K.M., Bao, H., Bayliss, K., Herrmann, M., Schorlemmer, D., Maechling, P.J. and Werner, M.J., 2022. pycsep: A python toolkit for earthquake forecast developers. Seismological Society of America, 93(5), pp.2858-2870. Schorlemmer, D., Gerstenberger, M.C., Wiemer, S., Jackson, D.D. and Rhoades, D.A., 2007. Earthquake likelihood model testing. Seismological Research Letters, 78(1), pp.17-29. Werner, M.J., Zechar, J.D., Marzocchi, W. and Wiemer, S., 2010. Retrospective evaluation of the five-year and ten-year CSEP-Italy earthquake forecasts. arXiv preprint arXiv:1003.1092. Zechar, J.D., Gerstenberger, M.C. and Rhoades, D.A., 2010. Likelihood-based tests for evaluating space–rate–magnitude earthquake forecasts. Bulletin of the Seismological Society of America, 100(3), pp.1184-1195. Zechar, J.D., Schorlemmer, D., Werner, M.J., Gerstenberger, M.C., Rhoades, D.A. and Jordan, T.H., 2013. Regional earthquake likelihood models I: First‐order results. Bulletin of the Seismological Society of America, 103(2A), pp.787-798

Global and regional long-term M4.95+ seismicity forecasts undergoing prospective evaluation

Contains a stationary M5.95+ seismicity forecast derived from the Global Earthquake Activity Rate (GEAR1) model of Bird et al. (2015) and nineteen time-invariant M4.95+ earthquake forecasts participating in forecast experiments conducted by the Collaboratory for the Study of Earthquake Predictability (CSEP) in California, New Zealand, and Italy.  Ten additional forecast files are included to properly perform comparative tests. Earthquake rates are expressed as number of M4.95+ earthquakes per 0.1o cell per year. Forecasts are stored in tab separated values files with the following fields (the first row is shown as an example): lon_minlon_maxlat_minlat_1depth_0depth_1mag_0mag_1rateflag-125.4-125.340.140.20.030.04.955.055.8499e-041 The data, forecasts, and tests are described in detail in the following publications and the references contained therein: Bayona, J.A., Savran, W.H., Iturrieta, P., Gerstenberger, M.C., Marzocchi, W., Schorlemmer, D., and Werner, M.J., Are Regionally Calibrated Seismicity Models more Informative than Global Models? Insights from California, New Zealand, and Italy. in review. Bayona, J.A., Savran, W.H., Rhoades, D.A. and Werner, M.J., 2022. Prospective evaluation of multiplicative hybrid earthquake forecasting models in California. Geophysical Journal International, 229(3), pp.1736-1753. Bird, P., Jackson, D.D., Kagan, Y.Y., Kreemer, C. and Stein, R.S., 2015. GEAR1: A Global Earthquake Activity Rate Model Constructed from Geodetic Strain Rates and Smoothed SeismicityGEAR1: A Global Earthquake Activity Rate Model Constructed from Geodetic Strain Rates and Smoothed Seismicity. Bulletin of the Seismological Society of America, 105(5), pp.2538-2554. Marzocchi W, Schorlemmer D, Wiemer S. Preface. Ann. Geophys. [Internet]. 2010Nov.5 [cited 2022Sep.16];53(3):III-VIII. Available from: https://www.annalsofgeophysics.eu/index.php/annals/article/view/4851 Rhoades, D.A., Christophersen, A., Gerstenberger, M.C., Liukis, M., Silva, F., Marzocchi, W., Werner, M.J. and Jordan, T.H., 2018. Highlights from the first ten years of the New Zealand earthquake forecast testing center. Seismological Research Letters, 89(4), pp.1229-1237. Savran, W.H., Bayona, J.A., Iturrieta, P., Asim, K.M., Bao, H., Bayliss, K., Herrmann, M., Schorlemmer, D., Maechling, P.J. and Werner, M.J., 2022. pycsep: A python toolkit for earthquake forecast developers. Seismological Society of America, 93(5), pp.2858-2870. Schorlemmer, D., Gerstenberger, M.C., Wiemer, S., Jackson, D.D. and Rhoades, D.A., 2007. Earthquake likelihood model testing. Seismological Research Letters, 78(1), pp.17-29. Werner, M.J., Zechar, J.D., Marzocchi, W. and Wiemer, S., 2010. Retrospective evaluation of the five-year and ten-year CSEP-Italy earthquake forecasts. arXiv preprint arXiv:1003.1092. Zechar, J.D., Gerstenberger, M.C. and Rhoades, D.A., 2010. Likelihood-based tests for evaluating space–rate–magnitude earthquake forecasts. Bulletin of the Seismological Society of America, 100(3), pp.1184-1195. Zechar, J.D., Schorlemmer, D., Werner, M.J., Gerstenberger, M.C., Rhoades, D.A. and Jordan, T.H., 2013. Regional earthquake likelihood models I: First‐order results. Bulletin of the Seismological Society of America, 103(2A), pp.787-798