Published September 16, 2022 | Version v2
Dataset Open

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

  • 1. University of Bristol
  • 2. University of Southern California
  • 3. GFZ Postdam
  • 4. GNS Science
  • 5. University of Naples Federico II


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_min lon_max lat_min 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 5.8499e-04 1

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:

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.


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RISE – Real-time Earthquake Risk Reduction for a Resilient Europe 821115
European Commission