Prospective evaluation of multiplicative hybrid earthquake forecasting models in California

The Regional Earthquake Likelihood Models (RELM) experiment, conducted within the Collaboratory for the Study of Earthquake Predictability (CSEP), showed that the smoothed seismicity (HKJ) model by Helmstetter et al. was the most informative time-independent earthquake model in California during the 2006–2010 evaluation period. The diversity of competing forecast hypotheses and geophysical data sets used in RELM was suitable for combining multiple models that could provide more informative earthquake forecasts than HKJ. Thus, Rhoades et al. created multiplicative hybrid models that involve the HKJ model as a baseline and one or more conjugate models. In retrospective evaluations, some hybrid models showed significant information gains over the HKJ forecast. Here, we prospectively assess the predictive skills of 16 hybrids and 6 original RELM forecasts at a 0.05 significance level, using a suite of traditional and new CSEP tests that rely on a Poisson and a binary likelihood function. In addition, we include consistency test results at a Bonferroni-adjusted significance level of 0.025 to address the problem of multiple tests. Furthermore, we compare the performance of each forecast to that of HKJ. The evaluation data set contains 40 target events recorded within the CSEP California testing region from 2011 January 1 to 2020 December 31, including the 2016 Hawthorne earthquake swarm in southwestern Nevada and the 2019 Ridgecrest sequence. Consistency test results show that most forecasting models overestimate the number of earthquakes and struggle to explain the spatial distribution of epicenters, especially in the case of seismicity clusters. The binary likelihood function significantly reduces the sensitivity of spatial log-likelihood scores to clustering, however; most models still fail to adequately describe spatial earthquake patterns. Contrary to retrospective analyses, our prospective test results show that none of the models are significantly more informative than the HKJ benchmark forecast, which we interpret to be due to temporal instabilities in the fit that forms hybrids. These results suggest that smoothing high-resolution, small earthquake data remains a robust method for forecasting moderate-to-large earthquakes over a period of 5–15 yr in California.This project has received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (grant agreement no. 821115, Real-time earthquake rIsk reduction for a reSilient Europe (RISE), http://www.rise-eu.org). Additionally, this research was supported by the Southern California Earthquake Center (contribution no. 11011). SCEC is funded by NSF Cooperative agreement EAR-1600087 and USGS Cooperative agreement G17AC00047

Pseudo-prospective Evaluation of UCERF3-ETAS Forecasts During the 2019 Ridgecrest Sequence

The 2019 Ridgecrest sequence provides the first opportunity to evaluate Uniform California Earthquake Rupture Forecast v.3 with epidemic‐type aftershock sequences (UCERF3‐ETAS) in a pseudoprospective sense. For comparison, we include a version of the model without explicit faults more closely mimicking traditional ETAS models (UCERF3‐NoFaults). We evaluate the forecasts with new metrics developed within the Collaboratory for the Study of Earthquake Predictability (CSEP). The metrics consider synthetic catalogs simulated by the models rather than synoptic probability maps, thereby relaxing the Poisson assumption of previous CSEP tests. Our approach compares statistics from the synthetic catalogs directly against observations, providing a flexible approach that can account for dependencies and uncertainties encoded in the models. We find that, to the first order, both UCERF3‐ETAS and UCERF3‐NoFaults approximately capture the spatiotemporal evolution of the Ridgecrest sequence, adding to the growing body of evidence that ETAS models can be informative forecasting tools. However, we also find that both models mildly overpredict the seismicity rate, on average, aggregated over the evaluation period. More severe testing indicates the overpredictions occur too often for observations to be statistically indistinguishable from the model. Magnitude tests indicate that the models do not include enough variability in forecasted magnitude‐number distributions to match the data. Spatial tests highlight discrepancies between the forecasts and observations, but the greatest differences between the two models appear when aftershocks occur on modeled UCERF3‐ETAS faults. Therefore, any predictability associated with embedding earthquake triggering on the (modeled) fault network may only crystalize during the presumably rare sequences with aftershocks on these faults. Accounting for uncertainty in the model parameters could improve test results during future experiments.Maximilian J. Werner and Warner Marzocchi received funding from the European Union's Horizon 2020 research and innovation program (Number 821115, RISE: Real‐Time Earthquake Risk Reduction for a Resilient Europe). This research was supported by the Southern California Earthquake Center (SCEC; Contribution Number 10082). SCEC is funded by National Science Foundation (NSF) Cooperative Agreement EAR‐1600087 and the U.S. Geological Survey (USGS) Cooperative Agreement G17AC00047

The Forecasting Skill of Physics‐Based Seismicity Models during the 2010–2012 Canterbury, New Zealand, Earthquake Sequence

The static coulomb stress hypothesis is a widely known physical mechanism for earthquake triggering and thus a prime candidate for physics-based operational earthquake forecasting (OEF). However, the forecast skill of coulomb-based seismicity models remains controversial, especially compared with empirical statistical models. A previous evaluation by the Collaboratory for the Study of Earthquake Predictability (CSEP) concluded that a suite of coulomb-based seismicity models were less informative than empirical models during the aftershock sequence of the 1992 Mw 7.3 Landers, California, earthquake. Recently, a new generation of coulomb-based and coulomb/statistical hybrid models were developed that account better for uncertainties and secondary stress sources. Here, we report on the performance of this new suite of models compared with empirical epidemic-type aftershock sequence (ETAS) models during the 2010-2012 Canterbury, New Zealand, earthquake sequence. Comprising the 2010 M 7.1 Darfield earthquake and three subsequent M = 5:9 shocks (including the February 2011 Christchurch earthquake), this sequence provides a wealth of data (394 M = 3:95 shocks). We assessed models over multiple forecast horizons (1 day, 1 month, and 1 yr, updated after M = 5:9 shocks). The results demonstrate substantial improvements in the coulomb-based models. Purely physics-based models have a performance comparable to the ETAS model, and the two coulomb/statistical hybrids perform better or similar to the corresponding statistical model. On the other hand, an ETAS model with anisotropic (fault-based) aftershock zones is just as informative. These results provide encouraging evidence for the predictive power of coulomb-based models. To assist with model development, we identify discrepancies between forecasts and observations. © 2018 Seismological Society of America. All rights reserved

Validating Nevada ShakeZoning Predictions of Las Vegas Basin Response against 1992 Little Skull Mountain Earthquake Records

Over the last two years, the Nevada Seismological Laboratory has developed and refined Nevada ShakeZoning (NSZ) procedures to characterize earthquake hazards in the Intermountain West. Simulating the ML 5.6–5.8 Little Skull Mountain (LSM) earthquake validates the results of the NSZ process and the ground shaking it predicts for Las Vegas Valley (LVV). The NSZ process employs a physics?based finite?difference code from Lawrence Livermore Laboratory to compute wave propagation through complex 3D earth models. Computing limitations restrict the results to low frequencies of shaking. For this LSM regional model the limitation is to frequencies of 0.12 Hz, and below. The Clark County Parcel Map, completed in 2011, is a critical and unique geotechnical data set included in NSZ predictions for LVV. Replacing default geotechnical velocities with the Parcel Map velocities in a sensitivity test produced peak ground velocity amplifications of 5%–11% in places, even at low frequencies of 0.1 Hz. A detailed model of LVV basin?floor depth and regional basin?thickness models derived from gravity surveys by the U.S. Geological Survey are also important components of NSZ velocity?model building. In the NSZ?predicted seismograms at 0.1 Hz, Rayleigh?wave minus P?wave (R?P) differential arrival times and the pulse shapes of Rayleigh waves correlate well with the low?pass filtered LSM recordings. Importantly, peak ground velocities predicted by NSZ matched what was recorded, to be closer than a factor of two. Observed seismograms within LVV show longer durations of shaking than the synthetics, appearing as horizontally reverberating, 0.2 Hz longitudinal waves beyond 60 s after Rayleigh?wave arrival. Within the basins, the current velocity models are laterally homogeneous below 300 m depth, leading the 0.1 Hz NSZ synthetics to show insufficient shaking durations of only 30–40 s

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 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 ..

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 ...

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

Effects of inspiratory impedance on the carotid-cardiac baroreflex response in humans

We were interested in a therapeutic device designed to increase carotid-cardiac baroreflex sensitivity (BRS) since high BRS is associated with a lower risk for development of hypotension in humans with experimentally-induced central hypovolemia. We hypothesized that spontaneous breathing through an impedance threshold device (ITD) designed to increase negative intrathoracic pressure during inspiration and elevate arterial blood pressure would acutely increase BRS in humans. We tested this hypothesis by measuring heart rate (HR), systolic (SBP) and diastolic (DBP) blood pressures, and carotid-cardiac BRS in 10 female and 10 male subjects breathing through a face mask at three separate ITD conditions: (a) 6 cm H(2)O; (b) 12 cm H(2)O; and (c) a control (0 cm H(2)O). HR was increased (P = 0. 013) from 64 +/- 3 bpm during control to 68 +/- 3 bpm at 6 cm H(2)O ITD and 71 +/- 4 bpm at 12 cm H(2)O ITD breathing conditions. During ITD breathing, BRS was not altered but responses were shifted to higher arterial pressures. However, SBP and DBP were elevated for both the 6 and 12 cm H(2)O conditions compared to the 0 cm H(2)O condition, but returned to control (sham) levels by 30 minutes after cessation of ITD breathing. There were no gender effects for BRS or any hemodynamic responses to breathing through the ITD. We conclude that breathing with inspiratory impedance at relatively low pressures can increase baseline arterial blood pressure, i. e., reset the operational point for SBP on the baroreflex stimulus-response relationship, in healthy subjects. This resetting of the cardiac baroreflex may represent a mechanism that allows blood pressure to increase without a reflex-mediated reduction in HR