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Operational Earthquake Forecasting: Proposed Guidelines for Implementation Southern California Earthquake Center Operational Earthquake Forecasting: Proposed Guidelines for Implementation Thomas H. Jordan Director, Southern California Earthquake Center S33D-01, AGU Meeting 14 December 2010 Southern California Earthquake Center Operational Earthquake Forecasting Authoritative information about the time dependence of seismic hazards to help communities prepare for potentially destructive earthquakes. • Seismic hazard changes with time – Earthquakes release energy and suddenly alter the tectonic forces that will eventually cause future earthquakes • Statistical models of earthquake interactions can capture many of the short-term temporal and spatial features of natural seismicity – Excitation of aftershocks and other seismic sequences • Such models can use regional seismicity to estimate short-term changes in the probabilities of future earthquakes Southern California Earthquake Center Operational Earthquake Forecasting Authoritative information about the time dependence of seismic hazards to help communities prepare for potentially destructive earthquakes. • What are the performance characteristics of current short-term forecasting methodologies? – Probability (information) gain problem • How should forecasting methods be qualified for operational use? – Validation problem • How should short-term forecasts be integrated with long-term forecasts? – Consistency problem • How should low-probability, short-term forecasts be used in decision-making related to civil protection? – Valuation problem Southern California Earthquake Center Supporting Documents • Operational Earthquake Forecasting: State of Knowledge and Guidelines for Implementation – Final Report of the International Commission on Earthquake Forecasting for Civil Protection (T. H. Jordan, chair), Dipartimento della Protezione Civile, Rome, Italy, 79 pp., December, 2010. • Operational Earthquake Forecasting: Some Thoughts on Why and How – T. H. Jordan & L. M. Jones (2010), Seismol. Res. Lett., 81, 571-574, 2010. Southern California Earthquake Center Prediction vs. Forecasting • An earthquake forecast gives a probability that a target event will occur within a space-time domain • An earthquake prediction is a deterministic statement that a target event will occur within a space-time domain Rupture Probability on San RTP Alarm for California M 6.4, Andreas System (WGCEP, 2007) 15 Nov 2004-14 Aug 2005 (Keilis-Borok et al., 2004) Southern California Earthquake Center Prediction vs. Forecasting 1.0 P < 0.2 P > 0.8 0.5 Shannon Entropy 0 0 0.5 1.0 Earthquake Probability For operational purposes, • deterministic prediction is only useful in a high-probability environment • probabilistic forecasting can be useful in a low-probability environment Southern California Earthquake Center Operational Forecasting in California • Organizations – USGS - National Earthquake Prediction Evaluation Council (NEPEC) – CalEMA - California Earthquake Prediction Evaluation Council (CEPEC) • Operational forecasting tools – Long-term models (WGCEP models; e.g., UCERF2) – Short-term models (Reasenberg-Jones, STEP, ETAS, Agnew-Jones) • Notification protocols – Southern San Andreas Working Group (1991) – California Integrated Seismic Network notifications • For M 5 events, probability of M 5 aftershocks and expected number of M 3 aftershocks Southern California Earthquake Center Long-Term Earthquake Probability Models Uniform California Earthquake Rupture Forecast (UCERF2) 1680 1857 UCERF2 30-yr Gain 5-yr Gain 1906 0 1 2 3 Probability Gain UCERF2 1-day probability for M > 7 Coachella rupture: -5 P = 3 x 10 UCERF2 ratio of time-dependent to time-independent participation probabilities for M 6.7 (WGCEP, 2007) Southern California Earthquake Center Short-Term Earthquake Probability (STEP) Model +- 0 12113 hour monthshourmonth hours Gerstenberger et al. (2005) Probability of Exceeding MMI VI http://earthquake.usgs.gov/earthquakes/step/ 2004 Parkfield Earthquake Southern California Earthquake Center Short-Term Earthquake Probability (STEP) Model + 1 hour STEP 1-day probability gain for MMI > VI shaking: G > 100 Gerstenberger et al. (2005) Probability of Exceeding MMI VI http://earthquake.usgs.gov/earthquakes/step/ 2004 Parkfield Earthquake Southern California Earthquake Center Summary of Probability Gains Method Gain Pmax(3 day) Prospectively Factor SAF-Coachella validated? Long-term renewal 1-2 1 x 10–4 No Medium-term seismicity 2-4 2 x 10–4 Yes patterns Short-term STEP/ETAS 10-100 3 x 10–3 Yes Short-term empirical 100-1000 3 x 10–2 No foreshock probability • The probability gains of short-term, seismicity-based forecasts can be high, but the absolute probabilities of large earthquakes typically remain low, even in seismically active areas, such as California. Southern California Earthquake Center Operational Forecasting in California • W. H. Bakun et al., Parkfield, California, Earthquake Prediction Scenarios and Response Plans. USGS OFR 87-192, 1987. • Southern San Andreas Working Group, Short-Term Earthquake Hazard Assessment for the San Andreas Fault in Southern California, USGS OFR 91-32, 1991. * # instances many ~10 2 & ')(#*(.! # $/*+.% " Southern California Earthquake Center Operational Forecasting in California • Earthquake forecasting in a “low-probability environment” is already operational in California, and the dissemination of forecasting products is becoming more automated – Level-A probability threshold of 25% has never been reached – Level-B threshold of 5-25% has been exceeded only twice (Joshua Tree and Parkfield) • However, procedures are deficient in several respects: – CEPEC has generally relied on generic short-term earthquake probabilities or ad hoc estimates calculated informally, rather than probabilities based on operationally qualified, regularly updated seismicity forecasting systems – Procedures are unwieldy, requiring the scheduling of meetings or telecons, which lead to delayed and inconsistent alert actions – How the alerts are used is quite variable, depending on decisions at different levels of government and among the public Southern California Earthquake Center The Validation Problem • To be fit for operational purposes, short-term forecasting methods should demonstrate reliability and skill with respect to long-term (e.g., time-independent) models – Forecasting methods intended for operational use should be scientifically tested against the appropriate data for reliability and skill, both retrospectively and prospectively • All operational models should be under continuous prospective testing competing time-dependent models – Collaboratory for the Study of Earthquake Predictability (CSEP) provides the infrastructure for this testing Southern California Earthquake Center CSEP Testing Regions & Testing Centers Western Pacific China EU Testing Center SCEC Testing Center ERI Testing Center Testing Center Global Zurich Beijing Tokyo Los Angeles Italy Japan California North-South Seismic Belt GNS Science Testing Center Wellington Testing Center Testing Region New Zealand Upcoming Upcoming Southern California Earthquake Center CSEP Evaluation of Short-Term Models in the California Testing Region (Rhoades T-test, M 3) STEP Model IG = 0.3, PG = 1.35/eqk IG = 2.6, PG = 13.5/eqk Reference forecast Information gain per earthquake Southern California Earthquake Center The Consistency Problem • Spatiotemporal consistency is an important issue for dynamic risk management, which often involves trade-offs among multiple targets and time frames • In lieu of physics-based forecasting, consistency must be statistically enforced — a challenge because: – Long-term renewal models are less clustered than Poisson – Short-term triggering models are more clustered than Poisson • Consistency can be lacking if long-term forecasts specify background seismicity rates for the short-term models (e.g., STEP) – Seismicity fluctuations introduced by earthquake triggering can occur on time scales comparable to the recurrence intervals of the largest events • Model development needs to be integrated across all time scales of forecast applicability – Approach adopted by WGCEP for development of UCERF3 Southern California Earthquake Center The Valuation Problem • Earthquake forecasts acquire value through their ability to influence decisions made by users seeking to mitigate seismic risk and improve community resilience to earthquake disasters – Societal value of seismic safety measures based on long-term forecasts has been repeatedly demonstrated – Potential value of protective actions that might be prompted by short-term forecasts is far less clear • Benefits and costs of preparedness actions in high-gain, low- probability situations have not been systematically investigated – Previous work on the public utility of short-term forecasts has anticipated that they would deliver high probabilities of large earthquakes (deterministic prediction) Southern California Earthquake Center The Valuation Problem • Economic valuation is one basis for prioritizing how to allocate the limited resources available for short-term preparedness – In a low-probability environment, only low-cost actions are justified Cost-Benefit Analysis for Binary Decision-Making (e.g., van Stiphout et al., 2010) Suppose cost of protection against loss L is C < L. If the short-term earthquake probability is P, the policy that minimizes the expected expense E: - Protect if P > C/L - Do not protect if P < C/L Then, E = min {C, PL}. • Many factors complicate this rational approach –
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