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Triggering Models vs. Smoothed Seismicity. Testing region: California Target events: M  ≥ 3.95 Testing period : 2008 -2010 Testing method: T-test. PG = probability gain = P / P 0 IG = information gain = log e ( PG ). STEP model. PG = 1.35/eqk. Reference forecast.

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triggering models vs smoothed seismicity
Triggering Models vs. Smoothed Seismicity

Testing region: California

Target events: M ≥ 3.95

Testing period: 2008-2010

Testing method: T-test

PG = probability gain

= P/P0

IG = information gain

= loge(PG)

STEP model

PG= 1.35/eqk

Reference forecast

PG= 10/eqk

Information gain per earthquake

japan and nz testing regions
Japan and NZ Testing Regions

1 day 3 month 6 month 5 year Total

New Zealand 2 8 1 4 15

darfield aftershock forecasting gerstenberger rhoades
Darfield Aftershock Forecasting(Gerstenberger & Rhoades)

Testing region: New Zealand

Target events: M ≥ 4 (ETAS, PPE-1d), M ≥ 5 (PPE-3m, PPE-5y)

Testing period: 4 Sept 2010 - 8 Mar 2011

Testing method: N-test

Forecast

Nobs = 271

(M ≥ 4)

209 are Darfield aftershocks

Nobs = 17

(M ≥ 5)

Number of earthquakes

darfield aftershock forecasting gerstenberger rhoades1
Darfield Aftershock Forecasting(Gerstenberger & Rhoades)

Testing region: New Zealand

Target events: M ≥ 4 (PPE-1d), M ≥ 5 (PPE-3m, PPE-5y)

Testing period: 4 Sept 2010 - 8 Mar 2011

Testing method: T-test

ETAS model

PG= 99/eqk

Reference forecast

PG= 544/eqk

PG= 1480/eqk

Information gain per earthquake

csep testing results
CSEP Testing Results
  • Comparative evaluations have quickly identified errors in model implementation
    • effective method for model verification (debugging)
  • 5-yr RELM testing program has been effective in ranking long-term forecasting performance for M ≥ 5 target events in California
    • RELM paper by Zechar, Schorlemmer, et al.
  • Aftershock triggering models (e.g., STEP, ETAS) obtain probability gains of 10-1000 relative to seismicity averaging models (e.g. PPE, TripleS)
    • Substantially more information gain can be obtained by updating forecasts more frequently than at 1-day intervals
  • Adaptive triggering models out-perform those with time-independent parameters
    • Gerstenberger’s STEP model currently shows the best short-term performance in California; adaptive models in NZ and Japan are still being evaluated
csep plans
CSEP Plans
  • Monitor the performance of 91 CSEP/Japan and 15 CSEP/NZ forecasting models during the active phases of the Tohoku and Darfield sequences
    • Reduce the updating interval for short-term forecasts from 1 day to 1 hr or less
    • Improve procedures for adapting forecasts to changes in the seismic environment
  • Incorporate forecasting models based on physical hypotheses about earthquake generation
    • e.g., Coulomb stress function, rate/state friction, dynamic vs. static triggering, slow slip events, tidal triggering
    • Expand prospective testing to models based on non-seismic data
  • Evaluate hypotheses critical to forecasting large earthquakes
    • e.g., fault segmentation, maximum magnitude, characteristic earthquakes, strongly coupled seismic gaps
    • Expand global testing program
    • Include model classes for legacy methods; e.g., M8/MSc
  • Develop CSEP capabilities to support operational earthquake forecasting
    • Prospectively test candidate forecasting procedures
    • Unify forecasting across temporal and spatial scales (e.g. long-term & short-term)
    • Reduce testing latency by modeling catalog completeness and accuracy
    • Expand retrospective testing over the entire history of instrumental catalogs
    • Initiate model testing using recorded ground motions
  • Support other prospective testing activities, including earthquake early warning