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Forecasting, Prediction, and Testing David D. Jackson, UCLA

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But 'earthquake on segment' is subjective. ... The next earthquake in a given region and magnitude interval will not be before ... – PowerPoint PPT presentation

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Title: Forecasting, Prediction, and Testing David D. Jackson, UCLA


1
Forecasting, Prediction, and TestingDavid D.
Jackson, UCLA
  • Thanks to Yan Kagan, Yufang Rong, Zheng-kang
    Shen, Ned Field, Daniel Schorlemmer, Matt
    Gerstenberger, John Rundle, Don Turcotte, Volodya
    Kossobokov, Ilya Zaliapin

2
Definitions
  • Forecast specification of the probability per
    unit area, magnitude, time, focal mechanism,
    etc.
  • Prediction special case of forecasting in which
    the probability in some region is much higher
    than normal, and high enough to justify
    exceptional .
  • Notes a prediction must be temporary it also
    requires a definition of normal (i.e., a null
    hypothesis).

3
Why forecast and test
  • Test hypotheses of earthquake physics
  • Quasiperiodic characteristic earthquakes
  • Magnitudes limited by fault geometry
  • Moment balance (tectonic in seismic out)
  • Earthquake rate proportional to stress rate
  • Inform decisions about earthquake risk
  • Facility locations, building codes, insurance
    rates, retrofit, etc.
  • Inspire envy

4
Some testable statements
  • At least one event will occur within given
    region, time interval, and magnitude interval
    with probability p.
  • For many small intervals, this is RELM type
    forecast
  • Replace region by segment and have WG88 type
    forecast. But earthquake on segment is
    subjective.
  • N events will occur within given region, time
    interval, and magnitude interval with probability
    p(N).
  • The largest event in given region and time
    interval will be m, with probability p(m). My
    recommendation for a usable and stable forecast.
  • If an event occurs in region 1, time interval 1,
    and magnitude interval 1, it will be in the
    included region 2, time interval 2, and magnitude
    interval 2 with probability p. (KB type
    forecast)
  • The next earthquake in a given region and
    magnitude interval will not be before time t with
    probability p(t). Replace region by segment and
    have WG88 type forecast.

5
What we can and cant do now
  • Can
  • Forecast 90 of quakes in 10 of area.
  • Predict aftershocks
  • Forecast mag-freq relationship for N(m)10.
  • Maybe can
  • Forecast earthquake rate from deformation rate.
  • Establish earthquake rate for normal
    conditions
  • Forecast Mmax
  • Cant
  • Predict times of individual earthquakes

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8
Likelihood Testing
  • Simulate catalogs using L(lat,lon)
  • Compute log likelihood function for observed and
    simulated catalogs
  • Sort L values in increasing order, plot order vs
    L.

9
Practical problems in testing
  • Many users many criteria
  • Earthquakes not independent
  • Testing should be rigorous, but also feel
    good.
  • Data on rupture lengths, endpoints of rupture,
    slip distribution, etc., not formalized

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12
Ten-year Prospective Test of Seismic Gap and Null
(Poissonian Smoothed Seismicity) models
Rank zones by decreasing probability of
characteristic earthquake accumulate area,
predicted earthquake number, and actual
earthquake number.
13
Properties of test methods
  • Likelihood ratio test
  • Includes absolute rates
  • Useful for marked point process lat, lon, mag,
    etc.
  • As used, assumes independent events
  • Adaptable to time varying forecasts
  • Could use declustered catalog
  • Gives scalar score
  • Likelihood ratio test on largest event in zone,
    time interval
  • Reduces effect of dependent events
  • May respond to long-term users investors,
    planners
  • Molchan diagram
  • Based on relative rates, as normally used
  • Needs a scalar measure to reject a hypothesis
  • Not convenient for marked point processes need
    to commit to magnitude threshold, e.g.
  • Does not avoid problem of dependent events

14
Testing scheme for elements of risk model
15
Conclusions
  • Many users Many criteria for optimality
  • Absolute rate vs. relative rate
  • Short time vs. long time
  • Big events vs. smaller ones
  • Biggest problem is interdependence of quakes
  • Long term users want stability unconditional
    probabilities
  • Scientists care about interactions conditional
    probabilities
  • Solutions to interdependence
  • Decluster catalog needs model
  • Test using conditional probabilities updated
    automatically
  • Test only largest earthquake in zone.
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