Mathematics – Probability
Scientific paper
Feb 2011
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2011geoji.184..759k&link_type=abstract
Geophysical Journal International, Volume 184, Issue 2, pp. 759-776.
Mathematics
Probability
2
Probabilistic Forecasting, Probability Distributions, Earthquake Interaction, Forecasting, And Prediction, Seismicity And Tectonics, Statistical Seismology, Dynamics: Seismotectonics
Scientific paper
We have constructed daily worldwide long- and short-term earthquake forecasts. These forecasts specify the earthquake rate per unit area, time and magnitude on a 0.5 degree grid for a global zone region between 75N and 75S latitude (301 by 720 grid cells). We use both the Global Centroid Moment Tensor (GCMT) and Preliminary Determinations of Epicenters (PDE) catalogues. Like our previous forecasts, the new forecasts are based largely on smoothed maps of past seismicity and assume spatial and temporal clustering. The forecast based on the GCMT catalogue, with the magnitude completeness threshold 5.8, includes an estimate of focal mechanisms of future earthquakes and of the mechanism uncertainty. The forecasted tensor focal mechanism makes it possible in principle to calculate an ensemble of seismograms for each point of interest on the Earth's surface. We also introduce a new approach that circumvents the need for focal mechanisms. This permits the use of the PDE catalogue that reliably documents many smaller quakes with a higher location accuracy. The result is a forecast at a higher spatial resolution and down to a magnitude threshold below 5.0. Such new forecasts can be prospectively tested within a relatively short time, such as a few years, because smaller events occur with greater frequency. The forecast's efficiency can be measured by its average probability gains per earthquake compared to the spatially or temporally uniform Poisson distribution. For the short-term forecast the gain is about 2.0 for the GCMT catalogue and 3.7 for the PDE catalogue relative to a temporally random but spatially localized null hypothesis. Preliminary tests indicate that for the long-term global spatial forecast the gain is of the order 20-25 compared to the uniform event distribution over the Earth's surface. We can also prospectively test the long-term forecast to check whether it can be improved.
Jackson David D.
Kagan Yan Y.
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