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  Statistical power of spatial earthquake forecast tests

Khawaja, M. A., Hainzl, S., Schorlemmer, D., Iturrieta, P. C., Bayona, J. A., Savran, W. H., Werner, M., Marzocchi, W. (2023): Statistical power of spatial earthquake forecast tests. - Geophysical Journal International, 233, 3, 2053-2066.
https://doi.org/10.1093/gji/ggad030

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Khawaja, Muhammad Asim1, Autor              
Hainzl, S.1, Autor              
Schorlemmer, Danijel2, Autor              
Iturrieta, Pablo Cristián2, Autor              
Bayona, José A.3, Autor
Savran, William H.3, Autor
Werner, Maximilian3, Autor
Marzocchi, Warner3, Autor
Affiliations:
12.1 Physics of Earthquakes and Volcanoes, 2.0 Geophysics, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum, ou_146029              
22.6 Seismic Hazard and Risk Dynamics, 2.0 Geophysics, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum, ou_146032              
3External Organizations, ou_persistent22              

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Schlagwörter: Earthquake hazards, earthquake interaction, forecasting and prediction, Statistical seismology, Earthquake forecast testing, Statistical power analysis
 Zusammenfassung: The Collaboratory for the Study of Earthquake Predictability (CSEP) is an international effort to evaluate earthquake forecast models prospectively. In CSEP, one way to express earthquake forecasts is through a grid-based format: the expected number of earthquake occurrences within 0.1° × 0.1° spatial cells. The spatial distribution of seismicity is thereby evaluated using the Spatial test (S-test). The high-resolution grid combined with sparse and inhomogeneous earthquake distributions leads to a huge number of cells causing disparity in the number of cells, and the number of earthquakes to evaluate the forecasts, thereby affecting the statistical power of the S-test. In order to explore this issue, we conducted a global earthquake forecast experiment, in which we computed the power of the S-test to reject a spatially non-informative uniform forecast model. The S-test loses its power to reject the non-informative model when the spatial resolution is so high that every earthquake of the observed catalog tends to get a separate cell. Upon analysing the statistical power of the S-test, we found, as expected, that the statistical power of the S-test depends upon the number of earthquakes available for testing, e.g. with the conventional high-resolution grid for the global region, we would need more than 32 000 earthquakes in the observed catalog for powerful testing, which would require approximately 300 yr to record M ≥ 5.95. The other factor affecting the power is more interesting and new; it is related to the spatial grid representation of the forecast model. Aggregating forecasts on multi-resolution grids can significantly increase the statistical power of the S-test. Using the recently introduced Quadtree to generate data-based multi-resolution grids, we show that the S-test reaches its maximum power in this case already for as few as eight earthquakes in the test period. Thus, we recommend for future CSEP experiments the use of Quadtree-based multi-resolution grids, where available data determine the resolution.

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Sprache(n): eng - Englisch
 Datum: 2023-01-242023
 Publikationsstatus: Final veröffentlicht
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 Ort, Verlag, Ausgabe: -
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 Art der Begutachtung: -
 Identifikatoren: DOI: 10.1093/gji/ggad030
GFZPOF: p4 T3 Restless Earth
OATYPE: Green Open Access
 Art des Abschluß: -

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Titel: Geophysical Journal International
Genre der Quelle: Zeitschrift, SCI, Scopus, ab 2024 OA-Gold
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Ort, Verlag, Ausgabe: -
Seiten: - Band / Heft: 233 (3) Artikelnummer: - Start- / Endseite: 2053 - 2066 Identifikator: ISSN: 0956-540X
ISSN: 1365-246X
CoNE: https://gfzpublic.gfz-potsdam.de/cone/journals/resource/journals180
Publisher: Oxford University Press