Application of the RI model to forecasting future large earthquakes in Japan

Kazu Z. Nanjo (ERI, Univ. of Tokyo)

International symposium “Toward constructing earthquake forecast systems for Japan”

27 May 2009 at ERI, Univ. Tokyo

RI & PI RI (Relative Intensity of Seismicity)

- Future large earthquakes regions with high seismic intensity

- More specifically, count past earthquakes for each node

PI (Pattern Informatics)- Future large earthquakes regions with high rate change

(activation and quiescence) of seism city

- More specifically, the change of number of events based on past earthquakes for each node

Studies for CA, China, and Japan show- Both are similar for their forecast accuracy

RI and PI need to be optimized

Forecast models using PI and RI

forecasting 2000-2009 M≥5 events

based on 1965-1999 M≥3 events

PIRI

•PI method: find seismic activation and quiescence•RI method: find seismic intensity

•PI method: find seismic activation and quiescence•RI method: find seismic intensity

Nanjo et al. (2006a,b)

Log10 P Log10 P

As of Aug. 2005

Molchan testA test to measure of matching between forecast map based on EQs. in ≤1999 and EQs. in ≥ 2000

A test to measure of matching between forecast map based on EQs. in ≤1999 and EQs. in ≥ 2000

•PI method: find seismic activation and quiescence•RI method: find seismic intensity

•PI method: find seismic activation and quiescence•RI method: find seismic intensity

Application of RI to Japan JMA catalog CSEP testing region (Bin size: 0.1 deg) Retrospective test: m≥5 events in the last 3 years

Optimization- Change t0 and minimum magnitude Mmin:

• To see the effect of catalog completeness on forecasting

- Nondeclustered and declustered catalogs: • To see aftershock effect on forecasting

tt 0 (v

ariable)

2005/04/01

2008/03/31

Forecast period58 m≥5 targets

Learning periodMmin: a variable

Evolution of MC since 1970 (d≤30km)

RI mapsNondeclustered Declustered

RI RI

(m>=3, t0=1985/01/01)

LLP=-350LLP=-350 LLP=-370LLP=-370

Likelihood test

m>=2.5m>=3.0m>=4.0

ND D

•Aftershock locations are important information of forecasting future events•Catalog completeness and maximizing data need to be considered for optimization

•Aftershock locations are important information of forecasting future events•Catalog completeness and maximizing data need to be considered for optimization

A proposed prospective forecast map

Summary

Results- Aftershock location

• Important information to forecast the location of future large earthquakes

- The need of optimization for RI forecast• Catalog completeness

• Maximize used data

• (Non)declustering

Current status for submission - Under test for the testing since 2008

- Ready for submission to the 1 day forecast class if there is any proposed one-day model!