Evaluating the RELM Test Results
We consider implications of the Regional Earthquake Likelihood Models (RELM) test results with regard to earthquake forecasting. Prospective forecasts were solicited for M≥4.95 earthquakes in California during the period 2006–2010. During this period 31 earthquakes occurred in the test region with M...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2012-01-01
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| Series: | International Journal of Geophysics |
| Online Access: | http://dx.doi.org/10.1155/2012/543482 |
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| author | Michael K. Sachs Ya-Ting Lee Donald L. Turcotte James R. Holliday John B. Rundle |
| author_facet | Michael K. Sachs Ya-Ting Lee Donald L. Turcotte James R. Holliday John B. Rundle |
| author_sort | Michael K. Sachs |
| collection | DOAJ |
| description | We consider implications of the Regional Earthquake Likelihood Models (RELM) test results with regard to earthquake forecasting. Prospective forecasts were solicited for M≥4.95 earthquakes in California during the period 2006–2010. During this period 31 earthquakes occurred in the test region with M≥4.95. We consider five forecasts that were submitted for the test. We compare the forecasts utilizing forecast verification methodology developed in the atmospheric sciences, specifically for tornadoes. We utilize a “skill score” based on the forecast scores λfi of occurrence of the test earthquakes. A perfect forecast would have λfi=1, and a random (no skill) forecast would have λfi=2.86×10-3. The best forecasts (largest value of λfi) for the 31 earthquakes had values of λfi=1.24×10-1 to λfi=5.49×10-3. The best mean forecast for all earthquakes was λ̅f=2.84×10-2. The best forecasts are about an order of magnitude better than random forecasts. We discuss the earthquakes, the forecasts, and alternative methods of evaluation of the performance of RELM forecasts. We also discuss the relative merits of alarm-based versus probability-based forecasts. |
| format | Article |
| id | doaj-art-c6a54c3076c149ce9656f4fa3d0d6aa4 |
| institution | Kabale University |
| issn | 1687-885X 1687-8868 |
| language | English |
| publishDate | 2012-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Geophysics |
| spelling | doaj-art-c6a54c3076c149ce9656f4fa3d0d6aa42025-02-03T01:11:13ZengWileyInternational Journal of Geophysics1687-885X1687-88682012-01-01201210.1155/2012/543482543482Evaluating the RELM Test ResultsMichael K. Sachs0Ya-Ting Lee1Donald L. Turcotte2James R. Holliday3John B. Rundle4Department of Physics, University of California, Davis, Davis CA 95616, USAGraduate Institute of Geophysics, National Central University, Jhougli 320, TaiwanDepartment of Geology, University of California, Davis, Davis CA 95616, USADepartment of Physics, University of California, Davis, Davis CA 95616, USADepartment of Physics, University of California, Davis, Davis CA 95616, USAWe consider implications of the Regional Earthquake Likelihood Models (RELM) test results with regard to earthquake forecasting. Prospective forecasts were solicited for M≥4.95 earthquakes in California during the period 2006–2010. During this period 31 earthquakes occurred in the test region with M≥4.95. We consider five forecasts that were submitted for the test. We compare the forecasts utilizing forecast verification methodology developed in the atmospheric sciences, specifically for tornadoes. We utilize a “skill score” based on the forecast scores λfi of occurrence of the test earthquakes. A perfect forecast would have λfi=1, and a random (no skill) forecast would have λfi=2.86×10-3. The best forecasts (largest value of λfi) for the 31 earthquakes had values of λfi=1.24×10-1 to λfi=5.49×10-3. The best mean forecast for all earthquakes was λ̅f=2.84×10-2. The best forecasts are about an order of magnitude better than random forecasts. We discuss the earthquakes, the forecasts, and alternative methods of evaluation of the performance of RELM forecasts. We also discuss the relative merits of alarm-based versus probability-based forecasts.http://dx.doi.org/10.1155/2012/543482 |
| spellingShingle | Michael K. Sachs Ya-Ting Lee Donald L. Turcotte James R. Holliday John B. Rundle Evaluating the RELM Test Results International Journal of Geophysics |
| title | Evaluating the RELM Test Results |
| title_full | Evaluating the RELM Test Results |
| title_fullStr | Evaluating the RELM Test Results |
| title_full_unstemmed | Evaluating the RELM Test Results |
| title_short | Evaluating the RELM Test Results |
| title_sort | evaluating the relm test results |
| url | http://dx.doi.org/10.1155/2012/543482 |
| work_keys_str_mv | AT michaelksachs evaluatingtherelmtestresults AT yatinglee evaluatingtherelmtestresults AT donaldlturcotte evaluatingtherelmtestresults AT jamesrholliday evaluatingtherelmtestresults AT johnbrundle evaluatingtherelmtestresults |