Improved earthquake aftershocks forecasting model based on long-term memory
A prominent feature of earthquakes is their empirical laws, including memory (clustering) in time and space. Several earthquake forecasting models, such as the epidemic-type aftershock sequence (ETAS) model, were developed based on these empirical laws. Yet, a recent study [ 1 ] showed that the ETAS...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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IOP Publishing
2021-01-01
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| Series: | New Journal of Physics |
| Subjects: | |
| Online Access: | https://doi.org/10.1088/1367-2630/abeb46 |
| _version_ | 1797750252093046784 |
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| author | Yongwen Zhang Dong Zhou Jingfang Fan Warner Marzocchi Yosef Ashkenazy Shlomo Havlin |
| author_facet | Yongwen Zhang Dong Zhou Jingfang Fan Warner Marzocchi Yosef Ashkenazy Shlomo Havlin |
| author_sort | Yongwen Zhang |
| collection | DOAJ |
| description | A prominent feature of earthquakes is their empirical laws, including memory (clustering) in time and space. Several earthquake forecasting models, such as the epidemic-type aftershock sequence (ETAS) model, were developed based on these empirical laws. Yet, a recent study [ 1 ] showed that the ETAS model fails to reproduce the significant long-term memory characteristics found in real earthquake catalogs. Here we modify and generalize the ETAS model to include short- and long-term triggering mechanisms, to account for the short- and long-time memory (exponents) discovered in the data. Our generalized ETAS model accurately reproduces the short- and long-term/distance memory observed in the Italian and Southern Californian earthquake catalogs. The revised ETAS model is also found to improve earthquake forecasting after large shocks. |
| first_indexed | 2024-03-12T16:30:59Z |
| format | Article |
| id | doaj.art-f0f482785e834b869809ffc4565b5015 |
| institution | Directory Open Access Journal |
| issn | 1367-2630 |
| language | English |
| last_indexed | 2024-03-12T16:30:59Z |
| publishDate | 2021-01-01 |
| publisher | IOP Publishing |
| record_format | Article |
| series | New Journal of Physics |
| spelling | doaj.art-f0f482785e834b869809ffc4565b50152023-08-08T15:32:14ZengIOP PublishingNew Journal of Physics1367-26302021-01-0123404200110.1088/1367-2630/abeb46Improved earthquake aftershocks forecasting model based on long-term memoryYongwen Zhang0https://orcid.org/0000-0002-3240-7249Dong Zhou1Jingfang Fan2https://orcid.org/0000-0003-1954-4641Warner Marzocchi3Yosef Ashkenazy4Shlomo Havlin5Faculty of Science, Kunming University of Science and Technology, Yunnan, Kunming 650500, People's Republic of China; Department of Solar Energy and Environmental Physics, The Jacob Blaustein Institutes for Desert Research, University of the Negev, Midreshet Ben-Gurion 84990, Israel; Department of Physics, Bar-Ilan University, Ramat Gan 52900, IsraelDepartment of Solar Energy and Environmental Physics, The Jacob Blaustein Institutes for Desert Research, University of the Negev, Midreshet Ben-Gurion 84990, Israel; School of Reliability and Systems Engineering, Beihang University , Beijing, 100191, People’s Republic of ChinaSchool of Systems Science, Beijing Normal University , Beijing 100875, People’s Republic of China; Potsdam Institute for Climate Impact Research , 14412 Potsdam, GermanyDepartment of Earth, Environmental, and Resources Sciences, University of Naples , Federico II, Complesso di Monte Sant’Angelo, Via Cinthia, 21 80126 Napoli, ItalyDepartment of Solar Energy and Environmental Physics, The Jacob Blaustein Institutes for Desert Research, University of the Negev, Midreshet Ben-Gurion 84990, IsraelDepartment of Physics, Bar-Ilan University, Ramat Gan 52900, IsraelA prominent feature of earthquakes is their empirical laws, including memory (clustering) in time and space. Several earthquake forecasting models, such as the epidemic-type aftershock sequence (ETAS) model, were developed based on these empirical laws. Yet, a recent study [ 1 ] showed that the ETAS model fails to reproduce the significant long-term memory characteristics found in real earthquake catalogs. Here we modify and generalize the ETAS model to include short- and long-term triggering mechanisms, to account for the short- and long-time memory (exponents) discovered in the data. Our generalized ETAS model accurately reproduces the short- and long-term/distance memory observed in the Italian and Southern Californian earthquake catalogs. The revised ETAS model is also found to improve earthquake forecasting after large shocks.https://doi.org/10.1088/1367-2630/abeb46earthquake memoryETAS modelforecasting |
| spellingShingle | Yongwen Zhang Dong Zhou Jingfang Fan Warner Marzocchi Yosef Ashkenazy Shlomo Havlin Improved earthquake aftershocks forecasting model based on long-term memory New Journal of Physics earthquake memory ETAS model forecasting |
| title | Improved earthquake aftershocks forecasting model based on long-term memory |
| title_full | Improved earthquake aftershocks forecasting model based on long-term memory |
| title_fullStr | Improved earthquake aftershocks forecasting model based on long-term memory |
| title_full_unstemmed | Improved earthquake aftershocks forecasting model based on long-term memory |
| title_short | Improved earthquake aftershocks forecasting model based on long-term memory |
| title_sort | improved earthquake aftershocks forecasting model based on long term memory |
| topic | earthquake memory ETAS model forecasting |
| url | https://doi.org/10.1088/1367-2630/abeb46 |
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