Earthquake Forecasting and Earthquake Prediction: Different Approaches for Obtaining the Best Model

2011 ◽  
Vol 82 (3) ◽  
pp. 442-448 ◽  
Author(s):  
W. Marzocchi ◽  
J. D. Zechar
Keyword(s):  
Earthquake Prediction ◽  
Earthquake Forecasting

How prediction statistics can help us cope when we are shaken, scared and irrational

2021 ◽  
Author(s):  
Yavor Kamer ◽  
Shyam Nandan ◽  
Stefan Hiemer ◽  
Guy Ouillon ◽  
Didier Sornette
Keyword(s):  
Earthquake Prediction ◽  
Information Technologies ◽  
Predictive Performance ◽  
Earthquake Forecasting ◽  
Skill Assessment ◽  
Surveillance Network ◽  
The Public ◽  
Predictive Skill ◽  
Earthquake Predictability ◽  
Set Up

<p>Nature is scary. You can be sitting at your home and next thing you know you are trapped under the ruble of your own house or sucked into a sinkhole. For millions of years we have been the figurines of this precarious scene and we have found our own ways of dealing with the anxiety. It is natural that we create and consume prophecies, conspiracies and false predictions. Information technologies amplify not only our rational but also irrational deeds. Social media algorithms, tuned to maximize attention, make sure that misinformation spreads much faster than its counterpart.</p><p>What can we do to minimize the adverse effects of misinformation, especially in the case of earthquakes? One option could be to designate one authoritative institute, set up a big surveillance network and cancel or ban every source of misinformation before it spreads. This might have worked a few centuries ago but not in this day and age. Instead we propose a more inclusive option: embrace all voices and channel them into an actual, prospective earthquake prediction platform (Kamer et al. 2020). The platform is powered by a global state-of-the-art statistical earthquake forecasting model that provides near real-time earthquake occurrence probabilities anywhere on the globe (Nandan et al. 2020). Using this model as a benchmark in statistical metrics specifically tailored to the prediction problem, we are able to distill all these voices and quantify the essence of predictive skill. This approach has several advantages. Rather than trying to silence or denounce, we listen and evaluate each claim and report the predictive skill of the source. We engage the public and allow them to take part in a scientific experiment that will increase their risk awareness. We effectively demonstrate that anybody with an internet connected device can make an earthquake prediction, but that it is not so trivial to achieve skillful predictive performance.</p><p>Here we shall present initial results from our global earthquake prediction experiment that we have been conducting on www.richterx.com for the past two years, yielding more than 10,000 predictions. These results will hopefully demystify the act of predicting an earthquake in the eyes of the public, and next time someone forwards a prediction message it would arouse more scrutiny than panic or distaste.<br><br>Nandan, S., Kamer, Y., Ouillon, G., Hiemer, S., Sornette, D. (2020). <em>Global models for short-term earthquake forecasting and predictive skill assessment</em>. European Physical Journal ST. doi: 10.1140/epjst/e2020-000259-3<br>Kamer, Y., Nandan, S., Ouillon, G., Hiemer, S., Sornette, D. (2020). <em>Democratizing earthquake predictability research: introducing the RichterX platform.</em> European Physical Journal ST. doi: 10.1140/epjst/e2020-000260-2 </p>

scholarly journals Precursory pattern of tidal triggering of earthquakes in six regions of China: the possible relation to the crustal heterogeneity

2013 ◽  
Vol 13 (10) ◽  
pp. 2605-2618 ◽  
Author(s):  
Q. Li ◽  
G.-M. Xu
Keyword(s):  
Earthquake Prediction ◽  
Earthquake Hazard ◽  
Earthquake Forecasting ◽  
Earthquake Occurrence ◽  
Crustal Rocks ◽  
Tidal Triggering ◽  
Crustal Heterogeneity ◽  
Tidal Variations ◽  
Prediction Efficiency

Abstract. We found the possible correlation between the precursory pattern of tidal triggering of earthquakes and the crustal heterogeneities, which is of particular importance to the researchers in earthquake prediction and earthquake hazard prevention. We investigated the connection between the tidal variations and earthquake occurrence in the Liyang, Wunansha, Cangshan, Wenan, Luquan and Yaoan regions of China. Most of the regions show a higher correlation with tidal triggering in several years preceding the large or destructive earthquakes compared to other times, indicating that the tidal triggering may inherently relate to the nucleation of the destructive earthquakes during this time. In addition, the analysis results indicate that the Liyang, Cangshan and Luquan regions, with stronger heterogeneity, show statistically significant effects of tidal triggering preceding the large or destructive earthquakes, while the Wunansha, Wenan and Yaoan regions, with relatively weak heterogeneity, show statistically insignificant effects of it, signifying that the precursory pattern of tidal triggering of earthquakes in these six regions is possibly related to the heterogeneities of the crustal rocks. The above results suggest that when people try to find the potential earthquake hazardous areas or make middle–long-term earthquake forecasting by means of precursory pattern of the tidal triggering, the crustal heterogeneity in these areas has to be taken into consideration for the purpose of increasing the prediction efficiency. If they do not consider the influence of crustal heterogeneity on the tidal triggering of earthquakes, the prediction efficiency might greatly decrease.

scholarly journals Introduction to Professor Usami's Review in 1974

2006 ◽  
Vol 1 (3) ◽  
pp. 415-415
Author(s):  
Kazuki Koketsu ◽  
Keyword(s):  
Earthquake Prediction ◽  
Early Stage ◽  
Strong Motion ◽  
Earthquake Forecasting ◽  
Professor Emeritus ◽  
Suruga Bay ◽  
Kanto Earthquake ◽  
Earthquake Prediction Research ◽  
Earthquake Research ◽  
Short Term Prediction

Tatsuo Usami, now professor emeritus at the University of Tokyo, published a paper entitled “Earthquake Studies and the Earthquake Prediction System in Japan” in the March 1974 issue of Technocrat. I was impressed by Professor Usami’s comprehensive review and healthy criticism of earthquake prediction in Japan, which appears fresh even today. He gave an overview of the 1923 Kanto earthquake and Program 1 to 2 of the earthquake prediction project in Japan. The motivation and research for the project in its early stage are well summarized in the paper. The Tokai earthquake hypothesis [1] was proposed during Program 3, so the budget for the project at national universities was approximately tripled in Program 4 and increased to about 12 billion yen in Program 7 (Table 1). The 1995 Kobe (Hyogo-ken Nanbu) earthquake occurred during Program 7 killing 6,434 people and completely destroying 104,906 houses [2]. Since this unexpected earthquake was as destructive as the 1923 Kanto earthquake, the earthquake prediction project was reformed in New Program 1 (Table 1). The Headquarters for Earthquake Research Promotion was established, moving emphasis from empirical short-term prediction to long-term earthquake forecasting and prediction of strong ground motion [3]. Dr. Hiroe Miyake and I reviewed this situation in a preceding article [4], taking over the mission of writing a recent history of Japanese seismology from Professor Usami's paper. References: [1] K. Ishibashi, “Did the rupture zone of the 1707 Hoei earthquake not extend to deep Suruga Bay?,” Rep. Subcomm. Tokai Distr., Coord. Comm. Earthq. Predict., Geogr. Surv. Inst., pp. 69-78, 1977 (in Japanese). [2] K. Koketsu, “Chronological table of damaging earthquakes in Japan,” in Chronological Scientific Tables 2007, Maruzen, pp.698-729, 2006 (in Japanese). [3] N. Hirata, “Past, current and future of Japanese national program for earthquake prediction research,” Earth Planets and Space, 56, pp. xliii-l, 2004. [4] K. Koketsu and H. Miyake, “Earthquake Observation and Strong Motion Seismology in Japan from 1975 to 2005,” Journal of Disaster Research, Vol.1, No.3, pp. 407-414, 2006. Kazuki Koketsu Professor, University of Tokyo

scholarly journals Laboratory earthquake forecasting: A machine learning competition

2021 ◽  
Vol 118 (5) ◽  
pp. e2011362118
Author(s):  
Paul A. Johnson ◽  
Bertrand Rouet-Leduc ◽  
Laura J. Pyrak-Nolte ◽  
Gregory C. Beroza ◽  
Chris J. Marone ◽  
...  
Keyword(s):  
Machine Learning ◽  
Data Analysis ◽  
Earthquake Prediction ◽  
Seismic Data ◽  
Earthquake Forecasting ◽  
Seismic Cycle ◽  
Pedagogical Tool ◽  
Failure Times ◽  
Testing Data ◽  
Earthquake Data

Earthquake prediction, the long-sought holy grail of earthquake science, continues to confound Earth scientists. Could we make advances by crowdsourcing, drawing from the vast knowledge and creativity of the machine learning (ML) community? We used Google’s ML competition platform, Kaggle, to engage the worldwide ML community with a competition to develop and improve data analysis approaches on a forecasting problem that uses laboratory earthquake data. The competitors were tasked with predicting the time remaining before the next earthquake of successive laboratory quake events, based on only a small portion of the laboratory seismic data. The more than 4,500 participating teams created and shared more than 400 computer programs in openly accessible notebooks. Complementing the now well-known features of seismic data that map to fault criticality in the laboratory, the winning teams employed unexpected strategies based on rescaling failure times as a fraction of the seismic cycle and comparing input distribution of training and testing data. In addition to yielding scientific insights into fault processes in the laboratory and their relation with the evolution of the statistical properties of the associated seismic data, the competition serves as a pedagogical tool for teaching ML in geophysics. The approach may provide a model for other competitions in geosciences or other domains of study to help engage the ML community on problems of significance.

scholarly journals Earthquake prediction

1978 ◽  
Vol 11 (1) ◽  
pp. 2-4
Author(s):  
F. F. Evison
Keyword(s):  
Earthquake Prediction ◽  
Short Range ◽  
Historical Record ◽  
Earthquake Forecasting ◽  
False Alarms ◽  
Prediction Methods ◽  
Economic Implications ◽  
The Social ◽  
Large Factor ◽  
Precursory Phenomena

The study of precursory phenomena shows increasing promise as a basis for earthquake prediction. Long-range forecasting can be expected to reduce by a large factor the uncertainty of estimates based on the historical record, and also to facilitate the development of short-range forecasting. The testing of prediction methods for reliability poses special problems. Earthquake forecasting will be much affected in practice by the social and economic implications of forecasts as such, and also by the relative implications of failures and false alarms, as well as successes.

Sign in / Sign up

Export Citation Format

Share Document