This study discusses the possible relationship between potentially destructive seismic events,earthquake swarms,and intense weather events occurring in the same epicentral zone at time intervals ranging from one day t...This study discusses the possible relationship between potentially destructive seismic events,earthquake swarms,and intense weather events occurring in the same epicentral zone at time intervals ranging from one day to a few weeks.The objective of the present study is,therefore,to analyze the interaction between the lithosphere,atmosphere,and ionosphere in order to propose,prospectively,a new hydro-climatic model to be applied not only in Italy,where this research was carried out.The study concerns some of the most intense Italian earthquakes starting from 1920,with the destructive event in Lunigiana,in North Western Apennines,until the recent earthquake swarm that hit the Emilia-Romagna region followed,as in the cases analyzed in this research,by strong atmospheric disturbances.The recurrence associating seismic events with atmospheric precipitation allows us to propose some hypotheses about the triggering mechanism.In tectonically stressed areas,during pre-seismic and seismic phases,the release of gases from the ground and electrical charges near active faults is known.It is hypothesized that water condensation nuclei are carried by radon gas on atmospheric gases,also originating from cosmic rays in the upper atmosphere,generated by air ionization.展开更多
With the aim to the quantification of anomaly identification and extraction for observed or analyzed records, we present two statistical methods of earthquake corresponding relevancy spectrum （ECRS） and sliding mean...With the aim to the quantification of anomaly identification and extraction for observed or analyzed records, we present two statistical methods of earthquake corresponding relevancy spectrum （ECRS） and sliding mean relevancy （SMR）. With ECRS method, we can obtain the abnormal confidence attribute of data in different value ranges. Based on the relevancy spectrum in different studied time-intervals, we convert the original time sequence into relevancy time sequence, and can obtain the SMR time series by using the multi-point cumulative sliding mean method. Then we can identify the seismic precursor anomaly. We test this method by taking the time sequence of r/-value in the northern Tianshan region as original data. The result shows that when the studied time-interval is 18 months, the precursor anomaly can be identified bet- ter from sliding mean relevancy. The anomaly corresponding rate is 83 percent, the earthquake corresponding rate is 86 per- cent, and the anomaly is characteristic of the middle term. To try the research on multi-parameter comprehensive application, we take the Kalpin tectonic block in Xinjiang as our studied region, and analyze the spatial and temporal abnormal characters of multi-parameter sliding extreme-value relevancy （MSER） before mid-strong earthquakes in the Kalpin block. The result indicates that ECRS and SMR sequence in different time-intervals can not only be used to identify the precursor anomaly of single-item data, but also offer the data of quantitative single-item anomaly for comprehensive earthquake analysis and prediction.展开更多
文摘This study discusses the possible relationship between potentially destructive seismic events,earthquake swarms,and intense weather events occurring in the same epicentral zone at time intervals ranging from one day to a few weeks.The objective of the present study is,therefore,to analyze the interaction between the lithosphere,atmosphere,and ionosphere in order to propose,prospectively,a new hydro-climatic model to be applied not only in Italy,where this research was carried out.The study concerns some of the most intense Italian earthquakes starting from 1920,with the destructive event in Lunigiana,in North Western Apennines,until the recent earthquake swarm that hit the Emilia-Romagna region followed,as in the cases analyzed in this research,by strong atmospheric disturbances.The recurrence associating seismic events with atmospheric precipitation allows us to propose some hypotheses about the triggering mechanism.In tectonically stressed areas,during pre-seismic and seismic phases,the release of gases from the ground and electrical charges near active faults is known.It is hypothesized that water condensation nuclei are carried by radon gas on atmospheric gases,also originating from cosmic rays in the upper atmosphere,generated by air ionization.
文摘With the aim to the quantification of anomaly identification and extraction for observed or analyzed records, we present two statistical methods of earthquake corresponding relevancy spectrum （ECRS） and sliding mean relevancy （SMR）. With ECRS method, we can obtain the abnormal confidence attribute of data in different value ranges. Based on the relevancy spectrum in different studied time-intervals, we convert the original time sequence into relevancy time sequence, and can obtain the SMR time series by using the multi-point cumulative sliding mean method. Then we can identify the seismic precursor anomaly. We test this method by taking the time sequence of r/-value in the northern Tianshan region as original data. The result shows that when the studied time-interval is 18 months, the precursor anomaly can be identified bet- ter from sliding mean relevancy. The anomaly corresponding rate is 83 percent, the earthquake corresponding rate is 86 per- cent, and the anomaly is characteristic of the middle term. To try the research on multi-parameter comprehensive application, we take the Kalpin tectonic block in Xinjiang as our studied region, and analyze the spatial and temporal abnormal characters of multi-parameter sliding extreme-value relevancy （MSER） before mid-strong earthquakes in the Kalpin block. The result indicates that ECRS and SMR sequence in different time-intervals can not only be used to identify the precursor anomaly of single-item data, but also offer the data of quantitative single-item anomaly for comprehensive earthquake analysis and prediction.
