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Abstract
In 1997 Russian scientist Morozova found some cloud anomalies possibly related to active fault systems and earthquakes. Now, 24 years later, the correlation between clouds and earthquakes is still controversial, and in this paper we checked systematically the satellite images in Italy from 2010 to 2013. The correlation between earthquakes and cloud anomalies was statistically examined by assuming different various leading times and magnitudes. The result showed that when the leading time interval was set to 23≤ΔT≤45 days and the magnitude is bigger than or equal to M4.7, 70% of earthquakes were preceded by cloud anomalies. Poisson random test showed that anomaly appearance rate (AAR) and earthquake occurrence rate (EOR) was much higher than those derived in a random situation, which means it is nearly impossible to deny the correlation between cloud anomaly and land earthquakes in Italy. Error matrix analysis showed this method provides 75% overall accuracy for the 52 total cases. Analysis also showed that cloud method provides a very high AAR value and similar EOR value compared with other earthquake prediction methods based on ionospheric or skin temperature data. The physical mechanism of cloud anomaly was likely caused by electric field, which linked active fault, atmosphere circuit conduction current, and cloud anomaly, and thus provides a reasonable hypothesis of cloud anomaly.
Highlights
Clouds are very common in the atmosphere, and they are always considered to be related to weather change
Based on this table it is possible to define the overall accuracy of the method as the sum of the total correct case divided by the total case (Fawcett, 2006), and it is equal to 75% which indicates that the method is better than a prediction made by chance that would give 50% of accuracy
Pulinets et al (2015) proposed a LAI (Lithosphere-Atmosphere-Ionosphere) coupling model and tried to explain this phenomenon by a complex chain of sub-processes starting from the release of ionized particles from the stressed fault. They considered that radon gas would emit from activated faults, and the vertical electric field above the faults supports the linear structure of cluster ion flows which leaded to the formation of anomalous linear clouds
Summary
Clouds are very common in the atmosphere, and they are always considered to be related to weather change. The statistics for the EMSC catalogue and USGS catalogue show that AAR and EOR are both significant for the case of 23≤ΔT≤45 days This proves that cloud method is convincing even for different catalogues. The time windows without cloud anomalies which are not followed by an earthquake is estimated as the number of not-alerted days (i.e., 1,070) divided by the width of the alerted window (23 days) and subtracting the three notpredicted earthquakes Based on this table it is possible to define the overall accuracy of the method as the sum of the total correct case (earthquake preceded by cloud anomaly in the proper time + absence of cloud anomaly and earthquake) divided by the total case (Fawcett, 2006), and it is equal to 75% which indicates that the method is better than a prediction made by chance that would give 50% of accuracy. This means cloud method used a shorter leading time interval and gave a better performance than telluric current method
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