# Successful Tests on Detecting Pre-Earthquake Magnetic Field Signals from Space
## 3 Results and Discussion
### Confutation Analysis  
To verify that the observed magnetic anomalies are related to seismic activity in the region and not coincidental, a type of analysis called \"confutation analysis\" is performed, comparing the results from our real data analysis with the results from a synthetic data analysis [42].  
Confutation analysis can aid in identifying and determining the causal relationship between magnetic anomalies and earthquakes. By manipulating the data in terms of time or location, we can gather more information about the actual correlation between these two phenomena. Confutation analysis allows us to investigate whether magnetic anomalies and earthquakes occur simultaneously in a specific location by chance or if there exists a direct causal relationship between them. This analysis can provide stronger evidence of the dependency between magnetic anomalies and seismic events or confute the results.  
In this study, we cannot utilize temporal displacement because the entire Alpine-Himalayan seismic belt is considered (Figure 1), which is one of the three major seismic belts in the world. Essentially, it is not possible to find a time period within this belt that is fully free of earthquakes. Additionally, there is a limitation in the available data, as the data only cover the period from 2014 onwards. Therefore, for this confutation analysis, we cannot rely on temporal displacement.  
In that case, we can only shift the data (E-W or N-S) laterally, which presents its own set of challenges. As a large region is considered in this context, it becomes challenging to displace this area to a location where no earthquakes have occurred. Furthermore, excessive N-S displacement may potentially result in the creation of magnetic conjugate anomalies [29; 50; 51]. Considering these conditions, we will shift the data southward by 30 degrees of latitude. The region to which the data has been shifted, as indicated in Figure S8, except for the two marked areas with a blue plus sign, shows relatively low seismic activity from 2014 to 2023. In Figure S8, the region to which the data has been shifted is indicated by a dashed blue rectangle, and the reference baseline is marked by a solid black rectangle. The main earthquakes are represented by hollow red circles, and their shifted positions are indicated by orange stars. On the other hand, since we have considered the Dobrovolsky region for earthquakes (Equation (1)), there may be some overlap in the case of major earthquakes. With all these considerations, it is indeed certain that the real seismic activity in the region to which the data has been shifted is lower than that of the Alpine-Himalayan seismic belt. Finally, applying the algorithm to the shifted synthetic earthquake data and real satellite measurements has yielded interesting results. Please note that the total number of earthquakes reduced slightly from 1077 to 1069 because some orbits did not cross a few corresponding Dobrovolsky regions. As shown in Table 3, without considering the constraints of geomagnetic indices and for all earthquakes with at least one abnormal orbit, only 256 out of 1069 earthquakes have exhibited pre-earthquake anomalies. This accounts for 24% of all earthquakes, whereas the ratio for the original earthquakes and magnetic field data is 83%. In the case where geomagnetic indices are considered, as indicated in Table 4, for the shifted data, the percentage of earthquakes exhibiting precursors reduces to 17%, while for the original data, it is 78%. Based on the results, it can be concluded that the satellite observations of magnetic anomalies along the Alpine-Himalayan belt are not statistically random and could be related to the occurrence of earthquakes.