## 2 Materials and Methods
### Ionospheric Scintillation Changes Computation  
Given that ionospheric scintillation is subjected to variations that follow, in the short term, a daily periodicity, and, in the long term, an annual, and 11-year solar cycle trend, data must be detrended to detect anomalous variations. As the daily variations are the short-term larger variations, and also because larger, more random fluctuations due to solar radiation are expected during the daytime, data has been filtered to keep only measurements from 0 h to 6h LT, during the night time, when the ionosphere is expected to be more stable, at least in equatorial regions where this study is conducted. This way we expect to better detect anomalous changes on a time-scale longer than 1 day, which are also more likely to be induced by Earth's internal sources rather than by solar or space-weather sources.  
To detrend the monthly/annual variations, the average of two months has been computed, and then subtracted from a seven day window average, in which we want to compute the \(S_{4}\) variation. More precisely, for a particular day \(D\) in which the relative variation is computed, the previous 61 day average is subtracted from the previous seven day average (both including the current day \(D\)). This is computed for every day, and every \(1^{\circ}\times 1^{\circ}\) pixel in the region covered by CYGNSS (from 40\({}^{\circ}\)S to 40\({}^{\circ}\)N) using Equation (2).  
\[\Delta S_{4}(x,y,D)=\frac{1}{7}\sum_{d=D-6}^{D}S_{4}(x,y,d)-\frac{1}{61}\sum_{ d=D-60}^{D}S_{4}(x,y,d), \tag{2}\]  
where \(x,y\) represent the longitude and latitude of each pixel in the map, and \(d\) is the day swept to compute the average. The \(S_{4}\) variation (\(\Delta S_{4}\)) is computed for every day \(D\), at each pixel in the map. It usually exhibits values ranging \(\pm 0.06\), being positive when the \(S_{4}\) in the last week has been larger than the typical value during the last two months.  
The selection of a two month (61 day) average for detrending is made to remove the long term, annual evolution of the ionospheric activity in addition to the variability of the sea-surface conditions, while the 7 day short average helps to smooth fluctuations in this activity due to space-weather with a daily or weekly timescale, and also fits with the approximate timescales expected for the earthquakes ionospheric precursors to occur, according to the studies referenced in previous sections [12; 13; 18]. Additionally, both averaging windows are asymmetrical in time, including only values before the current day. The reason for that is that our study is focused on searching for precursory changes in ionospheric scintillation.  
Due to the periodicity of the CYGNSS satellite's orbits, and the filter applied to keep only measurements from 0 h to 6 h LT, a time dependence was observed in the latitude of the regions covered by the study along the period studied.  
Figure 2 shows the position of the median latitude of the valid data pixels for every day in the period studied (blue line). It also shows, the area between the first and third interquartiles of the available data pixels (green area), and the maximum and minimum latitudes covered (gray area). This plot shows the oscillating behavior of the region covered in the study.  
This variation in the region covered will make that some regions away from the equator would not be included in the study during a certain time. Earthquakes taking place in these periods and regions would not be studied because of the lack of ionospheric scintillation data to correlate with. The method for discarding these data will be explained in the section regarding the creation of the confusion matrix.