## 5 Results and Discussions
### Discrepancies in Collected Seismicity Data
By analyzing individual magnitude variations, we can identify specific events that are outliers or particularly significant, providing insights into the most extreme or unusual seismic activities in the region. Simultaneously, by calculating the average magnitude over various time frames, we can discern broader patterns and trends that might not be apparent from individual events alone. This averaging process helps in smoothing out short-term fluctuations and focusing on longer-term trends, providing a clearer picture of the overall seismic dynamics. It allows us to see how seismic activity might be evolving over time, potentially influenced by geological processes or human activities. By combining these two analytical approaches, we ensure a holistic understanding of seismic magnitudes. Figure 5a expands the analysis of seismic activity in the Red Sea region to include the magnitudes of seismic events, using the same temporal metrics previously considered. The annual variation in reported magnitudes reveals a notable trend in seismic activity over the decades, characterized by an increasing frequency of events. Additionally, a shift towards higher magnitudes in recent years can be observed, potentially indicative of escalating tectonic stress within the region's crust. This aligns with the geologically active nature of the Red Sea, a site of divergent tectonic plate movement involving the spreading of the African and Arabian plates. The monthly variation in reported magnitudes does not suggest a strong seasonal pattern, implying that tectonic processes in the area are not significantly influenced by seasonal climatic variations. The scatter plot showing daily variations in reported magnitudes appears uniform, indicating that seismicity does not exhibit a daily periodicity. Similarly, the hourly variation in reported magnitudes demonstrates a relatively even distribution of seismic magnitudes throughout the day, suggesting that diurnal factors do not significantly influence the region's seismicity. Comparing the data across different seismic networks (KSUSN, SANDSN, and SNSN), there is a notable consistency in the capture of seismic events of various magnitudes. This reflects a robust and well-integrated seismic monitoring infrastructure in the Red Sea region. The consistency across networks also suggests that the recorded seismic activity accurately represents the regional tectonic behavior and is not merely an artifact of observational bias. Figure 5b provides an analytical representation of the average earthquake magnitudes recorded over various temporal scales by the KSUSN, SANDSN, and SNSN seismic networks. This data is crucial for understanding seismic trends and the operational characteristics of each network in relation to regional tectonic activity. The annual distribution of average magnitudes from KSUSN initially shows higher values that decrease over time, while SNSN displays a general increase, marked by a pronounced escalation in later years. SANDSN maintains relatively stable average magnitudes throughout the period. The recent surge in average magnitude reported by SNSN could indicate a shift in tectonic activity or changes in the network's detection capabilities. The monthly distribution from KSUSN reveals significant fluctuations in magnitude, possibly reflecting real variations in seismicity or seasonal influences on data collection. SANDSN and SNSN demonstrate more consistency, though SANDSN exhibits some variability, raising questions about outliers or seasonal seismic behavior. The daily distribution from KSUSN shows high variability, with some days reporting significantly higher average magnitudes, potentially indicative of outliers. In contrast, the more consistent trends from SANDSN and SNSN suggest a steadier detection of seismic magnitudes, although occasional deviations are present. The hourly distribution of average magnitudes from KSUSN shows the most significant variations, suggesting potential outliers within the hourly data.