# Automatic Detection of Whistler Waves in the Top-Side Ionosphere: The WhISPER Technique
## 4 Discussion and Conclusions  
A new technique called WhIPSER was developed for the automatic detection of whistler waves in the top-side ionosphere. The algorithm detected 860,623 whistlers over a period of 1290 days from 2019 to 2022. Detected events exhibit higher density in three primary geographical regions (Figure 8): central America, western central Africa, and parts of southeast Asia. In addition, our analysis reveals a pronounced seasonal variation in event occurrence (Figure 9), a negligible dependence on solar activity (Figure 10), and a significantly higher occurrence rate during nighttime (Figure 11). The reliability and robustness of the proposed technique were validated through visual inspection of a randomly selected event subset, demonstrating an accuracy of approximately 96%, using Parameter Set 1. Additional key performance metrics (Table 5) demonstrate excellent results, including an F\({}_{1}\) score score of 98%, a True Positive Rate of 96%, a True Negative Rate of 94%, and a Positive Predictive Value of 99%. Correspondingly, the False Negative Rate and False Positive Rate are low, at 4% and 6%, respectively. This performance surpasses that reported in prior research; for example, [PERSON] et al. [20] reported a detection accuracy of 92.14 % and [PERSON] et al. [28] reported a mis-detection rate (i.e., False Negative) of 25.07%. Tables 4 and 5 further illustrate two significant strengths of WhISPER: its interpretability and adaptability. Indeed, the performance metrics used to evaluate the algorithm are dependent on parameters \(T_{1}\), \(T_{2}\), \(T_{3}\) and \(T_{4}\), which are directly related to the signal's intrinsic characteristics, such as its energy content (here considered in the IPSD) and duration (selected by \(T_{4}\)). The elevated false negative rate observed with Parameter Set 2 results from the application of excessively restrictive parameters, leading to the exclusion of a significant portion of signals that are indeed whistlers. Conversely, the high false positive rate obtained with Set 3 indicates insufficiently stringent parameter selection, resulting in the erroneous inclusion of faint signatures misidentified as whistler waves. However, the parameters offer significant flexibility and can be tailored to meet diverse research goals. For instance, to maximize the detection of all potential whistlers, a parameter set similar to Set 3 (which exhibits the highest True Positive Rate) can be employed, acknowledging the associated increase in false positives. Conversely, for the stringent selection of only clear and intense whistlers and the minimization of false positives, a parameter set akin to Set 2 (which demonstrates the highest True Negative Rate) can be utilized, despite the potential exclusion of many whistlers with low-amplitude waveforms. For general applications, Set  
Figure 11: Average number of detected whistler per semiorbit for diurnal and nocturnal semiorbits. 1, which demonstrates high performance in both True Positive and True Negative Rates (96% and 94% respectively), represents the optimal choice. Given the focus on mid-to-low latitude regions (between \(-40^{\circ}\) and \(40^{\circ}\)), the observed whistlers are characterized by short durations, generally below 0.5 s. This is due to the fact that the signal duration is directly proportional to the propagation path length from the wave source to the observation point [28]. Indeed, the spatial distribution of the detected whistlers (Figure 8) aligns with the global lightning stroke density as recorded by the World-Wide Lightning Location Network (see Figure 2 in [51], Figure 4 in [52], Figures 17 and 18 in [53]). These results corroborate the findings reported in [54], which indicated that the most probable source regions for whistlers detected by the DEMETER satellite (orbiting in the top-side ionosphere at approximately 700 km) are located directly beneath the satellite's trajectory.