# Automatic Detection of Whistler Waves in the Top-Side Ionosphere: The WhISPER Technique
## 4 Discussion and Conclusions
The only notable discrepancy between the lightning and whistler distribution patterns is the reduced whistler occurrence over the Amazon region, despite the high lightning activity. This disparity may be attributed to the significant impact of South Atlantic Anomaly (SAA) on whistler propagation. Indeed, consistent with our findings, [PERSON] et al. [55] reported a reduced whistler occurrence at the longitudes of the SAA in DEMETER data compared to Van Allen Probes observations. Furthermore, the observed seasonal patterns, characterized by increased activity during local summer months (Figure 9), align with findings from previous studies on lightning distribution. Specifically, [PERSON] et al. (2006) [49] reported an increase in lightning flash density over southern Africa during the local summer months (from December to February); [PERSON] et al. (2016) [56] observed a similar seasonal pattern in the United States, with 64% of annual cloud-to-ground lightning flashes occurring in the local summer (between June and August); [PERSON] and [PERSON] (2014) [57] found a peak in ground flash density in Australia during the warm season (from November to April). Additionally, the whistler detection is not significantly influenced by geomagnetic conditions, as evident by the similar PDFs of whistler per semiorbit during different geomagnetic periods (Figure 10), indicating the neutral atmospheric origin of the detected signals [58]. The observed higher detection rate of whistlers during nighttime (Figure 11) is in agreement with previous studies on whistler occurrence, which report that whistlers are predominantly a nighttime phenomenon (see, e.g., [59]). The presented results, consistent with established literature on lightning and whistler occurrence, provide further validation for the WhISPER technique's efficacy in detecting whistlers from magnetic field data at ionospheric altitudes (\(\sim\)500 km). Beyond its exceptional detection accuracy, interpretability, and adaptability, a key advantage of this technique is its computational efficiency. Since high-resolution spectrograms are utilized solely for validation, whistler identification can be performed using only PSD data, directly provided by the satellite. Consequently, the comprehensive whistler search from 2019 to 2022 was completed in approximately 70 h on a standard laptop (CPU: AMD Ryzen 5 7530U, RAM: 8 GB), yielding an average processing time of approximately 7 s per semiorbit. This level of computational efficiency and speed is, to our knowledge, unmatched by any other existing automated whistler detection procedure. As a benchmark, the AWD technique detailed in [22] required a processing time of 5 to 10 min for each hour of data on a 3 GHz PC, indicating that WhISPER is approximately 25-50 times faster. To the best of our knowledge, this study presents the first extensive detection of whistlers using top-side ionosphere data. Indeed, previous detection or analysis methods have primarily relied on ground-based observations [22; 59; 60; 22] or satellite data from other regions of the circumterrestrial space [28; 41; 61; 62] or documented a significantly lower number of detected events in the top-side ionosphere (e.g., in [63] the authors identified hundreds of whistlers using DEMETER satellite data). Furthermore, the high sampling frequency of SCM enables the generation of clearer spectrograms compared to previous studies, such as those utilizing burst-mode data sampled at 250 Hz from Swarm satellite Absolute Scalar Magnetometers [64] or those conducted in noisier environments (e.g., [22]). Consequently, spectrograms and waveforms derived from SCM data (such as those shown in Figure 3) enable highly precise determination of whistler characteristics, including amplitude, duration, and frequency range. The comprehensive and detailed characterization of whistler wave characteristics, including dispersion, direction of propagation, and the subsequent derivation of electron density, will be detailed in Part 2.