Multi-Year Climatology of Large-Scale Traveling Ionospheric Disturbances Observed with High Frequency Amateur Radio Receiving Networks Using a Novel Automated Detection Algorithm

We present a fully automated, deterministic technique for detecting and characterizing Large Scale Traveling Ionospheric Disturbances (LSTIDs) using 14 MHz amateur (ham) radio data. The method isolates wave periods between 1-5 hours and applies sinusoidal curve fitting to the first-hop skip-distance edge of observed communication ranges, yielding quantitative estimates of LSTID amplitude, period, and minimum RF skip distance. Data from the Weak Signal Propagation Reporting Network (WSPRNet), the Reverse Beacon Network (RBN), and PSKReporter, now merged and publicly available on the CEDAR Madrigal database, were used to produce a unified multi-year climatology of LSTID activity over the continental United States for 2015-2022. Fitted amplitudes exhibit a strong, repeatable seasonal cycle, with enhanced activity during winter and reduced activity during summer, broadly tracking the Polar Vortex index in contrast, geomagnetic activity characterized by the AE and SYM-H indices shows weak correspondence with these seasonal patterns. Minimum RF skip distance exhibits a clear inverse relationship with F10.7 solar flux across the full multi-year record, consistent with solar-cycle modulation of the background F-region ionosphere. These results are consistent with prior studies and suggest that LSTID variability is modulated by neutral wind filtering, sudden stratospheric warming (SSW), vertical coupling, and solar activity.