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 and period. Data from the Weak Signal Propagation Reporting Network (WSPRNet), the Reverse Beacon Network (RBN), and PSKReporter, which is now merged and available on the CEDAR Madrigal database, were used produce a unified multi-year climatology of LSTID activity over the continental United States (2016–2023). Results show clear seasonal patterns: enhanced LSTID occurrence during winter, weaker activity in spring and fall, and modest summer increases. These results are consistent with prior studies and suggest modulation by neutral wind filtering, sudden stratospheric warming (SSW), vertical coupling, and solar activity.