Automated identification of discrete, lightning‐generated, multiple‐dispersed whistler waves in C/NOFS‐VEFI very low frequency observations. Issue 9 (24th September 2016) - Jacobson, Abram R.; Holzworth, Robert H.; Pfaff, Robert; Heelis, Roderick
Abstract: Automated wave feature detection is required to efficiently analyze large archives of very low frequency broadband recordings for discrete whistler identification and feature extraction. We describe a new method to do this, even in the presence of simultaneous, multiple whistler phase dispersions. Previous techniques of whistler identification were unable to deal with simultaneous, multiple phase dispersions. We demonstrate the new method with data from the Vector Electric Field Investigation (VEFI) payload on the Communication/Navigation Outage Forecast System (C/NOFS) satellite, from the mission years 2008–2014. Key Points: Frequently whistlers occur amidst multiple dispersions Multiple dispersions complicate whistler identification We have developed a new automated identification algorithm for this