Automated identification of discrete, lightning‐generated, multiple‐dispersed whistler waves in C/NOFS‐VEFI very low frequency observations
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. P...
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| Published in | Radio science Vol. 51; no. 9; pp. 1547 - 1569 |
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| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
| Published |
Washington
Blackwell Publishing Ltd
01.09.2016
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| Subjects | |
| Online Access | Get full text |
| ISSN | 0048-6604 1944-799X 1944-799X |
| DOI | 10.1002/2016RS005989 |
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| Summary: | 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 |
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| Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 |
| ISSN: | 0048-6604 1944-799X 1944-799X |
| DOI: | 10.1002/2016RS005989 |