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Chinese Journal of Space Science ›› 2020, Vol. 40 ›› Issue (6): 1014-1023.doi: 10.11728/cjss2020.06.1014

• Research Articles • Previous Articles    

Distinguish Small-scale Traveling Ionospheric Disturbances and Equatorial Plasma Bubbles by Clustering Algorithm

WANG Ling, YIN Fan   

  1. School of Electronic Information, Wuhan University, Wuhan 430072
  • Received:2020-01-13 Revised:2020-04-17 Published:2020-12-09

Abstract: By analyzing the 50Hz high-frequency magnetic field data by Swarm from January 2015 to December 2019, according to the magnetic disturbances above the threshold in the perpendicular direction to the main field, Small-Scale Traveling Ionospheric Disturbances (SSTID) within ±45°N magnetic latitude have been detected. When detecting SSTID, Equatorial Plasma Bubbles (EPB) can be excluded by determining whether there is magnetic disturbance above the threshold in the direction which is parallel to the mean ambient field. However, when the disturbance is weak, the algorithm cannot completely exclude it. According to the different density distribution of SSTID and EPB in parameter space, the EPB can be distinguished by a density-based clustering algorithm. The results demonstrate that the clustering algorithm is very effective on separating EPB and SSTID in different two-dimensional parameter spaces and brings out a clear boundary between the high density region and low density region. The EPB identified by the clustering algorithm shows the strong dependence on solar activity and their statistical features are consistent with the previous study.

Key words: Clustering algorithm, Ionosphere, Small-Scale Traveling Ionospheric Disturbance (SSTID), Equatorial Plasma Bubble (EPB)

CLC Number: