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Implementation of the Revised SuperDARN MSTID MUSIC Algorithm in the DARNtids Analysis Toolkit

Nicholas
Guerra
First Author's Affiliation
University of Scranton
Abstract text:

The DARNtids analysis toolkit is a python-based software package that first detects levels of medium scale traveling ionospheric disturbance (MSTID) activity in SuperDARN data and then runs the MSTID Multiple Signal Classification (MUSIC) analysis software on event periods with significant MSTIDs. The SuperDARN MSTID MUSIC code is able to report MSTID period, wavelength, speed, and propagation direction for each detected MSTID. Recently, it was found that this SuperDARN MSTID MUSIC code has a systematic bias in reported propagation direction and methods are being developed to mitigate this bias. In this poster, we present the software architecture of the DARNtids code and show how the revised SuperDARN MSTID MUSIC algorithm is implemented in DARNtids. The revised algorithm is used to compute a climatology of MSTIDs observed by North American SuperDARN radars from 1 November 2015 – 1 May 2016.

Poster PDF
Student not in poster competition
Poster category
ITIT - Instruments or Techniques for Ionospheric or Thermospheric Observation