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Reconstruction of radio-wave auroral absorption during magnetospheric substorm
Maria Shukhtina - Saint-Petersburg State University, Russia; Victor Sergeev - Saint-Petersburg State University,, Russia; Denis Rogov - Arctic and Antarctic Research Institute, St. Petersburg, Russia; Nikita Stepanov - Saint-Petersburg State University, Russia; Xiangning Chu - University of California, United States; Emma Spanswick - University of Calgary,, Canada; Tero Raita - Sodankyla Geophysical Observatory, University of Oulu, Finland
Energetic Electron precipitation (EEP) is an important magnetospheric substorm manifestation. EEP produces Cosmic Noise Absorption (CNA), braking radio- wave communication. Thus EEP and CNA modeling is a significant Space Weather problem.
Existing empirical EEP/CNA models are based on daily/hour geomagnetic indices (Ap or AE), not appropriate for substorms.
Our CNA model is based on the mid-latitude positive bay (MPB) index, which is the square of magnetic field horizontal component (H2=X2+Y2) at mid-latitude stations (McPherron&Chu,2017). As one of the main substorm acceleration mechanisms is betatron acceleration, CNA should be proportional to magnitude of dipolarization at the magnetospheric equator, which was shown to be proportional to mid-latitude H variation.
We use the linear prediction filter (LPF) technique connecting the current CNA value with MPB values during 4 preceding hours. The array of increments of square root of MPB index is the input, Canadian riometer data serving as output. LPFs are constructed with 5-min resolution for the center of the auroral zone (65-750 CGL) for all MLT sectors. The obtained response functions permit to calculate the CNA variation for substorms of arbitrary form and duration. The method was tested on a long disturbed interval and on independent Scandinavian riometer data with satisfactory result.
16 July 2020
Abstract submission opens:
16 July 2020
European Space Weather Medals:
6 September 2020
25 September 2020
Registration deadline: [extended]
10 October 2020
Abstract submission deadline:
4 September 2020