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Sudden ionospheric disturbance monitoring using a lightning detection network and machine learning

Mike Protts - Met Office; Edmund Henley - Met Office, United Kingdom; Andrew Horseman - Met Office, United Kingdom; Laura Dreyer - Met Office, United Kingdom; Samantha Adams - Met Office, United Kingdom; Stephen Prust - Met Office, United Kingdom; Ed Stone - Met Office, United Kingdom; Sue Twelves - Met Office, United Kingdom; Graeme Marlton - Met Office, United Kingdom; Debbie O'Sullivan - Met Office, United Kingdom

Session: Thermosphere-Ionosphere Interactions and Effects


Abstract

The new Met Office lightning detection system Leela measures very low frequency atmospheric electromagnetic radiation to identify lightning. 

Sudden changes in received signals not caused by lightning will, in some cases, arise from solar flares triggering Sudden Ionospheric Disturbances (SIDs). 

The Met Office Space Weather Operations Centre (MOSWOC) monitors space weather conditions - including solar flares, and the ionosphere - to inform users of potential impacts, e.g. on radio communication, or radars. 

Forecasting solar flares and resulting ionospheric disruptions is difficult, and there is value in MOSWOC having a monitoring/nowcasting capability.

Leela is also attractive as a ground-based alternative to the GOES satellites usually used, which can saturate for very large flares. 

We will present an overview of a recently-started project to use machine learning to detect anomalies in Leela data, and discriminate those associated with SIDs.



Approaching deadlines:

Registration opens:

16 July 2020

Abstract submission opens:

16 July 2020

European Space Weather Medals:

6 September 2020

Registration deadline:

25 September 2020

Registration deadline: [extended]

10 October 2020

Abstract submission deadline:

4 September 2020