Winners announced for the Space Weather Competition. Visit http://esws2020.iopconfs.org/winners for details.
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
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.
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