Technical Article

Real-time detection of solar flares from ground-based VLF data

¹ LIRA, Observatoire de Paris, Université PSL, Sorbonne Université, Université Paris Cité, CY Cergy Paris Université, CNRS, Meudon, France
² School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA

^* Corresponding author: This email address is being protected from spambots. You need JavaScript enabled to view it.

Received: 24 November 2025
Accepted: 11 May 2026

Abstract

A method for real-time solar flare detection and characterization using ground-based Very Low Frequency (VLF, 15–45 kHz) data is presented. The D-region, the ionosphere’s lowest region, is monitored by VLF waves propagating in the Earth-Ionosphere waveguide. The D-region electron density increases during sudden surges in X-ray radiation from solar flares. This subsequently enhances HF absorption. By seeking trend changes in VLF phase data, an incremental algorithm finds solar flares. 82.7% of M and X solar flares are detected within one fourth of their rise time. In addition, several VLF transmitters are monitored simultaneously. Combining information from their phase variations leads to an estimation of the Sun’s X-ray flux. Last, propagation models such as LMP or LWPC are combined with the VLF measurements to compute D-region electron density profiles. This method and its implementation in a new Python package are a step towards building a more resilient system for flare detection and alerts. Its reliance on ground-based data alone ensures an easy maintenance and a backup in case a satellite failure. It can provide earlier ionospheric impact detection than operational M5 satellite alerts in many cases, due to shortened data latency.