- 1Austrian Space Weather Office, GeoSphere Austria, Graz, Austria
- 2Institute of Physics, University of Graz, Graz, Austria
- 3Institute for the Study of Earth, Oceans, and Space, University of New Hampshire, Durham, NH, USA
- 4Kanzelhöhe Observatory for Solar and Environmental Research, University of Graz, Treffen am Ossiacher See, Austria
- 5Conrad Observatory, GeoSphere Austria, Vienna, Austria
Predicting the geomagnetic effects of coronal mass ejections (CMEs) remains a significant challenge in space weather forecasting. Spacecraft positioned upstream of L1, referred to as sub-L1 monitors, present a promising observational approach to addressing this problem. Such monitors have the potential to enhance both the lead-time and accuracy of geomagnetic storm forecasts.
In a hindcast analysis, we demonstrate that the geomagnetic impact of the May 2024 superstorm—a complex event involving at least five interacting CMEs that led to the strongest geomagnetic storm since 2003—was reasonably well reproduced using real-time data from the STEREO-A spacecraft. This spacecraft, positioned at 0.956 AU and 12.6° west of Earth, acted as a sub-L1 monitor during this event and observed the associated interplanetary shock 2.57 hours prior to its detection at L1.
Between November 2022 and June 2024, STEREO-A passed 0.05 AU ahead of the Wind spacecraft at ±15° heliospheric longitude, corresponding to the longitudinal separation for which monitoring below L1 is considered feasible. During this time interval, ten severe geomagnetic storms (Dst < -100 nT) and several moderate storms (Dst < -50 nT) were observed. This favourable spacecraft configuration enables a first robust statistical analysis of the utility of sub-L1 monitoring for space weather forecasting.
To refine our methodology and address unresolved questions from the May 2024 analysis, we apply solar wind-to-Dst models to both STEREO-A and L1 solar wind data. By comparing model outputs to observed geomagnetic indices, we quantify the predictive performance and disentangle contributions from observational and modelling uncertainties. Furthermore, we examine the influence of longitudinal separation between the spacecraft on prediction accuracy.
With this statistical analysis we aim to establish a critical benchmark for the development of future missions that leverage upstream monitoring to advance space weather forecasting capabilities.
How to cite: Weiler, E., Möstl, C., Davies, E., Amerstorfer, T., Lugaz, N., Amerstorfer, U., Veronig, A., and Haberle, V.: Advancing Space Weather Forecasting with Sub-L1 Monitors: A Statistical Analysis , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10611, https://doi.org/10.5194/egusphere-egu25-10611, 2025.
