Cosmic Ray Inter-Station Correlation Variations as Precursors of Geomagnetic Storms: A Statistical Study and Multi-Parameter Early Warning Framework

TL;DR

The paper tackles the challenge of extending geomagnetic storm predictive lead times by exploiting galactic cosmic ray (GCR) variations observed by a global neutron monitor network. It develops a three-stage analysis combining flux correlations, inter-station differences, and anisotropy metrics, introducing a simplified anisotropy indicator suitable for real-time monitoring. A two-stage, multi-parameter early warning framework is proposed, with mid-term anisotropy signals (48–96 h) identifying precursors and short-term flux-based metrics (0–48 h) grading storm intensity; this approach is validated on two representative extreme and severe storms. The findings show strong, intensity-dependent links between GCR characteristics and geomagnetic activity, suggesting practical pathways to extend GS prediction windows beyond traditional L1-based methods and to inform protective actions for critical infrastructure.

Abstract

The modulation of galactic cosmic rays (GCRs) by interplanetary disturbances, manifested as Forbush decreases (FDs), has long been recognized as a signature of coronal mass ejection (CME) passages through the heliosphere. While individual FD events have been extensively studied, systematic investigations of how GCR inter-station correlation variations relate to geomagnetic storm (GS) intensity have not been established. Here we analyze the relationship between GCR characteristics (from a global NM network) and GSs, aiming to understand the physical mechanisms of heliospheric disturbances and to develop complementary predictive capabilities beyond existing L1 solar wind monitoring. By applying a newly introduced anisotropy characteristic method alongside correlation analysis to 25 years of hourly NM data (1995-2020, seven stations), we demonstrate significant correlations between GCR parameters and geomagnetic activity. Inter-station relative differences and anisotropy enhancements show distinct precursor signatures depending on storm intensity, with extreme events displaying detectable signals 48-96 hours in advance. Based on these intensity-dependent response patterns, we propose a "two-stage multi-level" early warning framework: mid-term identification (48-96 hr) triggered by sustained anisotropy increases, followed by short-term grading (0-48 hr) based on inter-station relative difference variations and high-latitude flux changes. Validated on the extreme November 2003 and severe August 2018 geomagnetic storms, our approach successfully identifies precursor signals, providing a potential means to extend GS prediction windows.

Figures (4)

• Figure 1: Temporal evolution of Spearman correlation coefficients between GCR parameters and Dst index across five consecutive 20-hour segments before storm peak for (a) minor, (b) moderate, (c) severe, and (d) extreme storms. Each panel shows correlations for individual station fluxes and the inter-station relative difference $\delta$. Higher absolute values indicate stronger predictive capability. Note the distinct temporal patterns: $\delta$ peaks at 0--20 hours for severe storms ($r_s = -0.568$), while extreme storms show the strongest flux correlations in the same window.
• Figure 2: Spearman correlation coefficients between GCR parameter statistics (mean, standard deviation, range) and Dst statistics across different time windows (6, 12, 24, 48 hours). The $\delta$ parameter demonstrates consistently strong negative correlations across all window lengths, supporting its utility as a robust warning indicator.
• Figure 3: Cosmic ray variations during the 2003 November 20 extreme geomagnetic storm ($\mathrm{Dst_{min}} = -422$ nT). Top panel: Time series of relative cosmic ray flux deviations from quiet-period baselines for all seven neutron monitor stations (OULU, JUNG, SOPO, THUL, KERG, PTFM, TSMB). Each colored curve represents a different station, showing the temporal evolution of flux variations during the 100-hour period surrounding the storm. Note the initial synchronized decrease followed by spatially divergent responses as the storm main phase develops. Bottom panel: Comparison between the basic anisotropy characteristic $A_{\mathrm{basic}}$ (red curve, left axis) and the Dst index (blue curve, right axis, sign reversed for visualization). The vertical dashed line marks the storm peak time (minimum Dst). The pronounced anisotropy enhancement preceding and during the main phase demonstrates the method's sensitivity to approaching CME structures.
• Figure 4: Cosmic ray variations during the 2018 August 26 severe geomagnetic storm ($\mathrm{Dst_{min}} = -176$ nT). Top panel: Time series of relative cosmic ray flux deviations from quiet-period baselines for all seven neutron monitor stations. Unlike the 2003 extreme event, this storm exhibits more complex spatiotemporal evolution with non-synchronous flux variations appearing 40--80 hours before the storm, followed by convergence toward uniform decreases approximately 20 hours before the peak. Bottom panel: Basic anisotropy characteristic $A_{\mathrm{basic}}$ (red) and Dst index (blue, sign reversed). The anisotropy shows elevated values during the early non-synchronous phase (indicating directional modulation) before the global suppression phase begins. This two-phase pattern supports the rationale for a two-stage warning framework combining mid-term anisotropy monitoring with short-term flux analysis.