Speaker
Description
Investigating the relationship between galactic cosmic rays (GCRs) and solar activity is fundamental for understanding the physical mechanisms that govern particle transport in the heliosphere. Using multi-channel GCR flux data and solar activity proxies, previous studies have employed cross-correlation techniques, wavelet-coherence analyses, and information-theory- based methods, often framed within the force-field approximation to interpret the rigidity dependence of the modulation. Given the intrinsic non-linearity and non-stationarity of the data, we adopt a non-parametric approach based on Empirical Mode Decomposition to first sepa rate each time series into its intrinsic components. By identifying the modes that correspond to the shared space-climate dynamics between both signals, we compute their phase differ ence through Hilbert spectral analysis, leading to the determination of the time lag. Using a comprehensive multi-instrument and multi-species dataset, we determine the time lag be tween cosmic-ray intensities and several solar activity proxies, and we compare these findings with those obtained from well-established analyses. Our results reveal the time variability and characteristic patterns of the GCR–solar-proxy lag and provide qualitative confirmation of its expected charge-sign dependence. They explicitly highlight the role of gradient and curvature drifts in shaping these time-dependent effects within the heliosphere. Overall, our results offer important constraints for next-generation predictive models of cosmic-ray fluxes based on so lar activity proxies and contribute to improving long-term radiation-risk assessments for future human space exploration.