Speaker
Description
Investigating the intricate relationship between galactic cosmic rays (GCR) and solar activity is fundamental to our understanding of the physical mechanisms governing particle transport within the heliosphere. It also provides critical insights into radiation exposure and associated risks for space missions. In this study, we present advancements in our predictive model for solar modulation, designed to capture key particle transport processes such as diffusion, drift, convection, and adiabatic cooling. This model computes the energy spectrum and temporal evolution of cosmic radiation in the inner heliosphere with high fidelity. To improve its accuracy, particularly in the low-energy range, we calibrated and validated the model using the latest cosmic-ray data from space-based instruments, including AMS-02 aboard the International Space Station and ACE spacecraft. We established a robust cross-correlation between the model’s free modulation parameters and the sunspot number (SSN), serving as a proxy for solar activity. To enhance accuracy, we applied advanced signal decomposition techniques to filter out short-term periodicities typically associated with transient solar events such as flares and coronal mass ejections (CMEs). This correlation enables a solar cycle- and species-independent generalization, paving the way for long-term forecasting of GCR flux based solely on the knowledge of SSN. The model not only reproduces observations accurately but also demonstrates significant potential for space radiation monitoring and forecasting.
| Do you plan to attend in-person or online? | In-person |
|---|
