Speakers
Description
The modulation of galactic cosmic rays (GCRs), driven by the evolution of the heliospheric magnetic field, strongly influences the intensity of cosmic rays reaching near-Earth space. Characterizing this process is crucial both for advancing our understanding of cosmic-ray transport and for assessing radiation exposure and related hazards in space environments.
Here we present the PGLis model, a newly developed forecasting framework designed for the long-term prediction of galactic cosmic-ray fluxes near Earth. The model is the result of a synergistic effort between the Università degli Studi di Perugia (PG) and LIP - Laboratório de Instrumentação e Física Experimental de Partículas in Lisbon (Lis), and is based on a numerical solution of charged-particle transport in the heliosphere, coupled to the temporal variability of solar-activity proxies.
The PGLis model has been validated using multi-species flux measurements from space-based instruments such as PAMELA, AMS-02, and ACE, implementing signal demodulation techniques and a cross-correlation strategy between delayed solar sunspot number and effective modulation parameters. This approach accounts for the dynamic time-delay response of GCR fluxes with respect to solar activity.
The model demonstrates strong performance in reconstructing and forecasting across a broad, multi-channel, multi-species testing dataset, spanning different energy ranges and solar phases.
When combined with flux-to-dose conversion calculations, the model also shows strong capability in reconstructing dosimetric measurements in near-Earth space.
Furthermore, when coupled with solar-proxy forecasting models, PGLis enables decadal-scale predictions of GCR fluxes, thereby supporting long-term planning and radiation-risk assessment for future space missions.