Daily heliospheric modulation potential (V23) and modelled GCR dataset compared to space measurements of the GCR energy spectrum.

The activity of the Sun modulates the fluxes of galactic cosmic rays arriving at Earth. This heliospheric modulation of cosmic rays is often quantified by the modulation potential, which describes the average energy loss of particles during their transport in the heliosphere. The modulation potential is a useful parameter not only for understanding the behaviour of energetic particles in the heliosphere, but also as a measure of solar activity. However, the validity of the modulation potential, which utilizes the force-field methodology, is uncertain for shorter timescales, and often the estimates are only monthly or yearly.

Recently, an updated estimation of the modulation potential was done at a daily time resolution by utilizing neutron monitor (NM) measurements from 10 stations. We have now analysed the daily version and compared it (via a LIS model) to the variation of the daily GCR energy spectrum (for rigidities 1 to 100 GV) measured by the AMS-02 instrument in the ISS. We find that overall, the daily modulation potential works well for estimating daily count rates at different energies. The correspondence is lowest for the low energy bins, where we see an excess of particles, which seems to follow the solar cycle. For rigidities around 4-13 GV, we can see a very clear match, letting us estimate daily count rates for different energy bins with a few per cent accuracy. For higher energies, the noise background of the measurements masks the underlying variation.

The result is very interesting and promising for the feasibility of using the modulation potential estimates for shorter time scales. This will lead to a better understanding of the variability of the overall modulation and the possibility of utilizing and combining NM and spacecraft measurements. The results will be useful in space climate (e.g. long-term solar variation induced from cosmogenic isotopes) and space weather (e.g. CME's/Forbush decreases, CIR's, Flares/GLE's) research. Future work with additional datasets and analysis of the different LIS models is planned.