Analyzing Solar Cycle Behavior Through Neutron Monitor Data: Insights from Inflection Points

Neutron monitor (NM) count rates provide a reliable, ground-based proxy of solar modulation of galactic cosmic rays (GCRs), exhibiting an inverse correlation with solar activity. In this study, we analyze NM data from the OULU station during Solar Cycles (SCs) 20 to 25 using an inflection-point methodology previously applied to sunspot number (SSN) data. We model the NM count rate time series using a modified empirical function and extract the value of the count rate at the inflection point, \(C_i(t_{\mathrm{IP}})\), corresponding to the steepest decrease in GCR intensity due to rising solar activity. We find that \(C_i(t_{\mathrm{IP}})\), calculated using only the first 1800 days of each solar cycle, strongly correlates with key solar activity metrics. For the OULU station, a linear regression between \(C_i(t_{\mathrm{IP}})\) and the average SSN (\(SSN_{\mathrm{av}}\)) across SC 20–24 yields a coefficient of determination of \(R^2 \approx 0.98\). Similarly, the correlation with the maximum SSN (\(SSN_{\mathrm{max}}\)) gives \(R^2 \approx 0.91\). These results indicate that \(C_i(t_{\mathrm{IP}})\) may serve as a robust early-cycle predictor of solar cycle strength. Applying this method to the ongoing SC 25, we obtain \(C_{25}(t_{\mathrm{IP}}) = 103.1821\) counts (OULU), which predicts an average SSN of \(81.1 \pm 5.9\). These findings demonstrate the potential of NM data, and in particular inflection-point analysis, as a predictive tool for characterizing solar cycle evolution based on cosmic ray modulation.