Scaler data from the Pierre Auger Observatory as a proxy of solar activity

TL;DR

Solar activity modulates low-energy Galactic Cosmic Rays reaching Earth, and long, high-statistics ground-based proxies are needed to study this process. The authors analyze a 16-year scaler-rate time series from the Pierre Auger Observatory, applying Auto-Regressive gap filling and Monte Carlo Singular Spectrum Analysis to extract significant multi-scale periodicities, corroborated by sunspot indices and wavelet analyses. They identify decadal, annual, and shorter periods (∼9, ∼6 months; ∼28, ∼20, ∼14 days) that explain most of the variance and exhibit anticorrelation with the solar cycle, including signatures related to the Hale cycle and solar rotation. The work demonstrates that Auger scaler data provide a robust proxy of solar variability and GCR modulation in the heliosphere, with potential for extended insights via the AugerPrime upgrade.

Abstract

Solar activity variations strongly impact the modulation of the flux of low-energy Galactic Cosmic Rays (GCRs) reaching the Earth. The secondary particles, which originate from the interaction of GCRs with the atmosphere, can be revealed by an array of ground detectors. We show that the low-threshold rate (scaler) time series recorded over 16 years of operation by the surface detectors of the Pierre Auger Observatory in Malargüe (Argentina) strongly reflects solar activity and can be considered as a new proxy of solar variability. To achieve this result, we apply advanced spectral methods to this time series and to the classical solar sunspot number and sunspot area series. We detect and compare highly significant variations with periods ranging from the decadal to the daily scale and identify the origin of each variability mode. In conclusion, we show that the Auger scaler data, thanks to the very low noise level and high statistical significance related to the very high count rates ($\sim 10^6$ counts per second), allow for a thorough and detailed investigation of the GCR flux variations in the heliosphere.

Figures (5)

• Figure 1: Relative scaler rates series from 01 January 2006 to 19 March 2022. The scaler rate in this figure was obtained by resampling the original series every 6 days after applying a gap-filling process relying on an Auto-Regressive model to the series. The rate incorporates all the corrections detailed in Schimassek:2020soa and the text.
• Figure 2: MC-SSA spectrum of the relative scaler rate. The Monte Carlo ensemble size is 10 000. The gray bars, which bracket 99% of the power values obtained from the ensemble, represent the Monte Carlo band. The significant spectral components are indicated by the red squares, while the black dots represent the spectral components that can be parameterized as red noise. The significant components with the same period specified in blue are grouped with blue boundaries.
• Figure 3: Comparison between the decadal trend revealed in the Auger scaler rate (black curve) and the SN series sampled every 6 d (shaded red curve), superimposed by the decadal modulation revealed in the latter by SSA (red curve). An anticorrelation among the decadal trends is visible. The shaded gray bar represents the total time interval required for the polar field reversal in both hemispheres from June 2012 to November 2014.
• Figure 4: Continuous Wavelet power spectrum (panel b) of the Auger scaler rate sampled every 48 hours (panel a) and Global Wavelet Spectrum (panel c). The black curves in panel b enclose regions with a confidence level greater than 90% against a red-noise process null hypothesis, while the COI, indicating regions influenced by edge effects, is represented by the white curve.
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