Measurements of Forbush Decrease Events at the Center of the South Atlantic Magnetic Anomaly with Muon Detectors

Overview This dataset contains measurements of cosmic-ray muons collected in Paraguay, located at the center of the South Atlantic Magnetic Anomaly (SAMA). The measurements were conducted using a low-cost muon detector constructed with scintillation plates coupled to silicon photomultipliers (SiPM). The dataset spans two observation periods, capturing Forbush decrease (FD) events in May and October 2024 and their correlation with geomagnetic disturbances. Contents The dataset is structured into two periods: First Period (May 2024) data/first_period/muon_counts.csv – Time series of muon flux measurements. data/first_period/dst.csv – Disturbance Storm Time (Dst) index values. data/first_period/neutrons.csv – Neutron monitor data. data/first_period/fiuna.csv – Raw muon detector data. data/first_period/muones_corregidos.csv – Muon counts corrected for pressure and temperature. data/first_period/muons_may_junecorrected.csv – Muon counts for May–June, corrected. data/first_period/profileweather_teff.csv – Weather profile data (temperature, pressure). data/first_period/profileweather.csv – Additional weather data. data/first_period/vasouras.csv – Reference data from Vasouras station. Second Period (October 2024) data/second_period/muon_counts.csv – Time series of muon flux measurements. data/second_period/dst.csv – Dst index values. data/second_period/neutrons.csv – Neutron monitor data. data/second_period/fiuna.csv – Raw muon detector data. data/second_period/muons_sep_octcorrected.csv – Muon counts for Sep–Oct, corrected. data/second_period/neutron_second_period.csv – Neutron monitor data for second period. data/second_period/profileweather_teff.csv – Weather profile data. data/second_period/profileweather.csv – Additional weather data. data/second_period/vasouras.csv – Reference data from Vasouras station. Each file is formatted as a CSV table with time-stamped measurements at a fixed sampling rate. Methodology The detector was deployed at a location where the geomagnetic cutoff rigidity is 9.63 GV. Muon flux was recorded continuously and analyzed using the Truncated Time-Shift (TTS) test, a statistical method for detecting transient correlations in time series. The dataset is complemented with Dst index values obtained from geomagnetic monitoring databases and neutron flux data from global neutron monitor networks. Usage and Applications Space weather research: Investigating cosmic-ray variations and their relationship with geomagnetic storms. Muon detector validation: Benchmarking low-cost detection systems in high-radiation environments. Machine learning & time-series analysis: Developing models for forecasting cosmic-ray intensity variations. Software and Analysis analysisfirstperiod.ipynb – Jupyter Notebook for May–June 2024 FD event analysis, including temperature and pressure corrections and statistical testing. analysissecondperiod.ipynb – Jupyter Notebook for September–October 2024 FD event analysis, with similar methodology as the first period. analysisWithTeff.ipynb – Notebook demonstrating a simplified analysis workflow, matching the published paper, with step-by-step explanations. temperaturaPresureCorrection.py – Python script for correcting muon counts using atmospheric pressure and temperature data, generating figures and a corrected CSV. donwloadGdas.py – Script to download GDAS meteorological data from NOAA FTP servers for further analysis. New Analysis and Plotting Notebooks plot_and_analysis.ipynb – Notebook for visualizing and analyzing muon, pressure, temperature, neutron, and DST data for both periods. Includes hourly resampling, outlier removal, and comparative plots. plot_analysis_magnetic_and_muons.ipynb – Notebook for joint analysis and plotting of magnetic field data (from Vasouras station) and muon data, including percent change calculations and event marking. Other Files requirements.txt – List of dependencies required to run the analysis. README.md – Documentation of the repository.