Modeling Meteorological Effects on Cosmic Ray Muons Utilizing Multivariate Analysis

Abstract

AbstractCorrection of meteorological effects on muon component of secondary cosmic rays significantly extends the usability of muon monitors. We propose a new data driven empirical method for correction of meteorological effects on muon component of secondary cosmic rays, based on multivariate analysis. Several multivariate algorithms implemented in Toolkit for Multivariate Data Analysis with ROOT framework are trained and then applied to correct muon count rate for barometric and temperature effects. The effect of corrections on periodic and aperiodic cosmic ray variations is analyzed and compared with integral correction method, as well as with neutron monitor data. The best results are achieved by the application of linear discriminant method, which increases sensitivity of our muon detector to cosmic ray variations beyond other commonly used methods.