Scaling Cosmic Ray Neutron Flux for Enhanced Environmental Monitoring

Cosmic Ray Neutron Sensors (CRNS) are pivotal in measuring field-scale soil moisture, but uncertainties persist due to traditional methods of scaling parameter estimation, which often fail to consider site- and sensor-specific factors. This study integrates novel, data-driven approaches to refine scaling parameters for atmospheric pressure, air humidity and incoming cosmic ray intensity (β, ψ, ω) using measurement data. We demonstrate the strong potential for considerable improvents in the accuracy of CRNS-derived soil moisture estimates. Additionally, barometric correction in CRNS but also in neutron monitors is critical to account for local atmospheric density variations to minimize errors in soil moisture estimation and incoming cosmic ray intensity. Our analysis of CRNS and Neutron Monitor data from global stations reveals significant variability in barometric coefficients (β), influenced by geographical and atmospheric factors. The findings underscore the necessity for tailored scaling and correction methods to optimize CRNS applications in hydrology, agriculture, and climate research. Enhanced parameter estimation reduced RMSE by up to 25%, demonstrating potential for improved environmental decision-making and modeling accuracy.