This research develops a reliable methodology for estimating minimum temperature distribution in agricultural areas, focusing on frost conditions threatening crop production. The data was collected across the plain of Krya Vrysi in Central Macedonia. The approach uses linear regression equations between daily minimum temperatures from a central station and 12 autonomous temperature sensors with data loggers. Statistical analysis covered winter 2023–2024, with 2025 validation showing exceptional predictive capability—R2 values of 0.97–0.99 and RMSE of 0.34–0.58 °C. Spatial interpolation employed the Radial Basis Function with thin plate splines, effective for agricultural microclimatic interpolation. This methodology provides an operational frost prediction tool, enabling targeted interventions, reducing production losses and enhancing agricultural resilience.
Chronopoulos et al. (2025) studied this question.