Statistical Analysis of Climatic Variables for Potential Frost Prediction Application

This article focuses on analyzing the behavior of climatic variables to predict and mitigate frost in agriculture. Given the increasing climate variability and its impact on food security, understanding extreme weather is crucial. Frosts consistently threaten agricultural production, causing significant losses in crops. The study explores the correlation between various climatic factors such as temperature, wind speed and direction, cloud cover, and humidity, and the occurrence of frosts. Climatic data collected over 9 months using a weather station with ground-level and 1.5-m temperature sensors, as well as sensors for rainfall, radiation, humidity, wind speed, and direction updated every 30 s, were analyzed. Key indicators such as clear skies, high temperatures, and turbulent winds preceding frosts emerged, prompting early alerts for farmers. Additionally, distinguishing between white and black frosts enhances precise crop protection. This information provides valuable insights for informed decision-making in agriculture, especially in potentially devastating frosts.