The impact of climate change on our world has been alarming and some of the signals for this are soil moisture, temperature changes. This study will examine the correlation between surface longwave downward irradiance and essential soil parameters, such as moisture and temperature, within the distinctive context of the Mediterranean region. Employing a robust regression-based analysis, our research seeks to quantitatively evaluate the influence of irradiance on these fundamental aspects of terrestrial ecosystems in an area renowned for its unique climatic and environmental characteristics. Through meticulous data gathering and preprocessing, we have compiled an extensive dataset tailored to the Mediterranean climate, encompassing measurements of surface longwave downward irradiance, soil moisture, and temperature from the 2021 to 2023. The regression model, crafted with careful consideration of both linear and advanced techniques, features surface longwave downward irradiance as the independent variable and soil moisture or temperature as the dependent variable. Results from the training phase underscore the model's efficacy, revealing low values for mean absolute error (MAE), mean squared error (MSE), coupled with a noteworthy R-squared value. The testing phase rigorously assesses the model's capacity to extrapolate to unseen Mediterranean data, providing insights into its performance within this distinctive climatic context. Understanding the regression model coefficients yields valuable insights into the impact of surface longwave downward irradiance on soil moisture and temperature, specifically tailored to the Mediterranean region.