Generolo Jono Žemaičio Lietuvos karo akademija

Understanding how soil systems respond to atmospheric forcing requires analytical approaches capable of capturing not only instantaneous interactions but also delayed, cumulative, or depth‑dependent effects. In this study, we quantify the lagged response of soil‑moisture sensor to key meteorological variables across six monitoring stations, over the period 2022–2024. The meteorological dataset includes daily series of mean air temperature, total daily precipitation, sunshine duration, mean relative humidity and mean wind speed, while soil measurements represent three vertically installed within the natural soil profile moisture sensors with differing depths and thermal-hydric sensitivities. The resulting lag‑correlation heatmaps reveal that the soil–atmosphere coupling is highly station‑specific, displaying substantial variation in both the timing and the sign of the soil response. This analysis evaluates the instantaneous (lag 0) statistical relationships between daily meteorological variables and soil-profile responses at three depths (10 cm, 50 cm, 90 cm). Using Pearson correlation coefficients, we characterize how near-surface and sub‑surface layers respond to atmospheric forcing without temporal offset. The results confirm that day‑to‑day correlations are weak, especially in deeper horizons, reflecting the inherent delayed propagation of thermal and hydrological signals into the soil profile.