Understanding how soil systems respond to atmospheric forcing is critical not only for environmental science but also for defence operations requiring accurate terrain assessment. This study quantifies depth‑dependent and delayed soil responses to meteorological drivers using lag‑correlation analysis across six operational military monitoring stations (2022–2024). The results demonstrate that soil–atmosphere coupling exhibits strong station‑specific variability, with response times ranging from hours to several weeks depending on soil type and depth.
The analysis reveals weak instantaneous (lag 0) correlations but significantly delayed relationships, particularly in deeper soil layers, confirming that terrain conditions relevant for military mobility cannot be reliably inferred from current weather alone. Instead, cumulative and lagged atmospheric effects govern soil bearing capacity, trafficability, and subsurface stability.
These findings directly support defence applications, including terrain trafficability forecasting, planning of off‑road operations, sensor deployment optimization, and decision‑support systems. The proposed lag‑correlation framework provides a practical analytical tool to enhance situational awareness and operational readiness under dynamically changing meteorological conditions.
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.