Physical evaluation of active soil layer can be a suitable indicator for detecting climate change trends, especially the temporal study of soil and air temperatures. Using the singular spectrum analysis (SSA), trends, oscillatory components, and the degree of the coincidence of the soil temperature (ST) versus air temperature (AT) and precipitation (Prc) time series were investigated in Iran for three thermal regime classes (mesic, thermic, and hyperthermic) during 1993–2017. The results showed that the highest and lowest increases in ST trend occurred in the mesic and thermic thermal regimes, respectively. The return period of approximately 2.1 to 2.6 years was detected in all three studied thermal classes likely as a result of quasi-biennial oscillation (QBO) variation. In the mesic regime, the annual ST was affected to an equal extent by almost every season. For the thermic regime, the annual ST was most influenced by the ST oscillations in autumn and spring and regarding the hyperthermic regime in winter and summer. Result demonstrated by the implementation of the coincidence which exists between the short- and long-term oscillations of ST and AT time series, one can generate and reconstruct ST data gaps based on AT.
