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چکیده
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Identification of climatic parameters affecting soil temperature (ST) is essential in managing and controlling the damage caused by climate change on soil and its affected resources. Therefore, using monthly data of soil temperature (ST) at 10 cm depth and nine meteorological parameters including air temperature (AT), sunshine duration, relative humidity, dew point temperature, air pressure (QFE), wind speed, water vapor pressure, cloud cover, and precipitation of 30 high quality synoptic stations of Iran in the period 1993 to 2017 and using the partial least squares (PLS) method, the most effective meteorological parameters affecting ST were identifed on a seasonal and annual time scales for three ST regimes (mesic, thermic, and hyperthermic). In general, the PLS model suggests better performance in the thermic regime on a seasonal scale (winter and summer) and in the hyperthermic regime on an annual scale. In the summer of thermic regime, the PLS model with fve hidden components showed the best result in estimating the monthly mean ST at depth of 10 cm. The most important parameter afecting ST in all three thermal regimes and on a seasonal and annual time scales was AT, which was signifcantly more important than other parameters. The mean VIP values for AT in the studied thermal regimes were 1.5, 1.6, and 1.2 in summer, winter, and annual scale, respectively. On the annual scale of the mesic regime, water vapor pressure, and dew point temperature and in the thermic and hyperthermic regimes, the sunshine duration and the water vapor pressure were found to be more important parameters after the AT. Actually water vapor will have positive feedback on increasing AT and ST by increasing air heat capacity, acting as a greenhouse gas, and trapping longwave radiation. Results showed that the sunshine duration is the most infuencing parameter in estimating the ST in the summer of mesic regime than the thermic and hyperthermic regimes. This may be due to the location of th
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