Contrasting Temperature and Precipitation Patterns of Trees in Different Seasons and Responses of Infrared Canopy Temperature in Two Asian Subtropical Forests

Canopy temperature (Tc), one of the most important plant ecophysiological parameters, has been known to respond rapidly to environmental change. However, how environmental factors—especially the temperature and precipitation pattern—impact Tc has been less discussed for forest stands. In this study, we investigated seasonal variations and responses of the Tc and canopy-to-air temperature difference (ΔT) associated with environmental conditions in two subtropical forests with contrasting temperature and precipitation patterns—Dinghushan (DHS) (temperature and precipitation synchronous site: hot and wet in the summer) and Qianyanzhou (QYZ) (temperature and precipitation asynchronous site: hot and arid in the summer). The results showed that Tc exhibits clear diurnal and seasonal variations above air temperature throughout the day and year, suggesting that the canopy of both DHS and QYZ is typically warmer than ambient air. However, the canopy-warming effect was substantially intensified in QYZ, and the difference of ΔT between dry and wet seasons was small (−0.07 °C) in DHS, while it was up to 0.9 °C in QYZ. Regression analysis revealed that this resulted from the combined effects of the increased solar radiation and vapor pressure deficit (VPD), but reduced canopy conductance (gc) caused by drought in the summer in QYZ. Sensitivity analysis further indicated that the responses of ΔT to VPD and gc changes were quite divergent, presenting negative responses to the enhanced VPD and gc in QYZ, while there were positive responses in DHS. The high productivity coupled with low transpiration cooling that occurs in a temperature and precipitation synchronous condition mainly contributes to the positive responses of ΔT in DHS. This study reveals the seasonal variations, environmental responses, and underlying causes of Tc under different temperature and precipitation patterns, providing useful information for the regional assessment of plant responses to future climate change.