Soil moisture (SM), as the fundamental water source for vegetation (Miguez-Macho & Fan, 2021), dominates the ecosystem productivity (L. Liu, Gudmundsson, et al., 2020) and regulates terrestrial carbon uptake variability through land-atmosphere interactions (Humphrey et al., 2021). Among all interactions between SM and environmental factors, SM-temperature couplings significantly impact near-surface climates (Seneviratne et al., 2006). An increase in temperature might enhance evaporative demand and thereby promote evapotranspiration, leading to lower SM availability. In turn, drying soil conditions can further increase temperature by growing sensible heat flux, which is particularly responsible for temperature extremes such as heat waves (Seneviratne et al., 2010). Therefore, understanding the SM variations and their coupling strength with temperature is of vital importance for ecosystem and agriculture productivity and climate forecasting.Recently, two centuries-to-millennium summer SM series in dry inner Asia and southwest America was reconstructed by tree-ring width, and both studies suggest that the plunging SM in the past two decades was largely attributed to soaring temperature (Williams et al., 2020;Zhang et al., 2020) and enhanced by land-atmosphere interactions (Zhang et al., 2020). A hotter-drier regime seemed to be established in dry areas (Overpeck & Udall, 2020;Zhang et al., 2020). Although stronger SM-temperature couplings in dry regions than humid ones are commonly expected, SM also played an important role in temperature extremes in humid regions, such as the heatwave of 2003 in western Europe (WE) that resulted in tens of thousands of casualties (Miralles et al., 2014). However, to what extent the long-term SM variation has coupled with temperature over the past time in humid

Forest mortality and resilience driven by drought disturbances have attracted tons of attention. However, the acquisition of continuous spatial–temporal data is generally enslaved to the conventional field investigations. In this study, the resilience of semiarid forest was characterized with canopy dynamics from remote sensing observations, combining the variations in canopy greenness and water content. We integrated dense normalized difference vegetation index (NDVI) and normalized difference infrared index (NDII) time series from Landsat datasets, intending to assess the canopy resilience in 24 conifer patches along a climatic aridity gradient at the southern edge of the taiga in northern Mongolia and southern Siberia of Russia. The results exhibited four patterns of coordinated NDVI–NDII variation trends, indicating that the canopy water content of coniferous forests may decrease at first during a drought period, and sustained water loss may, in turn, induce an accompanying reduction in canopy greenness. Meanwhile, the patches with canopy recovery growth after initial declines were considered to have resilience to climate change. We further observed the combined effects of aridity degree and tree age on canopy resilience, and all seven patches with no resilience corresponded to the old‐tree group (the oldest trees reached or exceeded the age of 90). The observations indicated that the old‐growth forests in semiarid regions were less likely to show canopy resilience, which corresponded to a higher risk of sustained decline.

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