## 4 Discussion  
Both the SVPDI and SSMI showed significant increasing trends across the TRHR during the GS, suggesting an increasing trend in both atmospheric dryness and SM. An increase in the VPD can be primarily attributed to the increased saturated vapor pressure due to warming [9]. This warming, coupled with increased precipitation and the melting of ice, snow, and permafrost, has led to increased SM levels in the TRHR [42]. Geospatially, the SVPDI distribution exhibited a clear dichotomy between the eastern and western parts of the TRHR, with the atmosphere in the eastern areas becoming wetter, while the western parts became drier. SM, on the other hand, demonstrated marked upward trends, barring a small section of the east-central region. The concurrent rise in the SVPDI and SSMI underscores the significant warming and wetting that has occurred across the TRHR [43]. There is an increased probability of heat-related events under global warming, which in turn increases the probability of atmospheric droughts characterized by a high VPD [9; 44]. An atmospheric drought can actively drive terrestrial evapotranspiration and thus accelerate SM depletion. The reduction in SM leads to a decrease in evapotranspiration, which reduces latent heat and increases sensible heat, which further increases temperature and the VPD [5]. Ultimately, there is an increasing probability of concurrent atmospheric and soil droughts through strong land-atmosphere coupling [6]. Compound droughts showed a general upward trend in the TRHR, with larger increases in the GS compared to the entire year during 2001-2020. A similar pattern was observed by [PERSON] and [PERSON] [45], who pointed out that compound drought and heat events have significantly increased on the Tibetan Plateau. Further, the probability of the occurrence of low SM in tandem with compound drought and heat events is greater than that of individual events. The spectral emission profile of SIF encompasses approximately 650-800 nm within intact leaves, with two peaks in the red spectral region (around 685-690 nm) and near-infrared spectral region (about 730-740 nm) [24]. The inherent capacity of SIF to directly capture the dynamic processes of plant photosynthesis makes it a valuable indicator for monitoring vegetation growth and stress responses [19; 46]. All three of the SIF datasets used in this study showed high values in the southern and eastern regions of the TRHR, which mirror the spatial patterns derived previously from net primary productivity data by [PERSON] et al. [47]. These regions, due to their lower elevations, higher temperatures, and increased precipitation compared to other parts of the region, offer favorable conditions for robust vegetation growth. The notably high correlation coefficients observed between SIF and GPP, especially in the eastern parts of the TRHR (>0.9), further suggest that SIF can be used as a proxy for GPP to explore vegetation dynamics and carbon cycling processes across the region. The SIF exhibited a clear overall upward trend in the TRHR, indicating a clear greening signal from the region's vegetation. The discernible increase in temperature and precipitation within the TRHR has engendered substantial warming and increased moisture availability, thereby fostering an environment conducive to plant growth. Notably, the decadal attenuation of the summer westerly wind regime, accompanied by increased wetting, has also played an important role in vegetation greening within the TRHR [48]. The SMCII.0 data used in this study closely align with in situ SM data for the entirety of China, but SMCII.0 is not guaranteed to be of high quality in every region of China due to the uneven distribution of in situ SM stations, especially in the western part of the country [31]. Multiple SM datasets from different sources (e.g., observations, remote sensing, and model simulations) can be fused via a triple collocation analysis [49; 50] to further assess the changes in SM and soil drought in the TRHR.