## 3 Results
### Different Responses of Vegetation to CHD Events of Varying Intensities
To validate the above conclusions, we further analyzed the probability density distribution (PDF) of climatic and vegetation-related anomalies in the YRB (Figure 8), and the results further support our findings. During the extreme CHD event in 2022, positive T2m anomalies concentrated around 2.0 STD, and the maximum anomalies can exceed 4.0 STD. At the same time, negative SM anomalies mainly centered around \(-2.0\) STD, with extreme values exceeding \(-6.0\) STD. Correspondingly, GPP showed negative anomalies over most grid points, with extreme values reaching over \(-6.0\) STD (Figure 7a). In contrast, in 2003  
Figure 7: The probability density distribution (PDF) of vegetation-related anomalies (units: %). The blue, yellow, and red lines represent the CHD years 2003, 2013, and 2022, respectively. The solid lines and short- or long-dashed lines represent products GPP\({}_{\text{GOSIF}}\), GPP\({}_{\text{FluxSat}}\), and EVI\({}_{\text{MODIS}}\), respectively. Panels represent regions of (**a**) the entire defined YRB and grid points dominated by (**b**) evergreen forests (EF), (**c**) deciduous forests (DF), (**d**) mixed forests (MF), (**e**) shrubs, and (**f**) crops, respectively. and 2013, the positive temperature anomalies and negative soil moisture anomalies were more evenly distributed, and the intensity of extreme values was much lower than those in 2022. Therefore, in the two years, GPP anomalies were mainly concentrated around zero, and extreme values were around \(-3.0\) STD, which is half of that in 2022 (Figure 7a). Additionally, the PDF analysis also clearly reflects the different responses of the five vegetation types to the extreme CHD events. In 2022, the greatest differences in GPP responses were observed between deciduous forests and shrubs, and their PDF profiles differed significantly. For example, compared to deciduous forests, shrubs had a higher proportion and greater intensity of negative GPP anomalies (Figure 7). However, for climate anomalies, there was no obvious difference in the PDF profiles between deciduous forests and shrubs in 2022 (Figure 8). Their positive T2m anomalies and negative SM anomalies were both centered around \(2.0\) STD and \(-2.0\) STD, with extreme values reaching \(4.0\) STD and \(-6.0\) STD, respectively. Additionally, the comparison between deciduous forests and evergreen forests shows an opposite phenomenon. For T2m, most evergreen forest-dominated grid points showed weaker positive anomalies than deciduous forest-dominated grid points (Figure 8a). Nevertheless, the intensity and proportion of negative GPP anomalies for evergreen forests were still higher than those for deciduous forests. These differences illustrate that other climatic variables may be key factors causing the different responses between evergreen forests and deciduous forests. In comparison, although there were slight differences in climate anomalies among the five vegetation-dominated areas in 2003 and 2013, their GPP response differences were not particularly significant between the two years. Figure 9 shows the analysis of climatic and vegetation-related anomalies exceeding one STD, which are considered significant changes. The results clearly indicate that the extent  
Figure 8: The probability density distribution (PDF) of climatic anomalies (units: %). The blue, yellow, and red lines represent the CHD years 2003, 2013, and 2022, respectively. Panels **(a–d)** represent variables 2 m air temperature (T2m), soil moisture (SM), vapor pressure deficit (VPD), and downward solar radiation (DSR), respectively, for the whole defined YRB (All) and grid points dominated by evergreen forests (EF), deciduous forests (DF), mixed forests (MF), shrubs, and crops. of significant climate anomalies in 2022 was much broader compared to 2003 and 2013. Over 90% of the grid points in the whole YRB experienced anomalies in T2m, SM, and VPD exceeding one STD in 2022 (Figure 9c). In contrast, the proportion of grid points with significant anomalies in 2003 and 2013 was around 50%.