## 3 Results
### Correlations between Air Temperature Indices and Plant Growth  
The above results indicated that temperature factors have demonstrated complex variations during the past decades. The interaction of arid weather conditions and significant temperature discrepancies can have intricate effects on plant growth. To explore the connection between plant growth and air temperature indicators while removing potential confounding effects between the two variables, a partial correlation analysis was conducted. Additionally, in order to mitigate the potential influence of a single data source, partial correlation analysis of GPP and temperature indices were also examined. On the whole, T\({}_{\rm min}\) and NDVI illustrated a positive relationship in 86.7% of the TP, and 21% of this was significant (\(p<0.05\)) (Figure 6a), which was mostly concentrated in the central and southwest boundaries, whilst only 13.3% of the regions were negatively subject to T\({}_{\rm min}\). With regards to the T\({}_{\rm max}\) during the growing season (as displayed in Figure 6b), it is worth noting that over 61.8% of the regions exhibited significant positive correlations, and the strongest correlations were found to be concentrated in the eastern regions under conditions without water stress. In comparison, the western region illustrated a significant negative correlation (12.60%), which is basically in line with [PERSON] et al. (2017) The spatial partial correlation between GPP and air temperature exhibited a similar pattern to that of NDVI. Specifically, 65.24% of the TP for T\({}_{\rm min}\) displayed a positive association with GPP, and 7.38% of the correlation was found to be significant (\(p<0.05\)). As for T\({}_{\rm max}\) and GPP, most of the western regions showed a negative correlation (51.59%), while 48.41% displayed a positive correlation, and 4.3% was significant (\(p<0.05\)). The correlation between T\({}_{\rm min}\) and vegetation growth was generally stronger than that between T\({}_{\rm max}\) and vegetation. Overall, T\({}_{\rm min}\) had a relatively stronger explanatory significance to the variations of both NDVI and GPP. These results are in accord with recent studies, which have indicated that the vegetation index has exhibited a strong positive partial correlation with T\({}_{\rm min}\) during the summer season ([PERSON] et al., 2017). In contrast, the relationship between T\({}_{\rm max}\) and vegetation growth was spatially heterogeneous. A positive correlation was found across the eastern region, while T\({}_{\rm max}\) had a negative impact on plant growth in high-altitude arid regions of the western TP. This negative correlation between T\({}_{\rm max}\) and plant growth may be related to the increased water stress that is caused by warming-induced soil moisture depletion ([PERSON] et al., 2017). Figure 5: The mean annual time series of (**a**) T\({}_{\rm min}\), (**b**) T\({}_{\rm max}\) and (**c**) their differences (T\({}_{\rm D}\)) in different frozen regions from 1982 to 2017 in the growing season; ***\(p<0.01\). Additionally, we investigated the interannual correlations among T\({}_{\text{max}}\), T\({}_{\text{min}}\), and NDVI across three frozen soil grounds (Figure 7). Our findings indicated that the correlation between T\({}_{\text{min}}\) and vegetation growth was strongest in the permafrost ground (R = 0.7, \(p\) < 0.01) (Figure 7c). The correlation was lowest in the unfrozen region (R = 0.58, \(p\) < 0.01) (Figure 7a). In the seasonally frozen soil region, we observed a significant correlation between T\({}_{\text{max}}\) and vegetation growth (\(p\) = 0.67, R < 0.01). This was followed by the permafrost region (\(p\) = 0.62, R < 0.01), as illustrated in Figure 7f. By contrast, in the unfrozen regions, the correlations between T\({}_{\text{max}}\), T\({}_{\text{min}}\), and NDVI were all the lowest.