## 4 Discussion  
### Responses of SIF and VIs to Drought  
From the change characteristics of SPEI, SM\({}_{\text{surr}}\), and SM\({}_{\text{root}}\) in Figures 7 and 8, the drought still existed in the MLRYR in November and December 2019. Although the drought in December 2019 was alleviated compared with that in November 2019, the standardized anomalies of SPEI and soil moisture were still negative and Tem, LST, and PAR were positive. Correspondingly, the standardized anomalies of NDVI, EVI, and NIRv still changed considerably during November and even December of 2019, while those of SIF did not change significantly (Figure 10). As SIF is a direct probe of photosynthesis, it can capture the physiological state information of vegetation directly. During November-December 2019 and the same period throughout the year in the MLRYR, the vegetation generally entered the senescence stage and its photosynthetic capacity declined. Despite being affected by drought during this period, vegetation senescence information played a dominant role in  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**VIs** & **July** & **August** & **September** & **October** & **November** & **December** \\ \hline SIF & 0.138 & **0.341** & **0.525** & 0.430 & 0.368 & 0.367 \\ NDVI & **0.157** & 0.271 & 0.345 & **0.451** & 0.355 & 0.281 \\ EVI & 0.143 & 0.159 & 0.187 & 0.413 & 0.232 & 0.278 \\ NIRv & 0.142 & 0.205 & 0.191 & 0.413 & 0.220 & 0.282 \\ \hline \hline \end{tabular} Note: The bold font represents the most correlation factor.  
\end{table}
Table 2: Spatial consistency between standardized anomalies of MODIS GPP and that of SIF, NDVI, EVI, and NIRv during July–December in 2019.  
Figure 13: Scatter fitting between MODIS GPP and GOSIF (**a**), NDVI (**b**), EVI (**c**), and NIRv (**d**) during July–December 2019. Note: Each dot denotes the monthly value for each pixel (0.05\({}^{\circ}\)\(\times\) 0.05\({}^{\circ}\)); \(N\) indicates the data size.  
the SIF signal changes, which resulted in the little anomaly change of regional SIF; however, VIs (e.g., NDVI, EVI, and NIRv) are vegetation greenness indices [38], which are not as closely related to the physiological state of vegetation as SIF and cannot capture the changes of vegetation senescence stage sufficiently; therefore, VIs had an obvious delayed response in monitoring the physiological state of vegetation compared with SIF. This phenomenon is consistent with previous studies [6; 7; 8; 33; 39; 40]. Moreover, the vegetation was sparse and the leaf area index (LAI) was low during this time period; the VIs were significantly affected by soil background [41], which determined the dominant role of drought in NDVI, EVI, and NIRv changes ultimately. The above explanation could also be responsible for the apparent negative standardized anomalies of NDVI, EVI, and NIRv in central MLRYR. The results were echoed by [PERSON] et al. [15], who pointed out that the decrease in SIF was more significant than that of NDVI during the peak growth period in the Great Plains, while the reduction in NDVI continued and that of SIF eased during the senescence stage. [PERSON] et al. [42] also indicated that SIF is better than NDVI in determining the end date of the vegetation growing season. Moreover, as shown in Figure 14, the relative higher coefficients in September 2019 and the lower coefficients in December 2019 between the standardized anomalies of SIF and those of drought indices can also give a reasonable and quantitative explanation for the responses of SIF and VIs to drought in this study. In general, when vegetation enters the senescence stage gradually in autumn and winter, the VIs better reflect meteorological drought conditions if the drought continues.