## 4 Results
### Monitoring and Assessing the 2009 Drought in Victoria
In March, APAR\({}_{\text{NDVI}}\) and APAR\({}_{\text{EVI}}\) showed more severe drought losses (<\(-\)1\(\sigma\)) than did SIF and GPP. General Analyses of the Responses of FLUXCOM GPP, SIF, APAR\({}_{\text{NDVI}}\) and APAR\({}_{\text{EVI}}\) to Drought  
In this section, we explored the sensitivities of GPP and vegetation proxies to drought-related meteorology anomalies using the ARx model. Since the sensitivity of vegetation productivity to high temperature is variable in different seasons [50], we first analyzed the relationships between GPP and temperature based on data from 1982 to 2013 to obtain the annual-temperature-sensitive period. Figure 6 shows distinct seasonal features between the temperature and GPP for the general region of Victoria (Figure 6a), crop land (Figure 6b) and evergreen broadleaf forest land (Figure 6c). It is shown that the distribution of data points in GPP-temperature space is similar to a triangle, and GPP showed contrasting responses to temperature in different seasons. For the general area of Victoria, GPP decreases with increasing temperature in late spring (i.e., October and November) and summer. The vegetation productivity is slightly enhanced in autumn and barely changes in winter by increased temperature. The period with the highest GPP-temperature sensitivity is from October to February. The feature of crop land is similar to the result generated for the general region of Victoria. For evergreen broadleaf forest land, the annual-temperature-sensitive period when GPP decreased by increased temperature is from November to February. Based on the annual-temperature-sensitive period, we explored the impacts of temperature, water availability and PAR on vegetation activity indicated by GPP and vegetation proxies using the ARx model regarding memory effects. The sensitivities of these vegetation variables (e.g., GPP, SIF, APAR\({}_{\text{NDVI}}\) and APAR\({}_{\text{EVI}}\)) anomalies to temperature, water availability, PAR and the one-month-lagged vegetation activity are respectively represented by aT, aW, aP and aM, respectively. The ARx model output results for general Victoria region, crop land and evergreen broadleaf forest land are shown in Table 1. The aforementioned variables anomalies have been standardized using z-score standardization to assure comparability between the coefficients in the ARx model. Both GPP and SIF exhibit high levels of confidence, and the low root mean square error (RMSE) for general Victoria region. SIF gains the highest model precision (R\({}^{2}\) = 0.72) compared with APAR\({}_{\text{NDVI}}\) (R\({}^{2}\) = 0.29) and APAR\({}_{\text{EVI}}\) (R\({}^{2}\) = 0.20). It is interpreted that both GPP and SIF anomalies can be explained by meteorology anomalies and memory effects. aT estimated by SIF is more significant than those estimated by APAR\({}_{\text{NDVI}}\) and APAR\({}_{\text{EVI}}\). aP exhibits negative effects on vegetation activity. aW estimated by all the vegetation variables are similar in the ARx model. aM indicated by GPP, SIF and APAR\({}_{\text{NDVI}}\) are significant. It is interpreted that memory effects also have important impacts on vegetation  
Figure 6: Relationships between GPP and temperature according to different seasons based on data from 1982 to 2013 in Victoria. Results for the general Victoria region, crop land and evergreen broadleaf forest land are shown in (**a**), (**b**) and (**c**), respectively. The data point denotes the monthly zonal average of FLUXCOM GPP and temperature from meteorology stations for each studied region. productivity compared with other meteorology factors. The sensitivities of theses vegetation variables anomalies to water availability anomalies are stronger than those to temperature and PAR anomalies. Therefore, water availability is regarded as an important meteorology-forcing factor for plant activity during October-February in the studied area. These results agree well with the previous study that investigated water limitation and vegetation memory effects in Victoria [48].