## Materials and Methods
### Evaluation of SIF\({}_{757}\) Patterns  
To investigate the SIF\({}_{757}\) seasonal dynamics of different vegetation types, we explored the monthly means of SIF\({}_{757}\) for the period between September 2014 and November 2018 within the ERs (47 classes), biomes (6 classes), and KG-climate zones (14 classes). We calculated the monthly means for the biomes and KG-climate zones only if five or more SIF\({}_{757}\) retrievals were available per month in the forest areas. To characterize the ER-SIF\({}_{757}\) inter-annual temporal dynamics on the basis of the monthly means, we analyzed the distribution of the monthly means across the ERs on the basis of their medians and interquartile ranges (IQRs). The SIF\({}_{757}\) variability during the 2015-2016 El Nino drought event was analyzed for the Amazonian moist broadleaf forest biome (MBF) of the Af, Am, and Aw KG-climate zones for the period between September 2014 and December 2016 because the scPDSI and OCO-2 datasets overlapped only during this period. We define this period as the baseline period. For the drought estimation, we define the period from October 2015 to June 2016 as the climatological and rain anomaly (CARA) period [(7)]  
\[\text{SIF variations }(\%)_{\text{CARA period}}=\frac{\sum_{20}(\text{SIF}_{ \text{CARA}}-\text{SIF}_{\text{baseline without CARA}})*100}{\sum_{20}\text{SIF}_{ \text{baseline without CARA}}} \tag{2}\]  
We estimated the means of SIF\({}_{757}\) and fPAR, as well as the positive and negative SIF\({}_{757}\) variations during the CARA period, using 18 timesteps for 9 months at each KG-climate zone. Each time-step refers to the mean SIF\({}_{757}\) from the first 15 days or from the rest of the days in each month. The mean \begin{table}
\begin{tabular}{c c c c c c} \hline \hline  & \multicolumn{5}{c}{**Status**} \\ \hline
**Level** & & **Dry** & & **Non-Drought** \\ \hline scPDSI thresholds & \(\leq\)\(-\)4.0 & \(>\)\(-\)4.0, \(\leq\)\(-\)3.0 & \(>\)\(-\)3.0, \(\leq\)\(-\)2.0 & \(>\)\(-\)2.0, \(\leq\)\(-\)1.0 & \(>\)\(-\)1.0, \(<\)1.0 \\ \hline P and PET thresholds & & \(\text{P}-\text{PET}<0\) & & \(\text{P}-\text{PET}\geq 0\) \\ \hline Drought classification & Extreme & Severe & Moderate & Mild & Normal \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Drought index categories derived from the self-calibrating Palmer Drought Index (scPDSI) based on [PERSON] et al. (2016), [PERSON] et al. (2004), and [PERSON] et al. (2019). SIF\({}_{757}\) from each time-step of the CARA period was subtracted from the means of the other related yearly time-steps outside the CARA period in the baseline period. Finally, the percentage of SIF\({}_{757}\) variation was estimated for each time-step (Equation (2)). The analysis of the SIF variation during the CARA period (Equation (2)) focuses on forest stands within the MBF biome due to the sample sizes of the forest stands at the other biomes (Figure S2). For the combined analysis of SIF\({}_{757}\) and fPAR, we focused on the forest surfaces of all biomes within the Af, Am, and Aw KG-climate zones. In parallel, we analyzed the spatial and temporal distribution of three drought indicators at a monthly resolution at the basin scale, including scPDSI values below \(-2\), PET - P \(<0\), and the combination of both. In this study, the drought categories represent data only from pixels that include a combination of both. The yearly phenological variation of SIF\({}_{757}\) in the KG-climate zones between 1 October and 31 March was smaller than that during the other half of the year during 2014-2018. Thus, to avoid quantifying this variation in our ER scale drought analysis, we sampled the SIF\({}_{757}\) from that 6-month period during the 15 months of the baseline period. This period additionally includes the record-breaking heat of 2015-2016 [4]. Hence, we defined these 6 months within the baseline period as the El Nino 2015-2016 peak. In our final analysis, we particularly focused on the El Nino 2015-2016 peak drought conditions.