## 3 Results  
### SIF and SST Variations during the Summer Monsoon  
The 18-year climatology of SIF demonstrated spatial variability up to 0.55 W m\({}^{-2}\) um\({}^{-1}\) sr\({}^{-1}\) in the summer monsoon over India (Figure 1 and Table 3). The EHR dominated by thick forests emerged as the most productive ACZ with a mean SIF of 0.35 W m\({}^{-2}\) um\({}^{-1}\) sr\({}^{-1}\), while WDR characterised by sparse vegetation and arid climate turned the least productive area having the weakest SIF signals (0.05 W m\({}^{-2}\) um\({}^{-1}\) sr\({}^{-1}\)). SIF depicted maximum photosynthesis during August (0.26 W m\({}^{-2}\) um\({}^{-1}\) sr\({}^{-1}\)) and minimum during June (0.13 W m\({}^{-2}\) um\({}^{-1}\) sr\({}^{-1}\)) (Figure 3). During the monsoon's initial stages, the maximum SIF values are for forest areas with a mean value of 0.20 W m\({}^{-2}\) um\({}^{-1}\) sr\({}^{-1}\), while they are comparatively low over croplands (0.09 W m\({}^{-2}\) um\({}^{-1}\) sr\({}^{-1}\)). The contribution of the croplands to the total productivity of the vegetation in India increases rapidly (0.23 W m\({}^{-2}\) um\({}^{-1}\) sr\({}^{-1}\)) once the monsoon attains its peak in August. The magnitude of SIF over forest ecosystems across the country showed marginal variation in the second half of the monsoon (\(\sim\)0.3 W m\({}^{-2}\) um\({}^{-1}\) sr\({}^{-1}\)), and the SIF variability during August and September over the country is nearly the same (\(\sim\)0.25 W m\({}^{-2}\) um\({}^{-1}\) sr\({}^{-1}\)). The tropical Indian Ocean SST exhibits a unique regional distribution during the summer monsoon. The SSTs of the Western, Northern and Central Indian Ocean (WIO, NIO and CIO) have ranges of 26.78-30.22 \({}^{\circ}\)C, 23.33-29.53 \({}^{\circ}\)C and 21.91-28.26 \({}^{\circ}\)C, respectively, with NIO emerging as the warmest, followed by WIO and CIO (Figure 1). The de-trended time series of mean monthly SST anomalies during the monsoon period exhibited large \begin{table}
\begin{tabular}{c c c} \hline \hline  & CPH & Central plateau and hills \\ \hline TGP & Trans-Gangetic plains \\ \hline UGP & Upper Gangetic plains \\ \hline MGP & Middle Gangetic plains \\ \hline LGP & Lower Gangetic plains \\ \hline GPH & Gujarat plain and hills \\ \hline WDR & Western dry region \\ \hline WHR & Western Himalaya region \\ \hline EHR & Eastern Himalaya region \\ \hline \hline \end{tabular}
\end{table} 
Table 2: _Cont._ \begin{table}
\begin{tabular}{c c c c} \hline \hline
**ACZ** & **Minimum** & **Mean** & **Maximum** \\ \hline WCPG & 0.019 & 0.30 & 0.41 \\ ECPH & 0.011 & 0.20 & 0.47 \\ EPH & 0.013 & 0.25 & 0.45 \\ WPH & 0.013 & 0.18 & 0.38 \\ SPH & 0.016 & 0.17 & 0.41 \\ CPH & 0.01 & 0.17 & 0.34 \\ TGP & 0.01 & 0.18 & 0.34 \\ UGP & 0.049 & 0.22 & 0.37 \\ MGP & 0.014 & 0.22 & 0.43 \\ LGP & 0.022 & 0.24 & 0.41 \\ GPH & 0 & 0.13 & 0.35 \\ WDR & 0 & 0.05 & 0.19 \\ WHR & 0 & 0.08 & 0.39 \\ EHR & 0 & 0.35 & 0.54 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Minimum, mean and maximum SIF values in each of the agro-climatic zone during the summer monsoon. interannual variability in each of the oceanic regions (Figure 4). The maximum SST anomalies were observed in WIO, followed by NIO and CIO. The SST variations in WIO, NIO and CIO seem to be considerably interlinked until 2012. After 2012, the SST fluctuations in CIO are not in phase with the SST anomalies of WIO and NIO (Figure 4a). However, the SST anomalies of WIO and NIO are consistently linked (r = +0.80) all through the period of study (Figure 4a). The time series NINO3 index, DMI and W-CIO depicted the possible influence of climate events (ENSO and IOD) on the SST variations in individual Indian Ocean regions (Figure 4b). Overall, the W-CIO index (r = +0.74), SST variability in WIO (r = +0.59) and NIO (r = +0.58) exhibited robust correlation with DMI during the period of study. Meanwhile, SST anomalies in both WIO and NIO do not closely follow the pattern of DMI during 2006-2011.