## 1 Introduction
The observational evidence based on satellite data and model simulations showed that SST variations mostly interact with photosynthesis through teleconnections and the associated co-variability patterns between multiple climate variables [29]. Therefore, SST indices have predictive skills on the variability of terrestrial photosynthesis due to the time lag between each link in this cause-effect chain, compared to the meteorological parameters (e.g., rainfall and air temperature) [30]. It is reported that using SSTs, vegetation greenness of the arid and semi-arid climatic zones across the tropical belt can be forecasted 3-6 months in advance [26]. The ocean-vegetation link demonstrates the possible impact of SST on the functional status of terrestrial ecosystems. Thus, the current study intends to investigate how the tropical Indian Ocean contributes to anomalies in vegetation photosynthesis over the Indian subcontinent using SIF and SST indices. As an agrarian country with rich natural vegetation, India is surrounded by the Indian Ocean on three sides and experiences a monsoon climate [31; 32; 33; 34]. It offers an ideal site to study the oceanic influence on vegetation anomalies. Since hydroclimatic fluctuations predominantly control plant growth and productivity [35; 36], the majority of previous investigations focused on the effects of rainfall and temperature on various structural and functional characteristics of Indian vegetation [37; 38; 39]. Few studies used remote SST forcing to show the impact of ENSO on the inter-annual variability of vegetation productivity in India and attempted to illustrate the effect of climate variability on ecosystem services [40; 41; 42]. [PERSON] and [PERSON] (2015) showed the potential of predicting NDVI anomalies across India using soil moisture and the ENSO index [35]. Moreover, along with the ENSO teleconnections, the variability of SST in the tropical Indian Ocean also contributes to the vegetation anomalies in India [9]. At the same time, there exists a paucity of active research on the role of SST variations in the tropical Indian Ocean in bringing changes in the functioning of the Indian terrestrial vegetation ecosystem. Besides, this study aims to evaluate the varying responses of vegetation photosynthetic activity in India to SST anomalies using SIF measurements based on advanced remote sensing techniques. The application of satellite-based SIF data products offers a unique opportunity to comprehend how exactly terrestrial vegetation photosynthesis is linked to Indian Ocean SSTs, which is not addressed in the previous studies. Indian Ocean SST variability also plays a critical role in the climate conditions over the Indian subcontinent, significantly influencing vegetation anomalies. Thus, our study provides a simple framework that can identify the anomalies in Indian vegetation photosynthetic activity that arise from the rapidly varying climate conditions in the Indian Ocean, and clearly, this is of huge agricultural and economic interest. The present work focuses on the relationship between SST variations in the tropical Indian Ocean regions and SIF anomalies across the Indian mainland to understand the possible impacts of regional-scale SST anomalies on the photosynthetic activity of the nearby terrestrial ecosystem. The summer monsoon period (June-September) is critical to the vegetation over the Indian landmass as it plays a significant role in determining water availability [43]. Therefore, our analysis aims to explore the SST-SIF linkage exclusively for June, July, August and September. To account for the spatial variability of SST over the monsoon domain [44], the tropical Indian Ocean is divided into the Western Indian Ocean (WIO), Northern Indian Ocean (NIO) and Central Indian Ocean (CIO) following the spatial pattern of average seasonal SST during the summer monsoon (Figure 1).