Therefore, accurately monitoring changes in vegetation GPP under drought conditions remains a challenge. Solar-induced fluorescence (SIF) is a new indicator for monitoring vegetation growth and environmental changes [23]. Unlike traditional reflectance-based VIs, SIF is the optical signal emitted by chlorophyll-a after absorbing sunlight, lasting for a few nanoseconds [24]. Light absorbed by vegetation has three pathways of consumption: SIF, photochemical reactions, and thermal dissipation [25]. The direct connection between SIF and photosynthesis has been validated at different spatial scales. SIF products from various sensors (GOME-2, GOSAT, and OCO-2) have shown strong correlations with GPP [26; 27]. Some researchers have found that GOSAT SIF and GPP were strongly correlated [26; 28]. Other studies utilizing SIF have discovered a consistently significant relationship of GPP with SIF in terrestrial ecosystems across different temporal scales [29; 30]. SIF has also demonstrated good performance in estimating GPP under drought conditions. [PERSON] et al. (2019) investigated the potential of SIF in monitoring summer maize GPP under drought conditions and found that SIF was able to track spatiotemporal variations in GPP due to drought more effectively than NDVI [31]. [PERSON] et al. (2022) explored the capability of SIF in estimating the impact of drought on winter wheat GPP, demonstrating that SIF can accurately quantify GPP losses caused by drought [32]. However, research on the potential of SIF monitoring for grassland ecosystem GPP changes induced by drought is still relatively scarce. Numerous studies have demonstrated a strong correlation of SIF retrieved from various satellites with EC flux towers or GPP satellite products [33; 34]. However, uncertainties in SIF and GPP may blur the relationship of SIF with GPP. Variations in SIF caused by different sensors, retrieval algorithms, and other factors can change the SIF-GPP relationship [35]. Existing SIF products suffer from low spatial resolutions and limited coverage, which hinder the true SIF-GPP relationship [36]. In fact, due to the large footprint and spatial discontinuity of measurements from most satellite platforms, the spatial resolution of current satellite SIF datasets is relatively coarse, typically ranging from 0.5\({}^{\circ}\) to 2\({}^{\circ}\)[37]. Although the spatial resolution has improved, the data have only become available since 2017, limiting the analysis of drought impacts on grassland ecosystem productivity [38]. Few SIF products are applicable for drought monitoring and productivity assessment in grasslands. In recent years, several spatial downscaling SIF products have emerged, offering more fine-grained SIF data with longer time series, providing new data for accurately estimating GPP. There is currently no research available on spatial downscaling SIF products to monitor the impact of drought on grassland GPP. Therefore, this study considers the drought in the Xilingol grassland in 2009 as an example and explores the potential of downscaled satellite GOME-2 SIF (0.05\({}^{\circ}\)) to investigate the spatiotemporal variations in SIF in monitoring GPP due to drought. Specifically, our objectives are as follows: (1) to analyze the response mechanisms of SIF to drought stress; (2) to investigate the potential of SIF in estimating GPP; (3) to investigate the ability of SIF to estimate GPP changes under drought conditions.