## 5 Conclusions  
The much smaller footprint of OCO-2 provides the first opportunity to directly measure the ecosystem-scale photosynthesis at the ecosystem level, while its sparse global coverage imposes a strong limitation on the use of the OCO-2 SIF. We generated continuous gridded global SIF data with higher spatial and temporal resolutions (i.e., 0.05\({}^{\circ}\) and 8-day) based on a data-driven approach. The developed predictive SIF model allows us to estimate SIF for each 0.05\({}^{\circ}\)\(\times\) 0.05\({}^{\circ}\) grid cell across the globe for each 8-day interval based on MODIS and meteorological data, and extends the current short data record of OCO-2 SIF (since September 2014) to a much longer period (since March 2000). Our results showed that increasing training sample size could reduce the errors of predicted SIF, while the land cover type only played a small role in improving the SIF prediction. Our selected model, developed by four variables (i.e., EVI, PAR, VPD, and air temperature), performed fairly well in estimating SIF (R\({}^{2}\) = 0.79, RMSE = 0.07 W m\({}^{-2}\)\(\upmu\)m\({}^{-1}\) sr\({}^{-1}\)). Our new 0.05\({}^{\circ}\) SIF maps exhibited expected spatial and temporal variations, and agreed well with the coarse-resolution OCO-2 SIF in both annual mean and maximum magnitude. At four selected EC flux sites, the 0.05\({}^{\circ}\) SIF captured similar trajectories as compared to the original OCO-2 soundings, and were also spatially and temporally continuous. It also showed similar seasonality with the tower GPP. We further examined the relationship between the new 0.05\({}^{\circ}\) SIF and GPP from 91 EC flux sites, and found high correlations between SIF and GPP across biomes, indicating the potential of SIF in monitoring the photosynthesis. During the past 17 years, the annual global mean SIF has had a significant positive trend (0.0004 W m\({}^{-2}\)\(\upmu\)m\({}^{-1}\) sr\({}^{-1}\) per year, \(p<0.001\)). Our finer-resolution SIF data product GOSIF, freely available at [[http://globalecology.unh.edu](http://globalecology.unh.edu)]([http://globalecology.unh.edu](http://globalecology.unh.edu)), will benefit various applications in many areas, such as carbon cycle, remote sensing, climate change, ecosystem studies, and agriculture. For example, it may serve as a useful data set to monitor terrestrial photosynthesis and to assess plant water stress and phenology, and it can also be used for benchmarking terrestrial biosphere and Earth system models (e.g., CLM, ELM) which currently exhibit substantial uncertainty. The synergetic use of our 0.05\({}^{\circ}\) SIF product, along with new or forthcoming SIF data such as the TROPOspheric Monitoring Instrument (TROPOMI, 0.1\({}^{\circ}\)) and the FLEX (300 m), has great potential for studying terrestrial carbon cycle dynamics. The following are available online at [[http://www.mdpi.com/2072-4292/11/5/517/s1](http://www.mdpi.com/2072-4292/11/5/517/s1)]([http://www.mdpi.com/2072-4292/11/5/517/s1](http://www.mdpi.com/2072-4292/11/5/517/s1)), Figure S1: The spatial distribution and land cover types of the 91 eddy covariance (EC) flux tower sites from the FLUXNET 2015 Tier 1 dataset used in this study, Figure S2: Relationship between solar-induced chlorophyll fluorescence (SIF) from our global Orbiting Carbon Observatory-2 SIF (GOSIF) product and gross primary productivity (GPP) from the FLUXNET 2015 Tier 1 dataset across biomes, Table S1: The statistical measures for model development and validation, Table S2: FLUXNET Tier-1 sites used for evaluating GOSIF in this study. [PERSON] and [PERSON] designed the research. [PERSON] processed the data. [PERSON] and [PERSON] analyzed the data and wrote the paper. This study was supported by the National Aeronautics and Space Administration (NASA) (Climate Indicators and Data Products for Future National Climate Assessments: Grant No. NNX16 AG61G; Carbon Cycle Science Program: Grant No. NNX14 AJ18G), the National Science Foundation (MacroSystems Biology Program: Grant No.