This dataset provides high-resolution, spatially-contiguous, global solar-induced chlorophyll fluorescence (SIF) estimates at 0.05 degree (approx. 5 km at the equator) spatial and 16-day temporal resolution beginning in September 2014 and continuing to the present. This product, SIFoco2_005, was derived from Orbiting Carbon Observatory-2 (OCO-2) SIF observations was produced by training an artificial neural network (ANN) on the native OCO-2 SIF observations and MODIS BRDF-corrected seven-band surface reflectance along OCO-2's orbits. The trained ANN model was then applied to predict mean daily SIF (mW/m2/nm/sr) in OCO-2's gap regions based on MODIS reflectance and landcover. This framework was stratified by biomes and 16-day time steps. The high resolution and global contiguous coverage of this dataset will greatly enhance the synergy between satellite SIF and photosynthesis measured on the ground at consistent spatial scales. Potential applications of this dataset include advancing dynamic drought monitoring and mitigation, informing agricultural planning and yield estimation, and providing a benchmark for upcoming satellite missions with SIF capabilities at higher spatial resolutions.