## Data and Methods  
### Datasets  
Consistent global SIF observations have been acquired since 2007 from the GOME-2 sensor, onboard the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) Meteorological Operational Satellites. The GOME-2 sensor includes four spectral channels ranging from 240-790 nm, while channel four covers the SIF sensitive spectral region from 590-790 nm [25; 34] with an over-pass time of 9:30 a.m., near the peak of daily photosynthetic activity [35]. We used an existing GOME-2 SIF (version 2.6 MetOp-A) global record composited to a monthly time step and mapped to a 0.5 degree resolution global grid and WGS 1984 coordinate system [28; 34]. The 2007-2015 SIF record was used to create a monthly SIF (Mw m\({}^{-2}\) sr\({}^{-1}\) nm\({}^{-1}\)) climatology by averaging nine values for each month (Mw m\({}^{-2}\) sr\({}^{-1}\) nm\({}^{-1}\)) for each 0.5-degree grid cell over the global domain. All the negative SIF values mostly over the water bodies were treated as no data value. The global domain for this study encompassed all land areas except for regions with sparsely vegetated cover defined by a MODIS IGBP land cover classification [36]. The resulting monthly SIF observations were compared with collocated GPP observations obtained from local scale (-1 km\({}^{2}\) footprint) tower carbon flux measurements representing a range of global biomes. Satellite based Photosynthetically Active Radiation (PAR) observations from the Cloud and Earth Radiant Energy System (CERES, Ed3A) database [37] were used to account for the influence of solar radiation on the 2007-2015 GOME-2 SIF record; the CERES database is derived from MODIS observations from the Terra and Aqua satellites and has 1-degree spatial resolution and monthly averaged temporal coverage. The CERES PAR data were resampled to the same 0.5 resolution and projection format as the SIF record using nearest-neighbor resampling, and then temporally averaged to produce a monthly climatology. We then divided the SIF monthly climatology for each grid cell by the corresponding monthly mean PAR observations from CERES (Wm\({}^{-2}\)). The resulting PAR-adjusted SIF metric (SIF\({}_{\text{P}}\)) was used to distinguish temperature and moisture related controls on productivity apart from solar radiation. The SIF\({}_{\text{P}}\) observations were compared with mean monthly climate variables obtained from global reanalysis data for selected tower site locations and over the larger global domain. The monthly SIF\({}_{\text{P}}\) grid cells were also spatially averaged and compared with similarly averaged monthly climate variables for selected global sub-regions (Figure 1). We used in situ GPP records from 67 global carbon flux tower sites to evaluate relationships between the stand level tower GPP observations and coarser productivity and climate controls defined from the satellite SIF observations and global reanalysis data. The tower site records were selected from the 2015 FLUXNET synthesis [38] on the basis of representing major global biomes (Figure 1), and having multi-year daily GPP records occurring after year 2007 to overlap with the GOME-2 SIF record; the resulting tower sites selected for this investigation are summarized in Table S1. Gap-filled daily tower data derived using seven different nighttime carbon flux partitioning methods [39] were averaged to create a GPP mean monthly climatology for each tower site. We used a global daily surface meteorology record for the 2007-2015 period obtained from the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA2) global reanalysis [40]. The MERRA2 meteorological parameters processed for this study included daily minimum and mean air temperatures, dew point temperature, and root zone (integrated 0-1 m depth) SM. The MERRA2 data were resampled from a native 0.5 \(\times\) 0.65-degree global grid into a 0.5-degree resolution geographic projection consistent with the GOME-2 SIF record.