## Data and Methodology  
### Observational Data  
Global Ozone Monitoring Experiment-2 (GOME-2) terrestrial chlorophyll fluorescence data product is the primary dataset being used in this study. GOME-2 provides retrievals of SIF peaking at 740 nm, which are based on the measurements from a broader spectral range of 734-758 nm [45; 46]. GOME-2 SIF data have been successfully used to obtain the plant functional states related to GPP [47; 48; 22; 46; 49]. The GOME-2 v25 level 3 dataset we used in this study covers the time period from 2007 to 2012 and has a spatial resolution of \(0.5\times 0.5^{\circ}\). Tropical Rainfall Measuring Mission (TRMM) 3B42 rainfall data were further used to quantify the relationship between SIF, precipitation, soil moisture, and GPP. TRMM 3B42 and 3B43 gridded estimates are on a spatial resolution of \(0.25\times 0.25^{\circ}\) in the belt extending from \(50^{\circ}\)N to \(50^{\circ}\)S. We also used TRMM 3B43 monthly precipitation based on 3-hourly rainfall estimates summed for the calendar month with rain gauge data applied for large-scale bias adjustment. The TRMM 3B43 product was used to produce SIF predictions based on dependence between SIF and precipitation. In order to provide information on soil moisture impact on SIF and GPP, we have used the European Space Agency Climate Change Initiative Soil Moisture (ESA CCI SM) combined daily dataset (1978-2014) at 0.25 \(\times\) 0.25\({}^{\circ}\) spatial resolution. This dataset represents the most comprehensive global time series of satellite-based soil moisture applicable at up to the top 5 cm of the soil. The CCI Soil Moisture product combines passive Level 2 radiometer-based products from Scanning Multichannel Microwave Radiometer (SMMR), Special Sensor Microwave Imager (SSM/I), Tropical Rainfall Measuring Mission's Microwave Imager (TMI), and Advanced Microwave Scanning Radiometer (AMSR-E) with active scatterometer-based products from European Remote Sensing satellite (ERS-1/2) and Advanced Scatterometer (ASCAT). As shown in several studies [50; 51; 52; 53; 54], ESA CCI SM data have been successfully used for a variety of applications, e.g., studying land-atmosphere coupling dynamics. We linked GPP from FLUXNET measurements at five crop (US-Ne3, US-ARM, US-Twt, US-Tw2, US-Tw3) and five grass stations (US-KFS, US-AR1, US-AR2, US-Cop, US-Wkg) (Table 1) to SIF, precipitation and soil moisture. FLUXNET data have been extensively used in various studies investigating processes related to the exchange of CO\({}_{2}\) between the land surface and atmosphere [55; 56; 57; 58; 59]. It was previously demonstrated that ecosystem-level GPP can be accurately estimated from measurements of CO\({}_{2}\) fluxes at eddy covariance towers [60]. FLUXNET GPP values, which are calculated as difference between total ecosystem respiration and net ecosystem exchange, are obtained at a half-hourly step and expressed in umol/m\({}^{2}\)/s; therefore, we have converted GPP measurements to gC/m\({}^{2}\)/day and gC/m\({}^{2}\)/month, the units used throughout this study. GPP data are also available from Moderate Resolution Imaging Spectroradiometer (MODIS), a key instrument onboard the Terra (originally EOS AM-1) satellite that started providing global GPP products in 2000 [61]. We used monthly MOD17A2 data product available at \(1\times 1\) km spatial resolution as an observational reference to evaluate the performance of SIF-, precipitation- and soil moisture-based GPP estimates. Based on the light use efficiency (LUE) concept [62], MODIS GPP is expressed as  
\[GPP=PAR\cdot FAP\cdot LUE \tag{1}\]  
\[LUE=LUE_{max}\cdot f(VPD)\cdot g(T_{min}) \tag{2}\]  
\[FPAR=1-e^{-k\cdot LAI} \tag{3}\]  
where \(PAR\) is photosynthetically active radiation, \(FPAR\) is fractional absorption of \(PAR\), \(LUE\) is the efficiency with which absorbed radiation is converted to fixed carbon, \(f(VPD)\) is the scalar of daily vapor pressure deficit \((VPD)\), \(g(T_{min})\) is the scalar of daily minimum air temperature \((T_{min})\), and \(k\) is the extinction coefficient.