## 4 Discussion
Several recent studies reported that OCO-2 SIF had strong correlation coefficients with tower GPP in crop, grassland, and temperate forest areas [31; 34; 35], our results were consistent with these conclusions. We performed an intercomparison using OCO-2 SIF to verify the GOME-2 SIF results and found that the spatial differences in the footprints among GOME-2, OCO-2 and the flux towers represented one of the main reasons for the large discrepancies in the GPP estimates. We found that the robustness of the correlation coefficients between GOME-2 SIF and OCO-2 SIF were highly dependent on their spatial footprint overlaps, which might be one of the reasons why GOME-2 SIF exhibited universal correlation with the tower GPP. GOME-2 SIF showed stronger correlation coefficients with OCO-2 SIF based on samples with more than 70 soundings than with OCO-2 SIF based on all soundings (Figure 7, Figures S4 and S5), because SIF retrieval with less than 70 soundings within the spatial footprint overlaps could increase the effects of potential noise in the retrievals. The OCO-2 scale effect could demonstrate this phenomenon to some extent (Figure S1, Table S1), and when averaging in different bins, additional soundings were sorted into larger bins, which could reduce the effects of retrieval noise. Thus, OCO-2 SIF manifested a stronger correlation with the tower GPP. For GOME-2 SIF, the scale effect was weaker than the results of OCO-2 SIF (Figure S2, Table S1). We examined the daily GOME-2 observations and found them to be noisy; thus, we averaged them over time to reduce noise in a similar way as OCO-2 data were averaged in space. Our results demonstrated that OCO-2 SIF obtained by the sensor observing the surface in the nadir mode performed better than that obtained by the sensor in the direct sunlight reflected in the glint mode, because in the nadir mode, the satellite points the instrument to the local nadir with zero VZAs. In the glint mode, noticeable angular variations of SIF exist due to the varying VZA over time, and major directional effects on SIF added variations of the GPP-SIF relationship and OCO-2 SIF values [67; 29; 68]. Our results also showed that the OCO-2 SIF and GOME-2 SIF were correlated with APAR as well as with two environmental scaling factors (T\({}_{\text{scalar}}\)\(\times\) W\({}_{\text{scalar}}\)). These findings were consistent with previous studies [22; 31]. Different variables, such as EVI, PAR, air temperature, and LSWI, as well as a set of biome-specific parameters (e.g., maximum LUE, maximum, minimum, and optimum temperature) are included in the VPM model; SIF-based models such as linear models use a simple computational process for GPP estimations. However, it is unclear whether SIF-based models have lower uncertainties than VPM model in GPP estimation; this is a direction for future research. Besides, clouds could be a factor that influenced the SIF signals (Figure S3). However, both OCO-2 SIF and GOME-2 SIF have certain limitations in GPP estimations. OCO-2 SIF has sparse coverage and low temporal resolution, and GOME-2 SIF has coarse spatial resolution [46; 69], which severely hinders the investigations of the GPP-SIF relationship. Machine learning methods such as a feedforward neural networks architecture will provide an effective way to reproduce improved data [38], we expect a series of original issues such as sparse coverage and coarse spatial resolution will be improved to some extent. Importantly, we focus on space-borne SIF data with high spatiotemporal resolution. The tropospheric monitoring instrument (TROPOMI), on the Sentinel-5 Precursor platform, was launched on 16 August 2017, has a footprint size of 7 km \(\times\) 7 km at nadir [70; 71]. TanSat (CarbonSat) was launched on 21 December 2016 [72], which has a footprint size of approximately 2 km \(\times\) 2 km and a swath of 20 km wide at nadir with a revisit period of 16 days. These space-borne datasets will be available to the public, when it can be further used for GPP estimation and the carbon cycle research.