## 5 Conclusions  
In this paper, we examined the effect of the spatial resolution of daily two-band enhanced vegetation index (EVI2, 10m from Sentinel-2 MSI, 250m and 500m from MODIS) on the accuracy of gross primary productivity (GPP) estimations with different regression models at eight Nordic eddy covariance flux sites. The results gave high and consistent coefficients of explanation (R\({}^{2}\) = 0.84 for Sentinel-2; R\({}^{2}\) = 0.83 for MODIS) verifying the potential of remotely sensed data to provide accurate estimates of the seasonal carbon uptake dynamics across northern boreal landscapes at both the coarse and fine spatial scale. Sentinel-2 opens the possibility of very detailed GPP estimation across the northern landscape, which is of benefit for climate mitigation and adaptation work. The analysis showed that the quantitative differences in GPP estimation due to the different input data were small between Sentinel-2 MSI GPP and MODIS GPP; smaller than the effect of different model formulations. This can be explained by the combined effects of the higher temporal frequency of MODIS compensating for its lower spatial resolution, the time-series fitting method used for reconstructing daily EVI2, the homogeneity of the surrounding areas of the EC measurements, and the use of linear regression models. To further strengthen the development of GPP models based on Sentinel-2 data will require more analyses of different model formulations (including environmental drivers), more tests of remotely sensed indices and biophysical parameters, and analyses across a wider range of geographical locations and time.  
Conceptualization, Z.C., S.J. and L.E.; methodology, Z.C. and S.J.; software, Z.C. and S.J.; validation, J.H.; formal analysis, Z.C., S.J. and M.K.; investigation, Z.C., A.I., M.P. and M.M.; resources, L.E.; data curation, Z.C., J.H., A.I., M.P. and M.M.; writing--original draft preparation, Z.C. and S.J.; writing--review and editing. J.H., M.K., J.A., H.J., A.I., M.P., J.R., M.M., P.J. and L.E.; supervision, L.E., P.J., J.A. and H.J.; funding acquisition, L.E. and P.J. All authors have read and agreed to the published version of the manuscript.  
This research was funded by a grant from the Swedish National Space Agency to LE and PJ, Dnr. 119/13.  
PJ and LE acknowledge financial support from Gyllenstiernska Krapperupsstielsen. We acknowledge ICOS Sweden (cofinanced by the Swedish Research Council under the grant No. 2015-06020), ICOS Finland Hyytiala station, and ICOS Denmark Sore station for providing GPP and environmental data. This study was supported by an infrastructure grant to [PERSON] from the Faculty of Science, Lund University. The MOD09Q1 and MOD09A1 data products were retrieved from the online Data Pool, courtesy of the NASA EOSDIS Land Processes Distributed Active Archive Center (LP DAAC), USGS/ Earth Resources Observation and Science (EROS) Center, Sioux Falls, South Dakota, [[https://lpdaac.usgs.gov/tools/data-pool/](https://lpdaac.usgs.gov/tools/data-pool/)]([https://lpdaac.usgs.gov/tools/data-pool/](https://lpdaac.usgs.gov/tools/data-pool/)).  
The authors declare no conflict of interest.  
Figure 11: Sentinel-2 MSI, MODIS\({}_{250\text{m}}\), and MODIS\({}_{500\text{m}}\) daily EVI2 time-series generated by the box constrained separable least squares fitting to double logistic model functions.