## 4 Discussion  
### Comparison of Different Vegetation Phenology Indices  
An improved ability to describe the timing of phenological transitions accurately is crucial for a better understanding of climate-ecosystem linkages under current circumstances, especially in pan-Arctic regions. Our current results highlighted the existence of relationships between remotely sensed and GPP based estimations of phenological metrics, but these were inconsistent among the different indices. Our results showed that NDVI experienced abrupt variations at the beginning and end of the snow seasons indicating that NDVI is more sensitive than EVI and PI to snow at low fractional snow cover (Figure 6). The results also revealed a large gap between NDVI and EVI during the non-growing season, which can be explained as EVI is more sensitive to fractional snow variation at high snow coverage [50]. EVI and NDVI had stationary phases in the middle of the growing season. Unlike the saturation effects in high-biomass areas, which could be attributed to the increased contrast of the reflectances of the NIR and red band caused by non-linear stretching [47], the stationary phases of NDVI and EVI in the mid-growing season were caused by unstable fluctuations. In general, the most commonly used VI, NDVI, did not provide an ideal measurement of GPP in pan-Arctic regions, especially in ENF regions. EVI also showed large uncertainties at the onset of spring since it was strongly affected by the snow filtering and hard to predict the snow gone stages precisely [53]. Compared with EVI, MCD12 always shortened the growing season (Figure 4). In GRA, WET and ENF sites, for both SOS and EOS, MCD12 and EVI had comparable R\({}^{2}\) but MCD12 had less the RMSE in different extents (Table A3). In the OSH site, both of them had comparably poor R\({}^{2}\) (<0.13) and RMSE (>11.95). The general pattern showed that MCD12 usually did a better job in terms of RMSE than our retrievals, indicating the additional levels of quality control and filtering result in a more consistent product, even if it is a not very accurate indicator of flux tower data. In our study at higher latitudes, PI only improved phenology extraction in some sites (FI-Hyy, FI-Kaa, FI-Sod, and US-Atq) compared with traditional VIs, particularly at the onset of spring. Although PI showed a smoother time series, it was not an ideal index for extracting SOS and EOS in pan-Arctic regions [4]. PPI-based phenology retrieval of transition dates showed improved performance compared with traditional VIs. First, PPI was more robust, and more valid data on phenological transition dates could be extracted from PPI compared with the other indices in this study over the same time period. Second, PPI had fewer occurrences of negative R values compared with the other indices, except in ENF sites. In ENF sites, almost all of the phenological transition dates extracted by satellite observations showed relatively low correlations with tower-based GPP. PPI was able to detect the timings of SOS and EOS more precisely when evaluated against ground-observed GPP data in OSH sites. We found a surprisingly strong relationship between MODIS-based PPI SOS and GPP-based SOS (R\({}^{2}\) = 0.68, RMSE = 7.73). Other studies in the northern hemisphere Boreal Zone also suggested improved performance of PPI over NDVI and EVI for the retrieval of SOS [54]. Modeling and satellite observations showed that the influence of snow on PPI was less severe than on the traditional vegetation indices. However, because the red reflectance of soil and vegetation may differ greatly, PPI is more sensitive to soil brightness than EVI, though the difference is reduced with increasing LAI [50]. We demonstrated a clear systematic difference between VIs, likely related to their different sensitivities to changes in snow cover and vegetation activity. Remote sensing VIs were more closely related to the development of the canopy structure, which occurred ahead of photosynthesis in the spring and persisted after the cessation of photosynthesis in the autumn.