## 4 Discussion
This approach is more robust to outliers, which is apparent in the temporal profiles, and is also likely to provide a more conservative estimate of fluxes than the MODIS data. The GlobAlbedo-derived values are also not constrained by an underlying biome map and so will not be affected by land cover misclassification. This may explain the variability and much lower correlation between the GlobAlbedo- and MODIS derived values seen for tile h09v05 above (central Southern USA, Section \"Central USA: Tile h09v05\", Figure 9). These points aside, the comparisons show that in general timing (phenology) information agrees within one or two weeks, particularly in the most important green-up and senescence phases of the year. This is about as good as might be expected given the various uncertainties introduced by the temporal compositing window of the MODIS data and the assumptions underlying both retrieval methods. The MODIS values tend to remain high during the winter, particularly for the evergreen needleleaf sites (see Figure 4). If these values were used for driving productivity models, then this would likely lead to over-estimates of winter GPP and NPP. However, the GlobAlbedo-derived values tend to be much lower/more conservative in the peak season, largely due to their being effective values. This would have the reverse effect of depressing estimates of GPP and NPP in the summer. If the LAI and fAPAR are to be used for timing or phenology studies, the clear winter phase of GlobAlbedo-derived LAI and fAPAR is likely to be advantageous. In general, the different RT model schemes lead to consistently lower values of LAI and fAPAR in the GlobAlbedo-derived products compared with MODIS. This is clearly demonstrated in the values of the slope of the regressions summarized in Table 2, which are almost all \(>\)1 for fAPAR, except for one or two cases where the correlations are particularly poor anyway. For LAI, this difference is even more marked with slopes mostly between 1.5 and 3 but up to 8 in one or two cases. It is worth stressing again that a naive comparison of one product against the other might lead to the conclusion that they are fundamentally incompatible, rather than estimates of the same properties made under different (but equally valid) assumptions. As a result, if values are to be used for surface energy balance, or driving global vegetation models, care must be taken to take this into account when using either product [49; 50]. The per-tile comparisons shown in Figures 9-12 show the same general behavior _i.e._, high correlations in areas of seasonal vegetation, less likely to be affected by cloud and/or snow, lower correlations elsewhere, and with consistently lower values of both GlobAlbedo-derived LAI and fAPAR (and much lower range). The slope and intercepts in the whole hemisphere comparisons, shown in Figures 13 and 14 are quite stable between NH and SH. However, the variation in slope and intercept is larger for winter than summer cases, which reflects the generally lower values of both, and more importantly, the reduced quality and frequency of observations. Globally, the comparisons between GlobAlbedo and MODIS fAPAR show:
* **mean slope 1.01, \(\sigma\) = 0.78**
* **mean intercept 0.03, \(\sigma\) = 0.10** The corresponding global comparisons between GlobAlbedo and MODIS LAI show:
* **mean slope 1.70, \(\sigma\) = 1.73**
* **mean intercept 0.15, \(\sigma\) = 0.58**  
The recommendation we would make is that if users require a transformation between GlobAlbedo-derived LAI and fAPAR products against those derived from different RT approaches and assumptions, particularly for a given site, they can calculate a site-based or tile-based local transformation using the GlobAlbedo nearline subsetting tool: [37]. This tool also allows users to obtain corresponding GlobAlbedo albedo values. Our results also suggest that particular care is required when comparing (or using) values over sites with poor observation quality (cloud, snow low sun angles) and/or strong differences in overstory/understory phenology.