Results

3.1 Comparison of model performance

Globally, the LUE-EF model had the highest correlation coefficient of r = 0.86, followed by the LUE-NDWI model with r = 0.82 (Fig.1a). The LUE-EF model had the smallest normalized RMSE (0.50), indicating that the difference between the LUE-EF model and EC-towers GPP was the smallest among all models. The LUE-NDWI model had the second smallest normalized RMSE (0.52). The normalized RMSE for the other models was larger than the two new models. Model LUE-EF simulated the amplitude of the variations close to the data amplitude of EC-towers (SD ratio=0.93). When grouped by latitudinal zone (Fig.1b-e) the improvements of the new models were more apparent for tropical and northern temperate zones. In the temperate zones, the distribution of models in the Taylor diagram was relatively concentrated, whereas in the tropical and boreal areas there were larger differences among models. When grouped by biome (Fig.S2), the new LUE-EF model showed advantages of fit in simulating daily GPP for most biomes, both in terms of correlation coefficients and RMSE. For example, correlation coefficients were highest for LUE-EF in deciduous broadleaved and evergreen needleleaf forests, wetlands and grasslands (DBF, ENF, WET and GRA), with LUE-NDWI being the second highest in the latter three of those. It is important to note that these biomes also have the largest number of EC-towers. It is relevant to note that many biomes are underrepresented in the current EC-tower network, such as closed shrublands or deciduous needle-leaved forests (CSH and DNF), each represented by only one and two EC-towers. The Taylor diagram shows that the models in CSH, DNF and SAV are more dispersed, which means that model performances in these biomes vary greatly.
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