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.
<Fig 1 roughly here>