# Using Satellite-Derived Vegetation Products to Evaluate LDAS-Monde over the Euro-Mediterranean Area
## 3 Results
### Evaluation Using Satellite-Derived Vegetation Products  
#### 3.2.1 Evapotranspiration and GPP  
The consistency of the analysis with the evapotranspiration product from the GLEAM product and the GPP product from the FLUXNET-MTE dataset is evaluated in this section. Since these products are only available at the monthly scale, they were compared to monthly averaged analyzed simulations. The GPP product from the FLUXNET-MTE dataset is only available until 2011, so only the years 2007-2011 are considered in the statistics below. Figure 4 shows monthly mean time series of evapotranspiration and GPP over the Euro-Mediterranean area of the open-loop and analysis simulations and of the products. The dynamics of the simulated evapotranspiration variable was in line with GLEAM with a slight overestimation in winter and underestimation in summer. The impact of the assimilation was generally small, but is more noticeable during the summer season. The analyzed values were closer to the observations in the summer time. This was confirmed by the seasonal statistics shown in Figure 5, where they tend to be slightly better for the analysis during summer with lower RMSD values and higher correlation scores. Statistics for the whole time period (Table 1) showed that the assimilation of SSM and LAI products slightly improved the consistency of the model with GLEAM. Figure 3: Monthly seasonal scores (RMSD and correlation R) of the open-loop (blue) and analysis (red) simulations from 2007–2015 averaged over the Euro-Mediterranean area compared to the observations of: (**a**) SSM and (**b**) LAI. Red shade indicates an improvement from the assimilation process with either a lower error or a higher correlation score. Compared to the LDAS analyzed evapotranspiration, the GLEAM product had an RMSD varying from 0.3 kg\(\cdot\)m\({}^{-2}\)\(\cdot\)day\({}^{-1}\) in winter to 0.8 kg\(\cdot\)m\({}^{-2}\)\(\cdot\)day\({}^{-1}\) between May and July. The highest RMSD values mainly occurred over forested areas (not shown). Regarding the GPP variable, the simulated dynamics was consistent with FLUXNET-MTE, but the analyzed monthly GPP exceeded 5 g(C)\(\cdot\)m\({}^{-2}\)\(\cdot\)day\({}^{-1}\) only once (in 2013), while FLUXNET-MTE seemed to exceed this value for all the years. The assimilation only slightly reduced the mean bias between the simulations and FLUXNET-MTE. However, Figure 5 shows that the assimilation markedly reduced RMSD in summer. The assimilation also significantly improved the correlation scores during the other seasons. The statistics were also slightly improved when looking at the whole time period (Table 1) with a decrease of 10% in the bias and in the Standard Deviation of Differences (SDD) values. Compared to the LDAS analysis, the FLUXNET-MTE GPP product had a RMSD varying from 0.2 g(C)\(\cdot\)m\({}^{-2}\)\(\cdot\)day\({}^{-1}\) in winter to 2 g(C)\(\cdot\)m\({}^{-2}\)\(\cdot\)day\({}^{-1}\) between June and August. The highest RMSD values mainly occurred over areas covered by crops (not shown). Figure 4: Monthly time series of the products (green), open-loop (blue) and analysis (red) simulations from 2007 to 2015 averaged over the Euro-Mediterranean area for: (**a**) evapotranspiration; (**b**) gross primary production (observations only until 2011). In Figure 6, temporal correlation maps are presented, representative of the time evolution of the variable itself at a specific location. This figure shows the spatial distribution of the correlation for the whole available period (2007-2015 for the evapotranspiration, 2007-2011 for GPP) between the analysis and the observations. The model open-loop simulations already gave very good results in terms of correlation with 65% of the points with a correlation greater than 0.90 for the evapotranspiration and 55% for GPP (not shown). After the joint assimilation of SSM and LAI, 70% and 64% of the points had a correlation higher than 0.90 respectively.