## 4 Evaluation of Model Developments
### Evaluation of Updated Land Cover and Vegetation  
4.3.1. Land Use/Land Cover and Leaf Area Index Evaluation  
Evaluation of the new ESA-CCI LU/LC map and LAI disaggregation operator is performed through global offline and forecast coupled simulations. The offline simulations are driven by ERA5 meteorological data. A control simulation (CTR) with the current operational maps is compared with a simulation that includes the new ESA-CCI LU/LC map and the new LAI disaggregation operator (CLAI). The impact of the changes in LU/LC and LAI are assessed by evaluating the mean diurnal range of Land Surface Temperature (LST). The simulations are compared with the (LSA-SAF) LST. For each day and pixel, when at least 75% of the 3-hourly data was available the daily maximum and minimum LST are extracted to compute the diurnal range (representing the amplitude of the diurnal cycle) and the evaluation is performed for different seasons for the period 2004-2015. The mean LST diurnal range bias of the control simulation during June-August (JJA) and September-November (SON) for the 2004-2015 period is shown in Figure 9a,b. These two seasons were selected due to the high coverage of clear-sky conditions in the MSG disk, but the main features of the biases are similar in the remaining seasons. In both seasons there is wide-spread and substantial under-estimation of the diurnal range, which can reach values larger than 6 K in several regions such as the Iberian Peninsula, Southern Africa and East South America. During JJA there are indications of an over-estimation of the diurnal range in West Sahara and the Arabian Peninsula (Figure 9a). However, in these two regions there are some concerns on the quality of the LST satellite retrieval due to contamination by aerosols (West Sahara) and emissivity directional effects (Arabian Peninsula). The change in mean absolute error of the mean LST diurnal range between the simulation with the new ESA-CCI LU/LC and LAI (CLAI) and the control simulation for JJA and SON are shown in panels c,d of Figure 9. The results show a general reduction of the under-estimation of the diurnal range in the CLAI simulation. The increased diurnal range in CLAI is mostly driven by higher daytime maximum LST (not shown) and are consistent with previous results that indicated the added value of the updated LC and LAI in CLAI in terms of the LST diurnal cycle. Previous studies have also explored the role of vegetation seasonality [37; 88], suggesting that further improvements of the LST diurnal cycle can be achieved. In addition to the evaluation of the LST diurnal range, the mean evaporation of the CTR and CLAI simulations are compared with two independent estimates of evapotranspiration (ET) mostly constrained by remote sensing data: (i) the GLEAM version 3b ([PERSON] et al. [78]) and (ii) FluxCom Remote sensing ensemble flux products [76]. Figure 10 shows the comparison of evaporation (ET) 2003-2015 annual mean between the control run (CTR) and the CLAI run. Left panels show the CTR percentage bias (\(pbias=100(exp-obs)/obs\)) with regards to GLEAM (GL3b) and FluxCom (FCRS) ET products as observation proxies (a and c panels respectively). The right panels show the absolute \(pbias\) difference between the CLAI experiment and the CTR experiment, where GLEAM has been used for verification in panel (b) and FluxCom in panel (d). These differences show an overall reduction of the bias compared to both products (green colour). However, the results also show that on an annual time-scale, the improvements in \(pbias\) with CLAI with respect to CTR are fairly small compared to the differences of the observational-based products. The latter is illustrated by comparing GLEAM and FluxCom in panels (a) and (c). It highlights the uncertainty in estimating ET as also confirmed in [PERSON] et al. [76]. Evaluation of coupled forecast simulations is performed against the operational analysis.