# A Simulation Study of Global Evapotranspiration Components Using the Community Land Model
## 4 Conclusions and Discussion  
In this paper, the Qian atmospheric forcing dataset from 1952 to 2002 was used in the CLM4.0 and CLM4.5 land surface models for off-line simulation tests. Using reanalysis data provided by NOAA and CFSR and the FLUXNET data, and focusing on the seasonal variation in spatial patterns, the simulation results of CLM4.5 on global Ec, Et, Es and latent heat flux were evaluated, and the improvement of CLM4.5 compared with CLM4.0 was tested and analyzed. The main conclusions are as follows:  
1. The seasonal variation in the spatial pattern of the Ec is determined by the seasonal variation in the spatial distribution of precipitation and the sum of LAI and SAI. Ec mainly concentrates in the latitudes of 15\({}^{\circ}\) S-15\({}^{\circ}\) N in the tropics, but it is relatively rare in the desert and glacial permafrost regions. The ability of CLM4.5 to simulate the spatial distribution of the Ec in January and April is relatively strong. The simulated means of Ec from CLM4.5 are smaller in comparison to the reanalysis data. 2. CLM4.5 simulates well the seasonal variation of Et and the distribution of high and low centers, but the simulation results in most areas are relatively larger than the reanalysis data, and the simulation bias is particularly focused in the equator and the South Asia regions. Since the simulated Et in CLM4.5 in tropical evergreen broad-leaved forests is relatively small compared to CLM4.0, and as the other main PFTs are relatively large, the simulation results of CLM4.5 of Et in equatorial regions is lower than that of CLM4.0, while the Et of most other regions are relatively higher than those of CLM4.0. Compared with CLM4.0, CLM4.5 has a stronger simulation capability to simulate the spatial distribution of global Et, and its means are closer to the reanalysis data. Figure 11: Spatial distribution of global latent heat flux (units: W/m\({}^{2}\)): (**a-d**) difference between CLM4.5 and FLUXNET, (**e-h**) difference between CLM4.0 and FLUXNET, and (**i-l**) difference between CLM4.5 and CLM4.0. Although there is a large difference in the simulation of the high and low centers of global Es distribution in CLM4.5 compared with the reanalysis data, CLM4.5's ability to simulate the spatial pattern of global Et is better than that of CLM4.0. The simulation results of CLM4.5 for the spatial distribution of Es are worse than its results for Ec and Et. The simulated means of Es in CLM4.5 are closer than those of CLM4.0 to the reanalysis data, and the mean in October is almost entirely consistent with the reanalysis data. Compared with CLM4.0, the simulated Es in CLM4.5 in the middle and high latitudes of the Northern Hemisphere is significantly larger, although, only in October. 4. The simulated center position of the high and low values of latent heat flux and its seasonal variation in CLM4.5 are close to the reanalysis data. The ability of CLM4.5 to simulate the spatial distribution of the global latent heat flux in July is relatively strong. The simulated means of global latent heat flux in CLM4.5 is larger than the reanalysis data. The spatial distribution of the simulation bias of the latent heat flux in CLM4.5 is mainly determined by the bias distribution of Es rather than Et. The ability of CLM4.5 to simulate the spatial distribution of global latent heat flux shows little improvement relative to CLM4.0, but the simulation results of CLM4.5 on the means of latent heat flux have been improved. Although the simulated seasonal spatial distribution of global latent heat flux in CLM4.5 is basically consistent with the reanalysis data, there is still large negative bias in the middle and high latitudes in the Northern Hemisphere and positive bias in most of the Southern Hemisphere. The calculation of the spatial correlation coefficients in Section 3.4 shows that the simulated bias pattern of latent heat flux is similar to the bias pattern of soil evaporation, which may have implications for the further improvement of the CLM model.