## 3 Results and Discussion
### Discussion
A similar result was found by [13], although it was observed that the model overestimated \(H\) for the nocturnal period and mainly due to \(Rn\) overestimation. The second reason is related to the poor representation of soil heat flux (\(G\)) by the model. In general, overestimation of daytime \(G\) (10 to 50 W m\({}^{-2}\), not shown) occurs. Again, as the model seeks energy balance closure, it compensates for this surplus by understating H. The results of this study are similar to those reported in the literature [25; 57; 58; 59]. Ref. [60] noted that not considering a residual layer on the land surface can result in such overestimation. In addition, the LSEM tendsto overestimate \(G\) and mainly due to the low numerical resolution of soil temperatures close to the land surface, resulting in a delay in the representation of turbulent fluxes [56]. This is clear in the CMD representation of H (Figure 10a) and \(G\) (not shown). A decoupling of \(H.obs\) and \(H.clb\) curves is observed for the early hours of the morning. By the end of the afternoon, approximately after 5 p.m., the curves are similar again, precisely when differences with respect to \(G\) are smaller. Figure 14 shows the hysteresis of latent heat flux and sensible heat flux and net ecosystem exchange patterns of CO\({}_{2}\) against atmospheric variables air temperature (_Ta_), the vapor pressure deficit (\(VPD\)) and global radiation (\(Rg\)). Here, we clearly find the most pronounced errors for \(H\). While \(LE\) follows intense hysteresis patterns with respect to _Ta_ and \(VPD\), \(H\) underestimates the observed flux lag although it do follow the roughly elliptical form of the curves. In relation to \(Rg\), we find an overestimation of the \(LE\) mismatch and a displacement (rotation) of hysteresis in relation to \(H\). These results reinforce the model's difficulty in simulating \(H\), showing the better representation of parameterizations of this flux in relation to atmospheric forcing must be explored. Finally, the simulation of the net ecosystem exchange of CO\({}_{2}\) with the calibrated INLAND very closely reflected observed values and mainly in relation to the CMD. For the nocturnal period, we observed a slight underestimation of \(NEE\) (positive values); that is, the model is underestimating the ecosystem respiration. On the other hand, for the daytime period,  
Figure 14: Hysteresis loops relating: (**a**) latent heat flux (\(LE\)) against air temperature (_Ta_), (**b**) sensible heat flux (\(H\)) against _Ta_, (**c**) net ecosystem exchange of CO\({}_{2}\) (\(NEE\)) against _Ta_, (**d**) \(LE\) against deficit of water vapor pressure (\(VPD\)), (**e**) \(H\) against \(VPD\), (**f**) \(NEE\) against \(VPD\), (**g**) \(LE\) against global radiation (\(Rg\)), (**h**) \(H\) against \(Rg\), and (**i**) \(NEE\) against \(Rg\). Graphs correspond to observed values (\(obs\)) and simulated after calibration (\(sim\)) to the experimental site located in Santa Maria, southern Brazil, from 2014 to 2017. Numbers represent the hours of the day. \(NEE\) (negative values), indicating that the model overestimates the photosynthesis in the ecosystem. Despite this, good agreement between \(NEE\) and atmospheric forcing was found as illustrated by the strong representation of hysteresis in relation to \(Ta\), \(VPD\), and \(Rg\) (Figure 14). Moreover, in natural pasture of the Pampa biome, the presence of cattle is common [26]. The presence of these animals can affect \(NEE\), especially by soil fertilization.