## 3 Results and Discussion
### Discussion  
Although C3 and C4 type plants co-exist in the Pampa biome, there is a predominance of C3 metabolism plants as described by [27]. Tests were performed using FTP = 11 (C4 grasses) and FTP = 12 (C3 grasses); however, better results of statistical index were obtained for the FTP = 12, and the calibration was performed using this FTP. In addition, at the experimental site where the data were collected, there are herbivorous animals, especially beef cattle, managed under the grazing system. The presence of these animals is a common feature of the Pampa biome [55]. The model does not take into account the biomass extracted by the animals, however we understand that the calibration makes this representation. Inserting the biomass removal by herbivores in the model would be a structural change that is being implemented by BESM. As the animal load in the Pampa biome is, on average, uniform, this calibration can be used for the entire area covered by the biome. Regarding turbulent flux parameters (level 2), parameter \(V_{max}\) (the maximum velocity of carboxylation) stands out, representing a measure of the process through which enzyme Rubisco produces carbon compounds that become sugars and starches. This parameter has a direct impact on gross primary productivity (GPP) levels and consequently on \(NEE\) and can be considered representative of large regions provided that they include plant cover with similar plant species [9]. For all simulated variables, a significant improvement in results occurs after calibration. \(Rn\), \(LE\), and \(NEE\) presented the most significant improvements, especially in relation to daily averages. For the nocturnal period, practically no improvement in latent heat flux was seen. On the other hand, the diurnal representation of this variable improved remarkably. Decoupling between the simulated \(LE\) and the data observed for mid-April 2014, 2016, and 2017 (Figure 8b) was also reported by [25], who simulated the Brazilian Caatinga region. [25] describes limitations of the IBIS model in simulating latent heat fluxes when abrupt changes occur in the precipitation regime, especially because the model fails to capture large variations in the LAI for these periods. In fact, the LAI is a determining factor along with the radiative component that shapes evapotranspiration. However, unlike Caatinga, in which vegetation is predominantly xeromorphic, vegetation that predominates in the Pampa biome (Campos) is characterized by high levels of photosynthetic activity throughout the year and by an almost constant LAI. Southern Brazil does not experience dry and wet seasons as in semi-arid regions of Brazil, but rather two periods of the year are defined primarily by temperature variations: hot summer and cold winter seasons Figure 3. Both seasons are characterized by high precipitation volumes that are well distributed, and consequently soil water content levels remain high almost year-round ([46; 56]). Thus, among other factors, it can be said that the model failed to reproduce the reduction of the \(LE\) due to a decrease in photosynthetic activity associated with a reduction in surface temperature. Solar radiation reflected by the surface also partly explains errors found in the \(LE\) simulation. \(Rr\) is underestimated by 2 W m\({}^{-2}\) on average for almost every month of the year. Thus, for the model, with more energy available on the land surface, more energy is available for evapotranspiration, overestimating the observed \(LE\) value. The largest discrepancies between the calibrated simulation and observed data were found in sensible heat flux levels with high bias and RMSE values. This can be explained by the consistently poor simulation of daytime fluxes. The \(H\) simulation errors found may have resulted for two main reasons. The first is related to errors of 10 to 30% found in estimates of the observed fluxes by the Eddy Covariance system. As the model is based on the principle of energy conservation, such uncertainties violate this principle.