## 3 Results and Discussion
### Daily Variations and Seasonal Dynamics of Simulated Energy Fluxes  
Figure 3 shows the daily cycle of observed energy fluxes (solid black line), non-calibrated simulated data (dashed blue line) and calibrated simulated data (dashed red line) for Rn, H, LE and G during the wet season (February to May 2014) and Figure 4 shows the daily cycle of energy fluxes during the dry season (August to October 2014). Regarding observed values one can note that the components behave according to the daytime behavior of solar radiation, with maximum values occurring between 11h and 12h (local time). During the wet season, peak H and LE values were of 230 W m\({}^{-2}\) and 218 W m\({}^{-2}\), which corresponded to approximately 40% of Rn (564 W m\({}^{-2}\)), respectively (Figure 3). During the dry season, however, most of Rn (peak value of 582 W m\({}^{-2}\)) is clearly converted to H (peak value of 404 W m\({}^{-2}\)). The peak LE values are very small (20 W m\({}^{-2}\)) and the values of G and LE are approximately equivalent (Figure 4). The non-calibrated simulation severely underestimated daily H, as much as 40% in the wet season and 66% in the dry season (Figures 3B and 4B; respectively). Additionally, daily LE were overestimated by approximately 45% during the wet season and by up to 8.5 times in the dry season (Figures 3C and 4C; respectively). After the calibration of the biophysical parameters (Table 2), the model satisfactorily described the daily variations of Rn, H, LE and G (\(r>\) 0.8, \(d>\) 0.7; Table 3). In general, the adjusted Rn and G were satisfactory, with \begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline  & \multicolumn{6}{c}{**Statistic**} \\ \hline  & \multicolumn{6}{c}{**2014**} & \multicolumn{6}{c}{**2015**} \\ \cline{2-9}  & \(r\) & **MAE** & **RMSE** & \(d\) & \(r\) & **MAE** & **RMSE** & \(d\) \\ \hline Energy flux & & & & & & & \\ Rn (W m\({}^{-2}\)) & 0.98 & 43.84 & 80.46 & 0.94 & 0.96 & 31.70 & 50.56 & 0.98 \\ H (W m\({}^{-2}\)) & 0.85 & 50.52 & 68.83 & 0.89 & 0.91 & 46.94 & 71.97 & 0.89 \\ LE (W m\({}^{-2}\)) & 0.69 & 29.97 & 65.99 & 0.72 & 0.71 & 24.25 & 53.48 & 0.74 \\ G (W m\({}^{-2}\)) & 0.90 & 9.90 & 13.66 & 0.92 & 0.90 & 11.07 & 16.23 & 0.91 \\ CO\({}_{2}\) flux & & & & & & & & \\ GPP (g C m\({}^{-2}\) h\({}^{-1}\)) & 0.82 & 1.24 & 1.53 & 0.86 & 0.91 & 1.38 & 2.05 & 0.79 \\ NEE (kg C m\({}^{-2}\) h\({}^{-1}\)) & 0.84 & 1.99 & 2.25 & 0.83 & 0.81 & 1.74 & 2.00 & 0.80 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Results of the Pearson correlation coefficient (\(r\)), median absolute error (MAE), root mean square error (RMSE) and [PERSON]’s index of agreement (\(d\)) between eddy covariance observations of energy and CO\({}_{2}\) fluxes and simulations with the parameters set after calibration for the years 2014 and 2015. \(r>0.9\) and \(d>0.9\) (Table 3). However, LE was not satisfactorily simulated (\(r\)\(<0.7\)) in the dry season (Figures 1 and 4). The main weakness of the model was in relation to the simulation of peak hours (approximately 12:00 local time), where H was underestimated in the wet season (15%) and the dry season (16%) (Figures 3 and 4). On the other hand, simulated LE presented a good adjustment (\(r>0.8\)) with observed data in the wet season, but overestimated it by approximately 35% in the dry season (Figure 4). These results indicate a certain difficulty by the model to represent variations of energy fluxes at peak times, even after exhaustive calibration tests. Figure 4: Simulations without calibration (dashed blue lines), simulations with calibration (dashed red lines, simulation U) and eddy covariance observations (solid black lines) of mean daily cycle of energy fluxes during the dry season of 2014. Net radiation (Rn; (**A**)), sensible heat flux (H; (**B**)), latent heat flux (LE; (**C**)) and soil heat flux (G, (**D**)). Vertical bars indicate the standard deviation of fluxes.