# Weather Files for the Calibration of Building Energy Models
## 3 Results and Discussion
### Simulation and Calibration Results: Combination of On-Site and Third-Party Weather Data
The weather files weather_T, weather_GHI, and weather_DHI, in both houses, considerably improved the adjustment produced by the model calibrated with the weather file generated with the data of the third party. The models calibrated with weather_WS, weather_WD, and weather_RH improved very little or even worsened the results. Table 4 shows the results achieved when considering the base and the calibrated models in the checking period. These were very similar to those obtained during the training period, but in this case, there was no risk of overfitting because the data were independent of the training period. When the base models were simulated with the different weather files, only three of them complied with the limits suggested by Annex 58: the models simulated with weather_T and weather_GHI and the on-site data. The others did not meet the expectations (marked in red). However, when these models underwent the calibration process, they all improved their indices, introducing them within the range set out in Annex 58. When examining the effects of the sensors, as it happened during the training period, there was a group of sensors that generated weather files that improved the adjustment produced by the third-party data in both models--based and calibrated--these files were: weather_T, weather_GHI, and weather_DHI. The weather files weather_WS, weather_WD and weather_RH showed very little improvement and even worse when their results were compared with the models simulated with the third-party weather file. Looking at Table 4 (O5 house), one can see how an anomalous result was produced in the model calibrated with the weather file weather_WS. The result produced by the MAE index was much higher than the rest of the models, and could not be placed within the limits of Annex 58. This can be considered an outlier, as it does not apply to the rest of the tests performed. This result complies with that obtained after the comparative analysis of the weather files in the Taylor diagram (see Figure 6). One aspect that should be highlighted when looking at the results is that, for the two houses, and in both periods, there was a correlation between the improvement produced by the new weather files in the base models and that of the calibrated models. This correlation reached 95% for the two houses in the training period and 92% for the testing period. Looking at the results obtained, it could be concluded that, if there was a significant improvement in the degree of fit with the new weather file with respect to the third-party file, this will also occur if the model is subjected to a calibration process. This effect could be used as a prior qualitative test before carrying out the calibration process, which is costly in time. It should also be taken into consideration that the range of improvement between the based and calibrated models is not the same, and some discrepancies can occur. To summarize, Figures 7 and 8, respectively, produce a general view of the whole process, the results of which are discussed in the tables above. The dark grey bars represent the calibrated models, while the light grey bars represent the base models, which have not undergone any calibration process. The red dotted line indicates the limit imposed by Annex 58 to judge the quality of the model. When the models are below this line in the MAE index, they meet the quality conditions set. The effects of the calibration process and the different types of weather files on the energy models were also measured with the \(\rho\) index. Figures 9 and 10 show the \(\rho\) indices obtained by the different models when they were simulated and calibrated with the new weather files in the training and checking periods for both houses, as quantitatively shown in the tables described above. As in Figures 7 and 8, the light grey represents the model that was not subjected to any calibration process (base model), while the dark grey shows the results of the models that underwent the calibration process (calibrated model).