## 4 Methodology and Modeling
### The Morphing Procedure and Climate Files  
The _morphing_ process of climate files is executed using the tool CCWorldWeatherGen, version 1.9 [10]. The free tool projects future climate scenarios based on the period from 1961 to 1990 [32] using data from the global circulation model HadCM3 (Hadley Center \begin{table}
\begin{tabular}{c c c} \hline
**ABNT Bioclimatic Zone** & **ASHRAE Climatic Region** & **Representative City** \\ \hline
1 & 3A & Curitiba, PR \\
8 & 1A & Rio de Janeiro, RJ \\ \hline \end{tabular}
\end{table} 
Table 1: Representative cities. Coupled Model version 3), which models atmospheric and oceanic behavior on a global scale. It has a spatial resolution of approximately (300 \(\times\) 300 km), for which, given this low resolution, CCWorldWeatherGen performs a statistical process of dynamic downscaling and obtains the values of the climate variables for each location by averaging the results of four points on the HadCM3 model's spatial grid closest to the accurate coordinates of the desired location. The period considered in the model follows the World Meteorological Organization [36] recommendations, which establish a 30-year interval as the definition of climate behavior. The organization also maintains the recommendation that the period between 1961 and 1990 is taken as a standard common reference in studies, projections, and monitoring of the climate and its anomalies. HadCM3 model data are made available by the IPCC [37], and the CCWorldWeatherGen tool employs the Panel's A2 emissions scenario to modify climate files. The cited scenario projects global economic development with regional growth focuses in a heterogeneous world with a growing population, in which fewer measures favoring sustainable development are effectively applied (yet, it is not the worst-case emissions outlook assessed by the IPCC). CCWorldVeatherGen transforms a.epw file (EnergyPlus Weather) based on the desired extrapolation for the representative years of 2020, 2050, and 2080, according to the projections obtained by the HadCM3 model, each characterizing a defined climate period of 30 years: 2010 to 2039, 2040 to 2069, and 2070 to 2099, respectively. Regarding climate data for building simulations in the selected cities, a paper from 2015 [38] studies three types of existing climate files for Brazilian cities: TRY (Test Reference Year), SWERA (Solar and Wind Energy Resource Assessment), and INMET (Brazil's National Institute of Meteorology). The cited work evaluated several meteorological variables from the archives. Through this, it was possible to identify that the INMET files had data acquisition failures in some periods, linked to possible problems in the automatic sensors. Regarding SWERA data, few Brazilian cities have climate files of this type. Therefore, TRY files become necessary, Files of this type consider a real year within a 10-year period, treating it as a reference year without temperature extremes. However, TRY files do not present complete information about solar radiation data, which are supplied through the Typical Meteorological Year or TMY [39] file. In addition to having more information than TRY, it uses meteorological data from a longer interval, building a fictitious typical year with months from different years within an analyzed period of 15 years. The authors discourage using TRY files and recommend using TMY. Given considerations and recommendations [36; 39], one should opt for TMY-type files from older periods or a larger sample of years to ensure the reliability of the morphing process and the construction of realistic climate scenarios. In this sense, the authors of the present research chose to use the TMYx files, which construct typical meteorological years based on the entire existing collection period, made available by the Brazilian Building Labeling Program [40]. The original climate files' names are shown in Table 2, and the data sampling period.