The present study investigates the energy efficiency of different container house configurations across thirty European locations. By employing Heating Degree Days (HDDs) and Cooling Degree Days (CDDs), the research delves into climatic zone exploration, providing a simplified climatic classification for residential purposes and comparing it with the Köppen–Geiger model. The authors use specific hourly climatic data for each location, obtained through dynamic simulations with TRNSYS v.18 software. Initially, the CDDs are calculated by using different base temperatures (comfort temperatures that minimize energy demand) tailored to the specific conditions of each case. Then, the thermal loads of container houses are evaluated in different climatic scenarios, establishing a direct correlation between climatic conditions and the energy needs of these innovative and modular housing solutions. By comparing stacked and adjacent modular configurations in container housing, particularly in post-disaster scenarios, the study underscores the importance of adaptive design to optimize energy efficiency. The analysis conducted by the authors has allowed them to propose a climate characterization model based on HDDs, CDDs, and solar irradiance, obtaining an effective novel correlation with the Köppen–Geiger classification, especially in extreme climates. The present model emerges as a powerful tool for climate characterization in residential applications, offering a new perspective for urban planning and housing design. Furthermore, the results reveal a significant correlation between climate classification and the specific energy needs of container houses, emphasizing the direct influence of regional climatic characteristics on energy efficiency, particularly in small-sized dwellings such as container houses.