Local climate classification is mandatory for building energy standards and codes. The degree-days method is one of the most widespread methods used for climate classification. Many degree-days models are available for determining the cooling degree days (CDD) and the heating degree days (HDD). A limited number of studies have been conducted to evaluate the performance of these models in cooling-dominated climates, which is mandatory before a model is adopted for climate classification. In this research, five models, namely the hourly method, ASHRAE method, Erbs method, Schoenau and Kehrig (S-K) method, and hybrid S-K method, were evaluated and analyzed for predicting CDD and HDD. Hourly data from selected meteorological stations located in different regions of Oman were used. The results indicated that the performance of all models was acceptable and within 10% variation from the hourly method, with the hybrid S-K model being the best among all models. This model was then used to estimate the CDD and HDD for 31 weather stations in Oman using the monthly average temperature data. Regression models were then developed for CDD and HDD at different base temperatures, with determination coefficient, R2, of higher than 99%, maximum error of 4.9, and − 0.217% for CV[RMSE] and NMBE, respectively. Using the GIS ArcMap, the CDD values were used to generate the climate classification for Oman. Subsequently, four climate zones were identified, namely hot-humid climate, hot-dry climate, warm-humid climate, and high-altitude climate. The developed climate classification is useful and can be used for building energy efficiency programs, standards, and codes.
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