Abstract
The open source development paradigm was employed to develop a computational tool to process daily air temperature data. The computational workflow included data preprocessing, clustering procedure, as well calculation and visualization of the energy-related climate characteristics. Applicability of the developed tool was demonstrated considering an analysis of the regional features related to the heating and cooling energy demand indicators. It has been found that the considered locations have distinctively different patterns of the heating and cooling degree-days, despite of the very close values of the annual average temperatures.
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