The Infrared signature of a defence platform is strongly influenced by environmental conditions. This paper will outline two alternative methods to select a subset of climatic data to represent a large dataset as an input for Infrared signature modelling. A binning and ranking algorithm first presented by Vaitekunas and Kim (2013) will be compared with a genetic algorithm. The results for five different geographic locations will be assessed by comparing the cumulative distribution functions of the subset and the original dataset. Quantile-Quantile plots and the Kolmogorov-Smirnov statistic will be used to assess the solutions for the two different algorithms.