In this paper new comparison parameters are defined for assessing statistical similarity between two data sets. The new parameters are based on the commonly used Kolmogorov-Smirnov test. They allow quantifying differences between the cumulative distribution functions of each data series. These parameters are applied to global horizontal daily irradiation values from pyranometric measurements and satellite data. The test data from 38 stations distributed throughout Germany cover the time from 1995 until 2003. The results affirm that the new parameters contribute valuable information to the comparison of data sets complementing those that are found with the mean bias and root mean squared differences. (C) 2008 Elsevier Ltd. All rights reserved.