Validation metrics of homogenization techniques on artificially inhomogenized monthly temperature networks in Sweden and Slovenia (1950-2005).

In order to correctly detect climate signals and discard possible instrumentation errors, establishing coherent data records has become increasingly relevant. However, since real measurements can be inhomogeneous, their use for assessing homogenization techniques is not directly possible, and the study of their performance must be done on homogeneous datasets subjected to controlled, artificial inhomogeneities. In this paper, considering two European temperature networks over the 1950-2005 period, up to 7 artificial breaks and an average of 107 missing data per station were introduced, in order to determine that mean square error, absolute bias and factor of exceedance can be meaningfully used to validate the best-performing homogenization technique.

Combining stochastic models of air temperature and vapour pressure for the analysis of the bioclimatic comfort through the Humidex.

Several studies evidenced the importance of the knowledge of the bioclimatic comfort for improving people's quality of life. Temperature and relative humidity are the main variables related to climatic comfort/discomfort, influencing the environmental stress in the human body. In this study, a stochastic approach is proposed for characterizing the bioclimatic conditions through the Humidex values in six sites of Calabria (southern Italy), a region often hit by heat waves in summer months.