K. Sakellari, Stochastic exploration of atmospheric humidity on a global scale, Diploma thesis, 100 pages, Department of Water Resources and Environmental Engineering – National Technical University of Athens, Athens, March 2017.
For the stochastic investigation of the atmospheric moisture globally, temperature and dew point are the selected hydro-meteorological variables to examine. Hourly records of 953 global weather stations are used. The long-term persistence of hourly dew point is investigated, an adaptation for bias is done and then 10,000 synthetic series are produced using the multiple time-scale fluctuation algorithm in order to verify the value of the Ηurst coefficient of the historical data. In addition, the skewness and kurtosis of the standardized temperature and dew point data are computed. Furthermore, the double cyclostationarity of dew point is investigated using the data of the 22 best stations of the sample. Finally, the distributions of the standardized temperature and dew point data of the 22 best stations are compared to the Gaussian distribution using QQ-plots.