Statistical return periods of extreme weather events

Abstract

The Middle East & North Africa (MENA) region is one of the most populated areas on Earth in terms of city population. There are 643 cities in MENA region with population of urban agglomerations with 300,000 or more in 2018 according to United Nations. In this thesis, return periods of extreme temperature events are calculated using the probability density functions. For this purpose, Global Climate Model (GCM) outputs of Max Plank Institute Earth System Model Mixed Resolution (MPI-ESM MR) and Hadley Global Environment Model 2 - Earth System (HadGEM2-ES) are dynamically downscaled to 50 km for the MENA region by using the Regional Climate Model v4.4 (RegCM4.4) for 2 different Representative Concentration Pathways scenar ios, namely RCP 4.5 and RCP 8.5. Elevation correction is applied to each point for sea level. Temperatures at city centers are calculated from the nearest 4 grid points using inverse distance squared interpolation method. Daily maximum temperatures histograms are plotted for each city and future predictions of return periods are com pared with the reference period of 1971-2000 using the means and standard deviations obtained from Gaussian Mixture Model. The results show that the frequency of extreme events increases for all cities between 2070 and 2099. Peaks in temperature distribution are diverging from each other which will cause more severe extreme events. This divergence would cause cities to have shorter transition seasons and their climate would transform into only 2 seasons.