Uncertainty of extreme events using Climate Extreme indices of CMIP5 models

General Circulation Models (GCMs)are the main tools to explore the climate system at global scales to study past climate and estimate future projections. In this thesis, we use GCMs at a regional scale in order to evaluate climate variability and changes in extreme events. The Alpine and the Andean region located in two different continents, Europe and South America respectively, both with different climatic characteristics and biodiversity. These are identified among the most vulnerable regions. Studies have shown that there is great variability in the climate change impacts over these regions, due to their complex topography. Hence the evaluation of temperature and rainfall simulations seasonal and annual time scales are studied using global climate models participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5). We evaluated the uncertainty of forty-nine CMIP5 models using monthly and daily data from the period 1850-2100, and how hydro-meteorological extremes have changed in temporal and spatial distribution over time. Climate extreme events are changing and therefore, affecting the population, the economy, and the environment in these regions. We provide an overview of present and projected changes in climate extreme indices defined by the Expert Team on Climate Change Detection and Indices (ETCCDI) based on daily minimum and maximum temperatures and precipitation. We used the Historical experiment and two emission scenarios (RCP4.5 and RCP8.5).