Projected changes in the frequency of thermal comfort conditions at cold and warm cities, based on advanced bioclimatic indices

Climate change and global warming affect heat or cold related stress in humans and ecosystems. Human thermal comfort or discomfort conditions in particular, are assessed through the application of simple or rational thermal (or bioclimatic) indices. In contrast to simple, advanced indices like the Universal Thermal Climate Index (UTCI) are based on human energy balance between the human body and thermal environment and involve multiple meteorological parameters, like air temperature, air humidity, wind speed and mean radiant temperature. Accelerating warming is expected to affect both heat and cold related stress conditions in the future, resulting in increased frequency of heat related stress, especially at warmer cities like the cities of Mediterranean, and at the same time reduced frequency of cold related stress at colder cities, like the cities of northern Europe. Asymmetrical changes in the frequency of heat or cold related stress conditions will eventually determine the future changes (increases or decreases) in the frequency of conditions of no thermal stress at cities of different background climate. The study will investigate future changes in ‘thermal comfort’ or ‘favourable’ conditions at cities with different base climate. Simulations by a set of state-of-the-art Regional Climate Models (RCMs) in the frame of EURO-CORDEX (Coordinated Regional Climate Downscaling Experiment) modeling experiment (http://www.euro-cordex.net) with a horizontal resolution of about 12 km (0.11°) downscaled over the areas of interest will be realized for a control period and for two periods in the near and distant future, under the RCP4.5 and RCP8.5 future emissions scenarios. Simulations of meteorological variables for the estimation of UTCI at 3-hourly step will be retrieved for the closest land model grid point to the observation sites, while the performance of the RCMs will be evaluated against results from observations for the control period.