Speaker: Simone Russo
Date and time: Wednesday, March 26, 2014, 15:00 UTC
Abstract: The probabilities of the occurrence of extreme dry/wet years and seasons in Europe are estimated by using both the Standardized Precipitation Index (SPI) and the Standardized non-stationary Precipitation Index (SnsPI). The latter is defined as the SPI by fitting precipitation data with a non-stationary Gamma distribution, in order to model the precipitation time dependence under climate change. Daily precipitation outputs from five different regional climate models provided by the ENSEMBLES project, and bias corrected, are used. The five RCMs are selected as to represent the main statistical properties of the whole ENSEMBLES set, and the most extreme deviation from the ensemble mean. All indicators are calculated both for the ensemble of the five models over the period 1961-2098. Results show that, under global warming, climate in Europe will significantly change from its current state with the probability of the occurrence of extreme dry and wet years and seasons increasing respectively over southern dry and northern wet regions. Comparing non-stationary and stationary indices, the SnsPI is found to be more robust than the common SPI in the prediction of precipitation changes with multi-model ensembles.
About the speaker: Simone Russo has been a researcher for over 10 years in the field of applied physics. He has an M.Sc. in Physics from the University of Catania and a Ph.D in Applied Physics from Galileo Galilei school (Pisa University Italy). He has worked as research climatologist at the Royal Netherlands Meteorological Institute (KNMI, De Bilt, Netherlands), at the Laboratoire de Physique des Océans (University of Brest, France), and the Institute for Environmental Protection and Research (Ispra, Rome, Italy).
Currently he is working at the Joint Research Centre (European Commission, Italy) focusing on the detection of extremes in present climate and their projection to a future warming climate.