Using climate change models to assess the probability of weather extremes events: a local scale study based on the generalized extreme value distribution
ABSTRACT Regional climate models (e.g. Eta) nested to global climate models (e.g. HadGEM2-ES and MIROC5) have been used to assess potential impacts of climate change at regional scales. This study used the generalized extreme value distribution (GEV) to evaluate the ability of two nested models (Eta-HadGEM2-ES and Eta-MIROC5) to assess the probability of daily extremes of air temperature and precipitation in the location of Campinas, state of São Paulo, Brazil. Within a control run (1961-2005), correction factors based on the GEV parameters have been proposed to approach the distributions generated from the models to those built from the weather station of Campinas. Both models were also used to estimate the probability of daily extremes of air temperature (maximum and minimum) and precipitation for the 2041-2070 period. Two concentration paths of greenhouse gases (RCP 4.5 and 8.5) have been considered. Although both models project changes to warmer conditions, the responses of Eta-Hadgem2-ES to both RCPs are significantly larger than that of Eta-Miroc5. While Eta-Hadgem2-ES suggests the location of Campinas will be free from agronomic frost events, Eta-Miroc5 indicates that air temperature values equal to or lower than 5 and 2 °C are expected to present a cumulative probabilityof ~0.20 and ~0.05, respectively (RCP 8.5). Moreover, while the Eta-Miroc5 projected a reduction in the extreme-precipitation amounts, the Eta-Hadgem2-ES projected implausible large daily precipitation amounts. The Eta-Miroc5 performed better than the Eta-Hadgem2-ES for assessing the probability of air temperature and precipitation in Campinas. This latter statement holds particularly true for daily-extreme precipitation data.