Analysis of projected monthly changes of extreme temperature indices to support decision-makers

As global warming intensifies, the building of adaptation and mitigation strategies has become an urgent task. In the centre of these strategies often lie extreme weather events, which are expected to become even more severe and more frequent in the next decades. Therefore, extending our knowledge on the potential changes in these events is crucial to provide assistance for appropriate preparation and planning necessary actions. Using the latest CMIP6 global climate model simulations available in the IPCC’s Interactive Atlas (IA), a study on extreme events focusing on Europe was completed, with special emphasis on Central Europe.

Our goal was to study the potential changes of extreme temperatures over the continent, in order to analyse the spatial patterns and trends of changes for the end of the 21^st century. First, monthly multi-model mean data were downloaded from the IA for two different extreme temperature indices. The number of days with maximum temperature above 35 °C (i.e. TX35) and the number of days with a minimum temperature below 0 °C (i.e. frost days or FD) were selected for the analysis. The use of both hot and cold extreme temperature indices enabled us to cover every month in our study with TX35 analysed in the May–September and FD in the October–April period. Our target period was the 2081–2100 period compared to the values of 1995–2014 (i.e. the last two decades of the historical simulation period) as a reference. Every scenario available in the IA was considered, namely, SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5.

Six zonal segments were defined over Europe to analyse the projected changes, ensuring that the segments fairly cover the continent. This approach is able to reveal the major effects creating the spatial patterns in different regions. The most important effects are (i) the differences due to the north-south or east-west locations (i.e. the zonal and continental effects), (ii) elevation above sea level (i.e. the orographical effect), and (iii) the different levels of anthropogenic forcing (i.e. the different scenarios).

Our results show that the anthropogenic effect is a key factor due to the direct connection between the greenhouse effect and air temperature. Moreover, the sea-land surface differences have the greatest effect on the magnitude of changes in the indices, while continentality is also an important factor. Potential differences due to elevation, however, are often supressed by the spatial patterns created by sea-land differences.