Spatial Analysis of Extreme Temperature Indices under Climate Change Based on CORDEX Data and a Developed Bias Correction Method in Iran

In this research, the trend of spatial changes in extreme indices of temperature related to the health and agriculture sectors such as the number of frost days, number of summer days, number of icing days, number of tropical nights, growing season length, diurnal temperature range, cold spell duration index, and warm spell duration index were investigated for 54 synoptic stations throughout Iran for observational (1976-2005) and future (2025-2054) periods. Daily maximum and minimum temperature data of three regional climate models namely, CCSM4, MPI-ESM-MR, and NORESM1-ME from the CORDEX project under RCP4.5 and RCP8.5 scenarios were downscaled for each station using a developed multiscale bias correction method. Then, trends and changes of extreme temperature indices were investigated using Mann-Kendall and Sen’s trend line slope methods. The results indicated that the warm indices such as the number of summer days and tropical nights indices have had a positive trend at most stations in both observational and future periods. In contrast, cold indices like the number of frost days have had a decreasing trend in most stations. The results of cold and warm spell duration indices showed that most stations have had no trend for both periods. The growing season length has increased in more than 60% of stations (45% having a significant trend) mainly located in the northern, northwestern, and western regions of the country. Based on the results, it can be concluded that without considering thoughtful climate adaptation measures, some parts of the country may face health risks and limited habitability and agriculture in the future.