Assessment of Near-Future Temperature Extremes Using CMIP5 Ensembles Over Gujarat, India

The variability in hydro-climatological indicators severely affects environmental regulation, ecosystem sustainability and the occurrence of extreme events at a large scale. Determination of the extreme climatic indices is crucial for understanding the trend and severity of such events within a given period. Therefore, this study analyses the ETCCDI-defined temperature extreme indices using five CMIP5 models (BNU-ESM, canESM2, CNRM-CM5, MPI-ESM-LR and MPI-ESM-MR) under RCP4.5 and 8.5 scenarios for the period 2025 to 2050 in Gujarat, India. The Mann-Kendall and Sen’s slope estimator test was applied for the trend significance. The findings show that maximum and minimum temperature will increase by >1℃ under the RCP8.5 scenario by 2050. Cold spells are expected to decline significantly in both scenarios, while the multi-model mean (MMM) for warm spells exhibits an increasing trend in the RCP8.5 scenario. A significant decreasing trend is observed in cool nights and cool days in all models under both scenarios. Notably, except for the BNU-ESM and canESM2, other models project an increasing trend in warm nights however, MMM shows a significant increasing trend in the frequency of warm nights and days. Furthermore, the frequency of days with cool nights and days will decrease by >10% and ~20% respectively by the end of 2050. Spatially distribution analysis shows that the south-eastern part of Gujarat is likely to be more vulnerable to extreme events, as a higher frequency of such events has been observed over this area. It was also observed that the MPI-ESM-MR model demonstrated better predictive performance and outperformed other ensembles in the Gujarat region, as it shows a closer alignment with the MMM results.