Evaluating the Meteorological Pattern of District Swat Using Different SSP Scenarios

This study investigates the observed and projected impacts of climate change in District Swat, Pakistan, using meteorological records and CMIP6-based projections under SSP2-4.5 and SSP5-8.5 scenarios. Metrological variables, such as temperature and precipitation,were examined for long-term trends, anomalies, and extremes. Machine learning techniques (XGBoost and SHAP) were used to identify the most relevant online datasets and climate models. ERA5 emerged as the most reliable online source, and INM-CM5-0, CNRM-CM6-1, and CMCC-ESM2 were selected as the best-performing GCMs. The Mann-Kendall test showed a significant rise in minimum and maximum temperatures based on future conditions. For instance, the maximum temperature under SSP5-8.5 had a significant increasing trend with a Kendall Tau value of 0.1517, a Sen Slope of 0.00018,and a p-value less than 0.001. In the meantime, the trend of precipitation under SSP2-4.5 was decreasing significantly, which indicated the likelihood of an even more arid future.Under SSP5-8.5, temperature anomalies might be as high as 6.5°C, and precipitation anomalies could be as low as -1.5 mm or as high as +2 mm.Furthermore, Intensity-Duration-Frequency (IDF) analysis indicated that extreme rainfall events are projected to intensify, with rainfall intensities for the 100-year return period increasing from an observed value of 340 mm/hr to 360 mm/hr under SSP5-8.5. These outcomes show a potential rising trend of warmer and possibly drier conditions in the Swat District, and higher vulnerability to severe weather conditions. The results show that we need infrastructure that can handle climate change, flexible water management plans, and aggressive planning to lessen the effects of future extreme weather events.