The AL-DAMMAM unconfined groundwater aquifer region in western Iraq, characterized by its arid to semi-arid climate, suffers major effects from climate change. This study employed the Long Ashton Research Station Weather Generator (LARS-WG 8), a stochastic model designed for climate scenario generation to project future temperature and precipitation pattern changes. Climate projections were developed based on two widely used shared socioeconomic pathways (SSP2-4.5 and SSP5-8.5) using outputs from four CMIP6 (Coupled Model Intercomparison Project Phase 6) global climatic models (ACCESS-ESM1-5, HadGEM3-GC31-LL, MPI-ESM1-2-LR, and MRI-ESM2-0), covering projections until the year 2100. Historical records from 1993 to 2023 were used to calibrate and validate the model at five representative meteorological stations (Kerbala, Najaf, Ramadi, Haditha, and Rutba). The simulation was driven by NASA (National Aeronautics and Space Administration) datasets for daily minimum and maximum temperatures and CHIRPS (Climate Hazards Group InfraRed Precipitation with Station data) data for daily precipitation. The results of model validation demonstrate excellent performance with R2 0.988-0.99, RMSE lower than 0.26 degrees C for temperature, and 0.942-2.05 mm for precipitation. Also, the results show that SSP5-8.5 will culminate in maximum temperature rises by 1.24 degrees C (near-term) to 4.68 degrees C (end-century), with Najaf probably reaching 50.3 degrees C by 2100. The annual precipitation projections showed a general increasing trend with high spatial variability, with projected increases up to 30 mm in some areas. All stations demonstrate a pronounced seasonal pattern, with the most precipitation occurring in winter and early spring and minimal rainfall during the summer months. For the management of water resources and groundwater recharge patterns in this susceptible semi-arid area, these changes present major challenges. These findings provide crucial insights into potential climate change impacts on the AL-DAMAM aquifer, which could support the development of effective adaptation strategies for water resource management in this vulnerable region.