Prediction of  Precipitation  in Western of Iraq by Using the LARS –WG 8.0 Model

In many regions, around the world, the living environment is under considerable pressure due to climate change. As a result of these challenges, researchers are now more motivated, to analyze and predict changes, in key climatic variables, such as temperature and precipitation, to provide valuable insights for future planning and management. The Long Ashton Research Station Weather Generator, simply refers to as (LARS-WG 8.0), is used for predicting daily precipitation under two scenarios: SSP2-45 and SSP5-85. The outputs of, five general circulation models (GCMs), are utilized from 2021 to 2040. The findings, suggest that, (1) a statistical analysis, confirmed the skill and reliability of the LARS-WG model in downsizing precipitation time series. As such, (2) the ensemble mean, of the five GCMs indicated a rise in both monthly and annual data for the specified timeframe compared to the baseline period of 1985–2015. The findings, can enhance our understanding, of how climate change impacts urban areas and the environment. Thereby motivating planners, and interested parties, to identify the most effective strategies for mitigating these effects.