Projected Changes in Rainfall and Temperature in Southern Sri Lanka Using CMIP6 Models under Various Shared Socioeconomic Pathways for Different Climatic Periods

Abstract

Climate change constitutes a formidable obstacle to pursuing sustainable development across numerous nations. Sri Lanka is facing significant challenges due to climate change. In response, individuals and organizations are mobilizing efforts to address this pressing issue. This study centers on the anticipated alterations in precipitation and temperature within the Southern Province of Sri Lanka, utilizing models from the Coupled Model Intercomparison Project Phase 6 (CMIP6). This research employed downscaled data from the grid, specifically representing the Southern Province. Various models were leveraged to analyze this downscaled data, further enabling the projection of future climate changes under diverse scenarios and temporal frameworks. Validation was carried out by juxtaposing model-simulated historical climate data with actual observed records, a process that is essential for ensuring the study's data reliability. Downscaled data were analyzed using the trend pattern for different models. The multimodel ensembles revealed distinct patterns of temperature and precipitation increase across different Shared Socioeconomic Pathways (SSPs) 4.5 and 8.5 in the Southern Province from 2020 to 2100. Under the SSP2-4.5 scenario, the projected temperature is anticipated to rise by 1.18°C, with a corresponding increase in rainfall of 122.76 mm. In the SSP5-8.5 scenario, the temperature is projected to escalate by 1.91°C, along with a 148.47 mm rise in precipitation. Although these projections are grounded in model simulations, the actual consequences will be contingent upon future greenhouse gas emissions. The Southern Province may witness significant changes in both the intensity and duration of temperature and rainfall. Policymakers and communities should integrate these climate projections into their development and implementation of climate change adaptation strategies.