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Climate change research is based on scenarios derived from socioeconomic, climate, and impact modeling and their outputs. Each scenario has a mutual input-output relationship, and inter-disciplinary collaboration through the passing of scenarios ensures consistent knowledge. This process involves compounding uncertainties associated with modeling limitations and knowledge gaps. To address these uncertainties, model intercomparison projects have been conducted to improve understanding in different fields, and novel methods including those with emulators have been developed for synthesizing multi-model outcome and supporting observations. From this perspective, this session aims to promote interdisciplinary collaboration in scenario-building processes and invites presentations on all aspects of modeling methods and uncertainties, encompassing, but not limited to, recent progress in scenario frameworks and model intercomparison, key processes leading to reducing uncertainties, the development and application of different types of emulators, and the methodologies of assessing scenarios with uncertainty quantification.