Optimal High Resolution Earth System Models for Exploring Future Climate Changes

OptimESM将开发新一代地球系统模型（ESM），将高分辨率与关键物理和地球化学过程的前所未有的表现相结合。这些模型将用于提供关于达到或超过不同程度的全球变暖的后果的尖端和政策相关知识，包括关键地球系统现象迅速变化的风险以及全球变暖程度和突然变化的发生所产生的区域影响。OptimESM将通过将四个ESM小组与综合评估建模团队以及模型评估，地球系统过程，机器学习，气候影响和科学传播方面的专家聚集在一起来实现这些目标。OptimESM将进一步开发新的政策相关排放和土地使用情景，包括实现《巴黎协定》的情景，以及暂时或永久超过《巴黎协定》目标的情景。使用这些情景，OptimESM将提供长期预测，这将增加我们对触发冰盖、海冰、海洋环流、海洋生态系统、永久冻土和陆地生态系统等现象的潜在临界点的风险的理解。OptimESM将进一步加深我们对控制这些临界点的过程的理解，将超过各种临界点的风险归因于全球变暖的水平，并开发一系列技术来预警真实的世界中临界点的发生。人工智能（AI-）统计降尺度方法将被开发和应用，以提高我们对长期全球变化和临界点对区域气候，特别是极端事件的影响的理解。OptimESM的新知识和数据将积极传达给其他学科，如影响和政策研究社区以及公众。这些知识将为可采取行动的科学政策奠定坚实的基础。

OptimESM will develop a novel generation of Earth system models (ESMs), combining high-resolution with an unprecedented representation of key physical and biogeochemical processes. These models will be used to deliver cutting-edge and policy-relevant knowledge around the consequences of reaching or exceeding different levels of global warming, including the risk of rapid change in key Earth system phenomena and the regional impacts arising both from the level of global warming and the occurrence of abrupt changes. OptimESM will realise these goals by bringing together four ESM groups with Integrated Assessment Modelling teams, as well as experts in model evaluation, Earth system processes, machine learning, climate impacts and science communication. OptimESM will further develop new policy-relevant emission and land use scenarios, including ones that realise the Paris Agreement, and others that temporarily or permanently overshoot the Paris Agreement targets. Using these scenarios, OptimESM will deliver long-term projections that will increase our understanding of the risk for triggering potential tipping points in phenomena such as, ice sheets, sea ice, ocean circulation, marine ecosystems, permafrost, and terrestrial ecosystems. OptimESM will further our understanding of the processes controlling such tipping points, attribute the risk of exceeding various tipping points to the level of global warming, and develop a range of techniques to forewarn the occurrence of tipping points in the real world. Artificial Intelligence (AI-) methods for statistical downscaling will be developed and applied to improve our understanding of the effect of long-term global change and tipping points on regional climate, particularly extreme events. New knowledge and data from OptimESM will be actively communicated to other disciplines, such as the impacts and policy research communities, as well as the general public. This knowledge will provide a solid foundation for actionable science-based policies.