Project description
Novel Earth system models for improved policymaking
Monitoring and studying climate changes worldwide is essential for understanding the tipping points of climate change and working to avoid them with innovations, or new technologies, that improve our current tools. The EU-funded OptimESM project will develop one such tool: an innovative, new generation of Earth system models. It will combine basic physical and biogeochemical processes with high resolution, which will offer unparalleled knowledge on climate change and crucial tools for simulations and policymaking regarding the climate. This technology will also be used to provide new policy-relevant emission and land use methodologies to reach Paris Agreement goals.
Objective
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.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
- natural sciencesbiological sciencesecologyecosystems
- natural sciencescomputer and information sciencesartificial intelligencemachine learning
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Programme(s)
Funding Scheme
HORIZON-RIA - HORIZON Research and Innovation ActionsCoordinator
601 76 NORRKOEPING
Sweden