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Climate-related tipping points

 

Elements of the Earth system, including ecosystems, can suffer relatively rapid transitions in response to small changes in forcings, a process known as crossing a tipping point. Such transitions are often irreversible: the system does not return to its original state even when the forcing that caused it is brought back to its original value. The transition to a new state would have a high (even catastrophic) impact across multiple regions, physical processes, ecosystems and biodiversity, and should therefore be avoided (in line with the EU’s biodiversity strategy for 2030). Some of these tipping points may have already been crossed or have a high probability of being crossed during this century, like those caused in the ocean by warming, acidification and deoxygenation. Early warning signals, reversibility, hysteresis and resilience should be addressed through appropriate analysis methods. Mitigation pathways and safe operating spaces for humanity should be assessed and communicated to targeted audiences.

The ability and/or sensitivity of global Earth system models (ESM) to simulate tipping point crossings and other non-linear behaviour requires solid process understanding, firmly rooted in observational evidence, including from paleo-records. These processes need to be correctly represented in ESMs. The probability and impact of tipping point crossings and abrupt system changes need to be better quantified for a sound risk analysis (including aspects of irreversibility), addressing for example impacts on agriculture, fisheries, or health. Further, the approach to and crossing of tipping points lead to a loss of ecosystem resilience, causing a compounding effect in ecosystems already stressed due to non-climatic factors, and the potential for cascading impacts across trophic webs and ecosystems.

Projects should build on the results of and cooperate with, past and ongoing scientific research related to tipping points, abrupt ecosystems change and potential mitigation and adaptation strategies at global and regional levels.

When dealing with models, actions should promote the highest standards of transparency and openness, as much as possible going well beyond documentation and extending to aspects such as assumptions, code and data that is managed in compliance with the FAIR principles[[ FAIR (Findable, Accessible, Interoperable, Reusable).]]. In particular, beneficiaries are strongly encouraged to publish results data in open access repositories and/or as annexes to publications. In addition, full openness of any new modules, models or tools developed from scratch or substantially improved with the use of EU funding is expected. Finally, projects should take into account, during their lifetime, relevant activities and initiatives for ensuring and improving the quality of scientific software and code, such as those resulting from projects funded under the topic HORIZON-INFRA-2023-EOSC-01-02 on the development of community-based approaches.