Section 1: Earth system tipping points

Current state of knowledge

A.1. More than 25 Earth system tipping points have been identified from evidence of past changes, observational records and computer models. (Chapters 1.2, 1.3, 1.4)

A.1.1. In the cryosphere, six Earth system tipping points are identified, including large-scale tipping points for the Greenland and Antarctic ice sheets. Localised tipping points likely exist for glaciers and permafrost thaw. Evidence for large-scale tipping dynamics in sea ice and permafrost is limited. (Chapter 1.2.2)

A.1.2. In the biosphere, 16 Earth system tipping points are identified, including forest dieback (e.g. in the Amazon), savanna and dryland degradation, lake eutrophication, die-off of coral reefs, mangroves, and seagrass meadows, and fishery collapse. (Chapter 1.3.2)

A.1.3. In ocean and atmosphere circulations, four Earth system tipping points are identified, in the Atlantic Meridional Overturning Circulation (AMOC), the North Atlantic Subpolar Gyre (SPG), the Southern Ocean Overturning Circulation and the West African monsoon. (Chapter 1.4.2)

A.2. Some Earth system tipping points are no longer high-impact, low-likelihood events, they are rapidly becoming high-impact, high-likelihood events. (Chapters 1.2, 1.3, 1.4)

A.2.1. Multiple drivers are destabilising tipping systems, including climate change for most as well as habitat loss (e.g. deforestation), nutrient pollution and air pollution for some. Multiple drivers, interactions and feedback loops can make tipping thresholds difficult to assess. (Chapters 1.2.2, 1.3.2, 1.4.2)

A.2.2. Already, at today’s 1.2°C global warming, tipping of warm-water coral reefs is likely and we cannot rule out that four other systems may pass tipping points: the ice sheets of Greenland and West Antarctica, the North Atlantics Subpolar Gyre circulation, and parts of the permafrost subject to abrupt thaw. (Chapters 1.2.2, 1.3.2, 1.4.2)

A.2.3. Passing 1.5°C global warming, widespread mortality in warm-water coral reefs becomes very likely, and another three potential tipping systems start to become vulnerable: boreal forest, mangroves and seagrass meadows. (Chapter 1.3.2)

A.2.4. At 2°C global warming and beyond, several more systems could tip, including the Amazon rainforest and subglacial basins in East Antarctica, and irreversible collapse of the Greenland and West Antarctic ice sheets is likely to become locked in. (Chapters 1.2.2, 1.3.2)

A.2.5. Some systems can cross tipping points due to other drivers, or have their warming thresholds reduced by other human pressures, with for example Amazon dieback possible at lower warming if deforestation continues. (Chapters 1.3.2, 1.4.2)

A.3. Earth’s tipping systems can interact in ways that destabilise one another, making tipping ‘cascades’ possible. (Chapter 1.5)

A.3.1. Tipping systems in the climate are closely coupled together. Hence a tipping point in one system can have significant implications for other systems. (Chapter 1.5.1)

A.3.2. Most interactions between climate tipping systems are destabilising, tending to destabilise the Earth system beyond the effects of climate change on individual systems. (Chapter 1.5.2)

A.3.3. Global warming is rapidly approaching levels that could trigger individual tipping points in systems that can interact with and destabilise other tipping systems. (Chapters 1.2.2, 1.3.2, 1.4.2, 1.5.2)

A.3.4. Tipping ‘cascades’, where tipping one system causes another tipping point to be passed, and so on, are possible but currently highly uncertain. (Chapters 1.5.3, 1.5.4)

A.4. Early warning signals have been detected that are consistent with the Greenland Ice Sheet, AMOC, and Amazon rainforest heading towards tipping points. (Chapter 1.6)

A.4.1. Loss of resilience (the ability to recover from perturbations) is expected before reaching a tipping point, but does not directly reveal how close a tipping point is. (Chapters 1.3.1, 1.6.1)

A.4.2. Loss of resilience can occur in systems without tipping points, hence independent evidence that a system is prone to tipping is needed before interpreting loss of resilience as a tipping point early warning signal. (Chapters 1.6.1, 1.6.3)

A.4.3. The central western Greenland ice sheet, AMOC, and Amazon rainforest all have independent evidence of being prone to tipping and show observational evidence of loss of resilience consistent with moving towards tipping points. (Chapter 1.6.2)

A.5. The risks of crossing Earth system tipping points can be minimised through rapidly reducing anthropogenic drivers of global change. (Chapters 1.2, 1.3, 1.4)

A.5.1. Urgently and ambitiously reducing greenhouse gas emissions can limit the risks of crossing tipping points in the cryosphere, biosphere, ocean and atmosphere circulation. (Chapters 1.2.2, 1.3.2, 1.4.2)

A.5.2. Rapidly reducing other climate forcing agents, such as black carbon for the cryosphere, and aerosols for the monsoons, can further limit the risk of crossing specific tipping points. (Chapters 1.2.2, 1.4.2.3)

A.5.3. The risk of crossing biosphere tipping points can be minimised through a combined approach of rapidly reducing climate forcing and other interacting drivers such as deforestation, habitat loss and pollution, together with ecological restoration, inclusive conservation, and supporting sustainable livelihoods. (Chapter 1.3.2)

Priorities to advance knowledge

A.6. Deep uncertainties about Earth system tipping points can be reduced. (Chapters 1.2, 1.3, 1.4)

A.6.1. Short observational records and limited resolution of important feedback processes in models make assessing the existence and likelihood of tipping points difficult for many systems. (Chapters 1.2.2, 1.3.2, 1.4.2)

A.6.2. Key process uncertainties include: in the cryosphere, the potential for a marine ice cliff instability; in the biosphere, the complex interactions between ecohydrological and fire feedbacks; and in ocean and atmosphere circulation, the resolution of small- scale processes such as ocean mixing. (Chapters 1.2.2, 1.3.2, 1.4.2)

Recommendation:

A.6.3. Research funders, knowledge institutions and scientists should invest in reducing uncertainties surrounding the existence and likelihood of specific Earth system tipping points through targeted palaeo-data gathering, Earth observations, model development, knowledge sharing across disciplines, and a systematic model intercomparison project.

A.7. Assessment of Earth system tipping point interactions and possible cascades can be improved. (Chapter 1.5)

A.7.1. Earth system models can be improved to represent more tipping system interactions. Large ensembles of model runs can be used to detect less common but potentially important interactions. Direct causal interactions and indirect feedbacks – e.g. via changes in temperature – can be better quantified. (Chapter 1.5.5)

A.7.2. Palaeoclimate records of past abrupt changes can help identify and understand tipping point interactions and possible cascades. Methods of inferring causality can be applied to observational data to detect tipping system interactions. (Chapters 1.5.3, 1.5.5)

A.7.3. A fresh elicitation of expert knowledge could help identify potential tipping system interactions. (Chapter 1.5.5)

Recommendation:

A.7.4. Research funders, knowledge institutions and scientists should invest in improving assessment of tipping point interactions and possible cascades through the development and use of Earth system models, causal analysis of palaeoclimate and observation data, and expert elicitation.

A.8. Early warning of Earth system tipping points can be improved. (Chapter 1.6)

A.8.1. Model experiments can be designed and used to identify which observable variables and associated statistics are most promising to provide early warning signals of specific tipping points, and thus guide monitoring efforts. (Chapter 1.6.3)

A.8.2. Tipping point detection and early warning methods can be improved, with the application of machine learning showing promise. (Chapter 1.6.3)

A.8.3. For slow-tipping systems, such as ocean overturning circulations, investment in palaeo-data reconstructions can improve the potential to detect tipping point early warning signals. (Chapters 1.6.2, 1.6.3)

A.8.4. For fast-tipping systems, such as ecosystems, the reliability of early warning signals can be improved by reducing biases in satellite remote sensing data caused by missing data and by merging of data. (Chapter 1.6.3)

Recommendation:

A.8.5. Research funders, knowledge institutions and scientists should invest in improving early warning of Earth system tipping points through refining methods, use of models to guide monitoring efforts, palaeo-data gathering and improving remotely sensed datasets.