Harmful tipping points in the natural world pose some of the gravest threats faced by humanity. Their triggering will severely damage our planet’s life-support systems and threaten the stability of our societies.
In the Summary Report:
• Narrative summary
• Global tipping points infographic
• Key messages
• Key Recommendations
Executive summary
• Section 1
• Section 2
• Section 3
• Section 4
This report is for all those concerned with tackling escalating Earth system change and mobilising transformative social change to alter that trajectory, achieve sustainability and promote social justice.
In this section:
• Foreword
• Introduction
• Key Concepts
• Approach
• References
Considers Earth system tipping points. These are reviewed and assessed across the three major domains of the cryosphere, biosphere and circulation of the oceans and atmosphere. We then consider the interactions and potential cascades of Earth system tipping points, followed by an assessment of early warning signals for Earth system tipping points.
Considers tipping point impacts. First we look at the human impacts of Earth system tipping points, then the potential couplings to negative tipping points in human systems. Next we assess the potential for cascading and compounding systemic risk, before considering the potential for early warning of impact tipping points.
Considers how to govern Earth system tipping points and their associated risks. We look at governance of mitigation, prevention and stabilisation then we focus on governance of impacts, including adaptation, vulnerability and loss and damage. Finally, we assess the need for knowledge generation at the science-policy interface.
Focuses on positive tipping points in technology, the economy and society. It provides a framework for understanding and acting on positive tipping points. We highlight illustrative case studies across energy, food and transport and mobility systems, with a focus on demand-side solutions (which have previously received limited attention).
As alluded to earlier in this chapter, Artificial intelligence (AI), and in particular deep learning, is beginning to play an important role in tipping point prediction and EWS. With a wealth of data available now monitoring these systems, we can truly start to use these techniques alongside traditional EWS to attempt to fully understand Earth system tipping points. In addition to generic EWS derived from AI, we can conceive of system-specific AI-based EWS which are trained on models of specific climate tipping points. Eventually this might enable accurate prediction of critical thresholds in climate variables that would cause tipping, so that we can better predict when they would occur.