DIEP seminar by Jacques Bara
Humanity will not avoid 1.5°C of global warming without, at least, temporarily exceeding it, with the United Nations Environmental Programme very recently estimating the lowest peak warming feasibly achievable at 1.8°C. This threatens multiple climate tipping elements, large-scale climate subsystems -- such as the Amazon rainforest and the West Antarctic ice sheet -- that undergo abrupt, oftentimes irreversible transitions when their critical threshold in global warming is exceeded. Moreover, these subsystems interact in non-linear ways, whereby the collapse of one may stabilise or even destabilise others, causing potential cascades and domino effects throughout the network. To avoid extreme tipping risks under global warming overshoots, it is vital, therefore, to understand interacting tipping dynamics under overshoots and to characterise which overshoots are safe.
In this talk, I will discuss the tipping dynamics of a network of climate subsystems, driven by overshoot trajectories in global warming temperatures. We use a network model of eight interacting climate subsystems to model the dynamics of global tipping risks. In particular we treat each node as a Markov chain whose transition rates depend on internal factors (the time taken to collapse/recover), the level of global warming and the states of its neighbouring Markov chains. Moreover, we use a stylised overshoot model of global temperature, fitted to three emissions-based scenarios (SSP 1-1.9, SSP 5-3.4-OS and CurPol-OS), to drive the tipping dynamics, allowing us to vary different overshoot parameters (such as peak temperature and ramp down duration) one- or two-at-a-time. In this way, we construct a systematic assessment of overshoot trajectories to ascertain which overshoot characteristic most affects projected tipping risks, and under what values are said risks minimised.
Jacques' work broadly concerns dynamics on networks with several quite different applications including tipping risks on climate networks; games on dynamic networks; spatial social dilemmas of air pollution; biased elections and misinformation spread on social networks. His most recent focus is on social tipping within climate-behaviour contexts, such as the adoption of solar panels and plant-based diets. Methodologically he uses techniques from a broad range of fields including complex and dynamical systems, network science, (evolutionary) game theory. Jacques is currently a postdoc at the Computational Science Lab at the University of Amsterdam, and was previously at the University of Bonn (postdoc) and the University of Warwick (PhD).
If you wish to attend this seminar online, please send an email to b.v.meylahn@uva.nl to receive the zoom-link.