Concern and anticipation of future sea-level rise increase potential for social tipping interventions

Effective climate change mitigation necessitates swift societal transformations in order to meet the goals of the Paris Accord and to prevent abrupt, irreversible, transitions in the Earth System. Social tipping processes, where relatively small groups trigger sudden qualitative shifts in collective behaviour have been identified as a potential key mechanism instigating these necessary transformations.  However, the specific processes whereby experienced or anticipated future climate impacts effect large-scale societal changes remain largely unidentified and underrepresented in contemporary Earth System models. Here, we combine output from the MAGICC climate model, country-level social survey data and a low-dimensional network-based threshold model of social tipping to exemplify a transformative pathway in which climate change concern increases the potential for social tipping and extended anticipatory time horizons of future sea level rise shift the system closer towards a critical state whereby interventions, such as emergent social movements or policy change, can ultimately kick the system into a qualitatively different state. While dynamics of climate tipping elements are often reduced to a single control parameter, our findings suggest that such an approach may be inapplicable for social tipping processes, as single parameters alone may not reach critical thresholds required for tipping. Instead, we show that comparatively smaller changes in a set of multiple parameters can suffice to shift a system into its critical state where ephemeral (potentially deliberate) kicks can bring about social tipping. Tipping in the climate system is commonly associated with bifurcations, while social tipping processes are instead more likely induced by sudden events or shocks, where the required magnitudes of such kicks emerge from multiplicative, interacting factors. Effective analyses of such processes therefore requires novel modeling paradigms, specifically accounting for the increased complexity of socio-economic systems.