Redirect Innovation to foster Positive tipping Points and prevent Lock-ins in the clean Energy transition.

The climate is approaching dangerous points of no return, yet national climate commitments are lagging. One, and possibly the only, way for a timely transition to a green economy is through positive tipping points, i.e. rapid, large and irreversible shifts towards clean energy technologies due to strategic interventions and momentum buildup above critical thresholds. The current generation of coupled climate-energy-economic models, which guide climate mitigation strategies, is highly inadequate to represent and leverage these shifts properly. Current models overestimate technological costs, underestimate feasibility concerns, and oversimplify the decision-making process.The RIPPLE project aims to challenge these limitations and advance the empirical and modelling foundations of positive tipping points. First, it explores how innovation and diffusion of key green technologies can drive costs down and enable a swift transition away from fossil fuels. Novel economic approaches are integrated into a climate-energy-economic model to comprehensively map the space of alternative non-linear transitions of key technologies and their interdependencies. Second, the project investigates material and financial feasibility concerns. It augments a climate-energy-economic model to study lock-ins due to scarcity of critical materials, insufficient funds and fragile international dependencies. Third, the project elaborates on new ways of identifying early signals of positive tipping and generating policies that respond to those signals. Interpretable machine learning is used to turn noisy techno-economic data into actionable green energy tipping interventions, while exploratory modelling highlights the trade-offs between costs, speed, feasibility, fairness and robustness to uncertainties. The ultimate outcome is the first quantitative integrated framework to understand how to redirect innovation for the green economy to tip before the climate does.