EUNICE – Debiasing the uncertainties of climate stabilization ensembles

Climate change strategies need to be resilient to disruptive scientific and political uncertainties. Mathematical models can help identify robust courses of action, but computational and epistemic constraints limit their predictive capacity. The EU-funded, ERC-Consolidator, EUNICE project aims to quantify and analyse uncertainties in the stabilisation pathways consistent with climate stabilisation. Researchers will use machine learning and simulations to explore a vast range of scenarios extending into the deep future. EUNICE will help identify robust strategies to reduce emissions and deal with abrupt climate change, reconciling long-term predictions with the fast-changing political and technological landscape of climate policy.