Project description DEENESFRITPL Robust climate mitigation strategies against disruptive uncertainties 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 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. Show the project objective Hide the project objective Objective Mathematical models have become central tools in global environmental assessments. To serve society well, climate change stabilization assessments need to capture the uncertainties of the deep future, be statistically sound and track near-term disruptions. Up to now, conceptual, computational and data constraints have limited the quantification of uncertainties of climate stabilization pathways to a narrow set, focused on the current century. The statistical interpretation of scenarios generated by multi-model ensembles is problematic due to availability biases and model dependencies. Scenario plausibility assessments are scant. Simplified, single-objective decision criteria frameworks are used to translate decarbonization uncertainties into decision rules whose understanding is not validated.EUNICE aims to transform the methodological and experimental foundations of model-based climate assessments through quantification and debiasing of uncertainties in climate stabilization pathways. Our approach is threefold: construct, consolidate and convert. We first apply simulation and statistical methods for extending scenarios into the deep future (beyond the current century and status quo), quantifying and attributing deep uncertainties. We consolidate model ensembles through machine learning and human ingenuity to eliminate statistical biases, pin down near-term correlates of long-term targets, and identify early signals of scenario plausibility through prediction polls. Finally, we use decision-theoretic methods to convert model-generated maps of the future into resilient recommendations and experimentally test how to communicate them effectively. By advancing the state of the art in mathematical modelling, statistics, and behavioural decision-making, we strengthen the scientific basis of climate assessments, such as those of the IPCC. The approach and insights of EUNICE can be applied to other high-stakes environmental, social and technological evaluations. Fields of science natural sciencesearth and related environmental sciencesatmospheric sciencesclimatologyclimatic changesnatural sciencescomputer and information sciencesartificial intelligencemachine learningnatural sciencesmathematicsapplied mathematicsmathematical model Programme(s) HORIZON.1.1 - European Research Council (ERC) Main Programme Topic(s) ERC-2021-COG - ERC CONSOLIDATOR GRANTS Call for proposal ERC-2021-COG See other projects for this call Funding Scheme HORIZON-AG - HORIZON Action Grant Budget-Based Coordinator POLITECNICO DI MILANO Net EU contribution € 1 730 000,00 Address Piazza leonardo da vinci 32 20133 Milano Italy See on map Region Nord-Ovest Lombardia Milano Activity type Higher or Secondary Education Establishments Links Contact the organisation Opens in new window Website Opens in new window Participation in EU R&I programmes Opens in new window HORIZON collaboration network Opens in new window Other funding € 0,00 Participants (1) Sort alphabetically Sort by Net EU contribution Expand all Collapse all Third-party Legal entity other than a subcontractor which is affiliated or legally linked to a participant. The entity carries out work under the conditions laid down in the Grant Agreement, supplies goods or provides services for the action, but did not sign the Grant Agreement. A third party abides by the rules applicable to its related participant under the Grant Agreement with regard to eligibility of costs and control of expenditure. FONDAZIONE CENTRO EURO-MEDITERRANEOSUI CAMBIAMENTI CLIMATICI Italy Net EU contribution € 265 000,00 Address Via marco biagi 5 73100 Lecce See on map Region Sud Puglia Lecce Activity type Research Organisations Links Contact the organisation Opens in new window Website Opens in new window Participation in EU R&I programmes Opens in new window HORIZON collaboration network Opens in new window Other funding € 0,00
