Debiasing deep uncertainties in climate change strategies
EUNICE develops new and integrated approaches to quantify the deep uncertainties associated with climate change hazards and low-carbon policies, advancing the foundations of computational modelling for effective climate solutions.
EUNICE combines computational and AI sciences to increase confidence in the quantification of climate uncertainties. It generates recommendations for robust decision-making amid profound uncertainty and mounting climate risks, arising from the interconnection of physical and socio-economic systems.
The three step-change approach of EUNICE
Construct
We apply computational and statistical methods for better capturing future climate risks and mitigation scenarios
Consolidate
We consolidate climate scenarios by identifying neat-future trends and risks and their consequences for long-term climate change
Convert
We convert computer-generated maps of the future into robust and actionable recommendations for policy actions