It is through the effective use and combination of climate science and impacts science, and the models used by each community, that we have been able to quantify uncertainty, assess risk, and thus equip society to deal with climate change. EQUIP has brought together the UK climate modelling, statistical modelling, and impacts communities to work closely together for the first time on quantifying uncertainty and developing risk-based prediction for decision making. Through quantifying uncertainty more systematically across climate and impacts, and through working with users, EQUIP has led to improved utility from ensemble climate simulation and climate science. We have conducted integrated analyses of the cascade of uncertainty from climate to impacts for a range of sectors, principally crops, marine ecosystems, water management and heat related mortality due to heat waves and droughts. This is significantly different from tagging impacts models onto climate models, since it implies analysis of sources of uncertainty and use of the resulting information to find better ways of quantifying uncertainty in predictions of climate impacts for decision makers.
The project has resulted in advances in methodology that will enable more systematic quantification of uncertainty and hence more confident statements about climate, climate change, and its impacts. Specific foci included assessment of the information content of climate model projections, combination of climate models and data-driven models to support decisions, and evaluation of the quality of climate and impacts predictions.
These advances came from both targets that were achievable with a relatively small amount of effort – such as improved analysis of uncertainty in impacts – and objectives that built capacity in the longer term, such as growing a collaborative community of scientists and furthering our understanding of the cascade of uncertainty from climate to impacts.
We have achieved our specific objectives through seven interacting workpackages, which you can explore using the Research links on the left.
The project has: