ECLAIR aimed to develop an innovative interdisciplinary model framework to refine the estimate of aerosol indirect effect (i.e. influence of atmospheric aerosol particles on cloud properties), which remains the single largest uncertainty in the current drivers of climate change. A major reason for this uncertainty is that current climate models are unable to resolve the spatial scales for aerosol-cloud interactions.
We proposed to resolve this scale problem by using statistical emulation to build computationally fast surrogate models (i.e. emulators) that can reproduce the effective output of a detailed high-resolution cloud-scale model. By incorporating these emulators into a state-of-the-science climate model, the aim was to, for the first time, achieve the accuracy of a limited-area high-resolution model on a global scale with negligible computational cost.
The main scientific outcome of the project was anticipated to be a highly refined and physically sound estimate of the aerosol indirect effect that enables more accurate projections of future climate change, and thus has high societal relevance. In addition, the work aimed at quantifying largest uncertainties in and improving the process-level understanding of aerosol-cloud interactions.
The key project objectives were achieved. The main breakthrough of the project was the development of the pioneering emulator-based approach in climate modelling. We expect this approach to open up completely new research opportunities also in other fields that deal with heterogeneous spatial scales. In addition, the project developed arguably the most detailed cloud-scale model in the world in terms of aerosol-cloud-precipitation interactions. With the help of this model, several aspects of process-level understanding have already been improved.
