ECLAIR project - European Research Council Consolidator Grant

Emulation of subgrid-scale aerosol-cloud interactions in climate models: towards a realistic representation of aerosol indirect effect.

The challenge

ECLAIR aims to develop an innovative interdisciplinary model framework to refine the estimate of aerosol indirect effect, 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 plan to resolve this scale problem by using statistical emulation to build computationally fast surrogate models that can reproduce the effective output of a detailed high-resolution cloud-resolving model.


The scientific objectives of the project are to: 1) construct a framework in which aerosol-cloud interactions within climate model grid cells can be described with fast statistical surrogates of high accuracy cloud-scale models; 2) quantify how the uncertainties related to atmospheric aerosols propagate to our predictions of aerosol indirect effects; and 3) to obtain a refined estimate of the aerosol indirect forcing in present day and future conditions.

Expected outcomes

The main scientific outcome of the project will 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 developed surrogate models will help to quantify how the remaining uncertainties in aerosol properties impact predictions of aerosol indirect effect. This information will be used, together with extensive measurement data from our collaborators, to improve the process level-understanding of aerosol-cloud interactions. The comprehensive uncertainty analyses performed will be highly valuable for future research efforts as they point to processes and interactions that most urgently need to be experimentally constrained. Furthermore, the pioneering framework developed can open up new research opportunities also in other fields that deal with heterogeneous spatial scales.

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