Constraining the climate-scale impact of aerosols on cloud droplet number concentrations

The aim of this project is to understand and constrain the sensitivity of cloud droplet number concentrations to changes in aerosols on a climate scale - often referred to as ACINd - as this relation is fundamental for many aerosol effects on clouds and climate.

Previous estimates of ACINd from in-situ observations, satellite data and Earth System Models (ESMs) differ substantially, but the main reasons for the discrepancies are unclear; whether they are mostly due to inadequacies in the model parameterizations or if uncertainties associated with the different observational methods play a crucial role.

We will develop a novel framework to systematically compare estimates of ACINd on a range of temporal and spatial scales using a variety of methods.

Firstly, we will apply a clustering algorithm to group the observational data based on meteorological conditions and aerosol properties.

Thereafter, we will use large-eddy simulation (LES) to identify and explore the drivers of variability in the observed ACINd values, and to scrutinize potential issues with the commonly used methods.

Finally, we will use LES to investigate how small-scale variability in meteorological variables affect ESM estimates of ACINd, and improve the representation of processes relevant for ACINd in an ESM.

The project will result in more reliable estimates of the aerosol effect on cloud droplet number concentrations and a methodological framework to further explore aerosol effects on clouds and climate.