Quantifying Sources of Inter-model Diversity in the Aerosol First Indirect Effect

Abstract:

Aerosol presents a large source of uncertainty in estimates of climate sensitivity. It is important to gauge model performance in simulating aerosol processes, and which aspects of aerosol-climate interaction contribute to uncertainty, to enable effort to be prioritized. Recent studies have shown that the total aerosol radiative forcing is dominated by aerosol-cloud interactions. Uncertainty in aerosol-cloud interactions is the largest uncertainty in the radiative forcing of climate, and estimates of the radiative forcing depend on several aspects of the climate that are currently not well modelled.

We show that there is a wide range of natural and anthropogenic aerosol loads across CMIP5 models. Even when models are driven with the same emissions there is large diversity in global sulphate load, and in its spatial distribution. Inter-model diversity in parameters that depend on aerosol is even greater: estimates of global mean cloud droplet radius, a metric for aerosol-cloud interactions, span over an order of magnitude.

A simple model of aerosol-cloud interactions has been developed for a subset of CMIP5 models. This model is used to rank sources of inter-model diversity in estimates of magnitude of the cloud albedo effect. We show that different parameterisations of aerosol-cloud interactions are the main cause of inter-model diversity. Uncertainty in pre-industrial sulphate load also makes a substantial contribution, with smaller influences from inter-model differences in the change in sulphate load during the industrial era, and from differences in cloud fraction.