Abstract
Abstract. The impacts of representing cloud microphysical processes in a stochastic subcolumn framework are investigated, with emphasis on estimating the aerosol indirect effect. It is shown that subgrid treatment of cloud activation and autoconversion of cloud water to rain reduce the impact of anthropogenic aerosols on cloud properties and thus reduce the global mean aerosol indirect effect by 19%, from −1.59 to −1.28 W m−2. This difference is partly related to differences in the model basic state; in particular, the liquid water path (LWP) is smaller and the shortwave cloud radiative forcing weaker when autoconversion is computed separately for each subcolumn. However, when the model is retuned so that the differences in the basic state LWP and radiation balance are largely eliminated, the global-mean aerosol indirect effect is still 14% smaller (i.e. −1.37 W m−2) than for the model version without subgrid treatment of cloud activation and autoconversion. The results show the importance of considering subgrid variability in the treatment of autoconversion. Representation of several processes in a self-consistent subgrid framework is emphasized. This paper provides evidence that omitting subgrid variability in cloud microphysics contributes to the apparently chronic overestimation of the aerosol indirect effect by climate models, as compared to satellite-based estimates.
Highlights
Aerosol–cloud interactions and their changes due to anthropogenic aerosol emissions represent a major uncertainty in climate projections
We used the ECHAM5-HAM2 climate–aerosol model augmented with a stochastic subcolumn framework for cloud microphysics and radiation to study the aerosol indirect effects
Compared to a reference model configuration with general circulation models (GCMs) grid-scale cloud microphysics and uniform cloud droplet number concentration (CDNC) inside the GCM grid-cells, calculating cloud activation and autoconversion explicitly in the subcolumn space generally decreased the change in cloud properties between pre-industrial (PI) and present-day (PD) aerosol emission conditions
Summary
Aerosol–cloud interactions and their changes due to anthropogenic aerosol emissions represent a major uncertainty in climate projections. The cloudy subcolumns can be directly used in the radiation calculations by the use of the Monte Carlo Independent Column Approximation method (MCICA; Pincus et al, 2003) This is a significant advantage, as the entire chain of processes from formation of cloud droplets to radiative transfer can be considered consistently using the same subgrid framework. A series of climate model simulations using the modified model version from Tonttila et al (2013) is presented in this study, with focus on liquid phase stratiform clouds These simulations demonstrate directly that omitting subgrid variability in cloud microphysics contributes to the overestimation of model-based aerosol indirect effect.
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