Articles | Volume 15, issue 2
Atmos. Chem. Phys., 15, 703–714, 2015
Atmos. Chem. Phys., 15, 703–714, 2015

Research article 19 Jan 2015

Research article | 19 Jan 2015

Explicit representation of subgrid variability in cloud microphysics yields weaker aerosol indirect effect in the ECHAM5-HAM2 climate model

J. Tonttila1,3, H. Järvinen3, and P. Räisänen2 J. Tonttila et al.
  • 1Finnish Meteorological Institute, Atmospheric Research Centre of Eastern Finland, P.O. Box 1627, 70211 Kuopio, Finland
  • 2Finnish Meteorological Institute, P.O. Box 503, 00101 Helsinki, Finland
  • 3Department of Physics, University of Helsinki, P.O. Box 64, 00014 Helsinki, Finland

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.

Final-revised paper