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Volume 17, issue 19 | Copyright
Atmos. Chem. Phys., 17, 12145-12175, 2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 12 Oct 2017

Research article | 12 Oct 2017

Uncertainty from the choice of microphysics scheme in convection-permitting models significantly exceeds aerosol effects

Bethan White1, Edward Gryspeerdt2, Philip Stier1, Hugh Morrison3, Gregory Thompson3, and Zak Kipling4 Bethan White et al.
  • 1Atmospheric, Oceanic and Planetary Physics, University of Oxford, Oxford, UK
  • 2Institute for Meteorology, Universität Leipzig, Leipzig, Germany
  • 3National Center for Atmospheric Research, Boulder, Colorado, USA
  • 4European Centre for Medium-Range Weather Forecasts, Shinfield Park, Reading, UK

Abstract. This study investigates the hydrometeor development and response to cloud droplet number concentration (CDNC) perturbations in convection-permitting model configurations. We present results from a real-data simulation of deep convection in the Congo basin, an idealised supercell case, and a warm-rain large-eddy simulation (LES). In each case we compare two frequently used double-moment bulk microphysics schemes and investigate the response to CDNC perturbations. We find that the variability among the two schemes, including the response to aerosol, differs widely between these cases. In all cases, differences in the simulated cloud morphology and precipitation are found to be significantly greater between the microphysics schemes than due to CDNC perturbations within each scheme. Further, we show that the response of the hydrometeors to CDNC perturbations differs strongly not only between microphysics schemes, but the inter-scheme variability also differs between cases of convection. Sensitivity tests show that the representation of autoconversion is the dominant factor that drives differences in rain production between the microphysics schemes in the idealised precipitating shallow cumulus case and in a subregion of the Congo basin simulations dominated by liquid-phase processes. In this region, rain mass is also shown to be relatively insensitive to the radiative effects of an overlying layer of ice-phase cloud. The conversion of cloud ice to snow is the process responsible for differences in cold cloud bias between the schemes in the Congo. In the idealised supercell case, thermodynamic impacts on the storm system using different microphysics parameterisations can equal those due to aerosol effects. These results highlight the large uncertainty in cloud and precipitation responses to aerosol in convection-permitting simulations and have important implications not only for process studies of aerosol–convection interaction, but also for global modelling studies of aerosol indirect effects. These results indicate the continuing need for tighter observational constraints of cloud processes and response to aerosol in a range of meteorological regimes.

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Short summary
Aerosols influence cloud and precipitation by modifying cloud droplet number concentrations (CDNCs). We simulate three different types of convective cloud using two different cloud microphysics parameterisations. The simulated cloud and precipitation depends much more strongly on the choice of microphysics scheme than on CDNC. The uncertainty differs between types of convection. Our results highlight a large uncertainty in cloud and precipitation responses to aerosol in current models.
Aerosols influence cloud and precipitation by modifying cloud droplet number concentrations...