Can models robustly represent aerosol–convection interactions if their cloud microphysics is uncertain?
|Title:||Can models robustly represent aerosol–convection interactions if their cloud microphysics is uncertain?|
|Item Type:||Working Paper|
|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. In the Congo basin simulations both microphysics schemes have large positive biases in surface precipitation, frequency of high radar reflectivities and frequency of cold cloud compared to observations. 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 strongly differs not just between microphysics schemes but also between different 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 sub-region 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. 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 just for modelling studies of aerosol–convection interaction. These results indicate the continuing need for tighter observational constraints of cloud processes and response to aerosol in a range of meteorological regimes.|
|Copyright Statement:||© Author(s) 2017. This work is distributed under the Creative Commons Attribution 3.0 License.|
|Keywords:||Meteorology & Atmospheric Sciences|
|Open Access location:||https://doi.org/10.5194/acp-17-12145-2017|
|Appears in Collections:||Space and Atmospheric Physics|