Abstract

Abstract. A 1200×1200 km2 area of the tropical South Atlantic Ocean near Ascension Island is studied with the HadGEM climate model at convection-permitting and global resolutions for a 10-day case study period in August 2016. During the simulation period, a plume of biomass burning smoke from Africa moves into the area and mixes into the clouds. At Ascension Island, this smoke episode was the strongest of the 2016 fire season.The region of interest is simulated at 4 km resolution, with no parameterised convection scheme. The simulations are driven by, and compared to, the global model. For the first time, the UK Chemistry and Aerosol model (UKCA) is included in a regional model with prognostic aerosol number concentrations advecting in from the global model at the boundaries of the region.Fire emissions increase the total aerosol burden by a factor of 3.7 and cloud droplet number concentrations by a factor of 3, which is consistent with MODIS observations. In the regional model, the inversion height is reduced by up to 200 m when smoke is included. The smoke also affects precipitation, to an extent which depends on the model microphysics. The microphysical and dynamical changes lead to an increase in liquid water path of 60 g m−2 relative to a simulation without smoke aerosol, when averaged over the polluted period. This increase is uncertain, and smaller in the global model. It is mostly due to radiatively driven dynamical changes rather than precipitation suppression by aerosol.Over the 5-day polluted period, the smoke has substantial direct radiative effects of +11.4 W m−2 in the regional model, a semi-direct effect of −30.5 W m−2 and an indirect effect of −10.1 W m−2. Our results show that the radiative effects are sensitive to the structure of the model (global versus regional) and the parameterization of rain autoconversion. Furthermore, we simulate a liquid water path that is biased high compared to satellite observations by 22 % on average, and this leads to high estimates of the domain-averaged aerosol direct effect and the effect of the aerosol on cloud albedo. With these caveats, we simulate a large net cooling across the region, of −27.6 W m−2.

Highlights

  • Marine boundary-layer clouds are a substantial source of uncertainty in climate models (Bony and Dufresne, 2005; Wood, 2012; Schneider et al, 2017)

  • The region in which biomass burning aerosol interacts with South Atlantic clouds is studied in the HadGEM climate model with prognostic aerosol number concentration from the UK Chemistry and Aerosol model (UKCA) aerosol microphysics module, in regional and global configurations

  • A square of length 1200 km centred near Ascension Island, resultant large radiative effects sum to −27.6 W m−2, in an especially strong smoke episode

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Summary

Introduction

Marine boundary-layer clouds are a substantial source of uncertainty in climate models (Bony and Dufresne, 2005; Wood, 2012; Schneider et al, 2017). 2, we introduce our ∼ 65 km resolution (N216) version of the global climate model with two-moment aerosol microphysics (prognostic mass and number concentrations) This model is used to drive a simulation of a roughly square domain of length approximately 1200 km (strictly 10.8◦ of latitude and longitude) surrounding Ascension Island with a grid spacing of 4 km, intended to allow us to turn off the convection parameterisation in the model. This is the first time prognostic aerosol number concentrations are included in a regional UM configuration with realistic meteorology, except for the idealised demonstration case study of (Planche et al, 2017). We highlight some areas where further work is needed in our conclusions

Model structure and spin-up
Aerosol emissions and transport
Cloud microphysics
Model tuning
Satellite retrievals
Smoke transport in the global model
Meteorology and dynamics
Aerosols: cloud condensation nuclei and optical depth
Cloud droplet number concentration and liquid water path
Precipitation
Effects of biomass burning aerosol on heating and temperature
Aug 1500
Model results
Comparison of cloud radiative effects with other studies
Findings
10 Conclusions
Full Text
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