Large simulated radiative effects of smoke in the south-east Atlantic

Hamish Gordon, Paul R. Field, Steven J. Abel, Ben T. Johnson, Mohit Dalvi, Daniel P. Grosvenor, Adrian A. Hill, Annette K. Miltenberger, Masaru Yoshioka, Ken S. Carslaw
2018 Atmospheric Chemistry and Physics Discussions  
<p><strong>Abstract.</strong> A 1200<span class="thinspace"></span>km-square 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 ten-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. We examine the interaction of the smoke with clouds and find it has substantial instantaneous
more » ... , indirect and semi-direct radiative effects, which vary in magnitude and sometimes sign between model configurations. <br><br> The region of interest is simulated at 4<span class="thinspace"></span>km resolution, with no parameterised convection scheme. The simulations are driven by, and compared to, the HadGEM global model, running at approximately 65<span class="thinspace"></span>km resolution. 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. <br><br> The smoke aerosol is simulated realistically, and is found to affect dynamical, microphysical and radiative properties of the atmosphere across the region. The model captures the large-scale horizontal transport of the aerosol adequately, approximately reproducing a transition from pristine to polluted conditions. However, for some of the simulation, the smoke is around 1<span class="thinspace"></span>km too low in altitude and therefore mixes into the clouds earlier than observed. Fire emissions increase the total aerosol burden by a factor 3.7 and cloud droplet number concentrations by a factor of 3, which is consistent with MODIS observations. Strong localised perturbations to heating and cooling rates due to the smoke affect the dynamics: in the regional model, the inversion height is reduced by up to 200<span class="thinspace"></span>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<span class="thinspace"></span>g<span class="thinspace"></span>m<sup>&amp;minus;2</sup> relative to a simulation without smoke aerosol, when averaged over the polluted period. This increase is mostly due to radiatively driven dynamical changes: the reduced entrainment of dry air from above the cloud layer, rather than precipitation suppression by aerosol. <br><br> The smoke has substantial direct radiative effects of +11.4<span class="thinspace"></span>W<span class="thinspace"></span>m<sup>&amp;minus;2</sup> in the regional model, when averaged over the polluted five days of our case study. The semi-direct radiative effect of the smoke, &amp;minus;30.5<span class="thinspace"></span>W<span class="thinspace"></span>m<sup>&amp;minus;2</sup>, is larger than the indirect radiative effect, &amp;minus;10.1<span class="thinspace"></span>W<span class="thinspace"></span>m<sup>&amp;minus;2</sup>. However, the radiative effects are sensitive to the model set-up: the semi-direct effect is smaller in the global model, and also in a simulation with the Kogan (2013) parameterisation of autoconversion and accretion instead of the default, from Khairoutdinov and Kogan (2002). Furthermore, we simulate a liquid water path that is biased high compared to satellite observations by 22<span class="thinspace"></span>% 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 &amp;minus;27.6<span class="thinspace"></span>W<span class="thinspace"></span>m<sup>&amp;minus;2</sup>.</p>
doi:10.5194/acp-2018-305 fatcat:phi5xktq4bdmben6wi3nwwap7y