Charactering biomass burning aerosol in the Weather Research and Forecasting model with Chemistry (WRF-Chem), with evaluation against SAMBBA flight data.

Abstract:

The burning of forests in the Amazonia region is a globally significant source of carbonaceous aerosol, containing both absorbing and scattering components. Biomass burning aerosol (BBA) are efficient CCN, modifying cloud properties and influencing atmospheric circulation and precipitation tendencies. The impacts of BBA are highly dependent on their size distribution and composition. Studies in this region can therefore benefit greatly from the use of state-of-the-art sectional aerosol representations.

A bottom-up fire emissions inventory, 3BEM, has been developed by Longo et al.¹. It uses satellite products to identify fire locations, applying the emissions factors of Andrei and Merlot³ to generate daily emission maps. Flaming emissions are very buoyant, and a method for injecting emissions at altitude is needed to accurately describe the vertical profile of BBA. A parameterisation has been developed to simulate this sub-grid process⁴, and previously implemented in WRF-Chem using a modal aerosol scheme⁵. For this work we have modified the WRF-Chem model to simulate 3BEM emissions using the MOSAIC sectional aerosol scheme⁶.

This modified version of WRF-Chem v3.4.1 has been run for September 2012 over South America (25km grid-spacing). We will present model results evaluating the modelled aerosol vertical distribution, size distribution, composition and optical properties against measurements taken by the FAAM BAe-146 research aircraft during the SAMBBA field campaign. The plume-rise parameterisation was found to inject flaming emissions too high over most fires, resulting in high modelled aerosol loadings at high altitude. We probed the behaviour of the parameterisation by developing a new SAMBBA-tuned 3BEM emissions scenario, which uses more realistic estimates of fire size. Results from high-resolution (5 and 1km) nested simulations will also be presented, in order to evaluate the impacts of explicit aerosol-cloud interactions in non-parameterised clouds. 

1. K. Longo et al., 2010, Atmos. Chem. Phys., 10, 5785-5795.

2. M. O. Andreae and P. Merlot, 2001, Global Biogeochem. Cy., 15(4), 955-966.

3. S. Freitas et al., 2007, Atmos. Chem. Phys., 7, 3385-3398.

4. G. Grell et al., 2011, Atmos. Chem. Phys., 11, 5289-5303.

5. R. Zavari et al., 2008, J. Geophys. Res., 113, D132024.