Articles | Volume 16, issue 22
Atmos. Chem. Phys., 16, 14657–14685, 2016

Special issue: South AMerican Biomass Burning Analysis (SAMBBA)

Atmos. Chem. Phys., 16, 14657–14685, 2016

Research article 24 Nov 2016

Research article | 24 Nov 2016

Evaluation of biomass burning aerosols in the HadGEM3 climate model with observations from the SAMBBA field campaign

Ben T. Johnson1, James M. Haywood1,2, Justin M. Langridge1, Eoghan Darbyshire3, William T. Morgan3, Kate Szpek1, Jennifer K. Brooke1, Franco Marenco1, Hugh Coe3, Paulo Artaxo4, Karla M. Longo5,a, Jane P. Mulcahy1, Graham W. Mann6, Mohit Dalvi1, and Nicolas Bellouin7 Ben T. Johnson et al.
  • 1Met Office, Exeter, UK
  • 2CEMPS, University of Exeter, Exeter, UK
  • 3Centre for Atmospheric Science, University of Manchester, Manchester, UK
  • 4Physics Institute, University of São Paulo, São Paulo, Brazil
  • 5National Institute for Space Research (INPE), São José dos Campos, Brazil
  • 6National Centre for Atmospheric Science, School of Earth and Environment, University of Leeds, Leeds, UK
  • 7Department of Meteorology, University of Reading, Reading, UK
  • anow at: NASA Goddard Space Flight Center and USRA/GESTAR, Greenbelt, MD, USA

Abstract. We present observations of biomass burning aerosol from the South American Biomass Burning Analysis (SAMBBA) and other measurement campaigns, and use these to evaluate the representation of biomass burning aerosol properties and processes in a state-of-the-art climate model. The evaluation includes detailed comparisons with aircraft and ground data, along with remote sensing observations from MODIS and AERONET. We demonstrate several improvements to aerosol properties following the implementation of the Global Model for Aerosol Processes (GLOMAP-mode) modal aerosol scheme in the HadGEM3 climate model. This predicts the particle size distribution, composition, and optical properties, giving increased accuracy in the representation of aerosol properties and physical–chemical processes over the Coupled Large-scale Aerosol Scheme for Simulations in Climate Models (CLASSIC) bulk aerosol scheme previously used in HadGEM2. Although both models give similar regional distributions of carbonaceous aerosol mass and aerosol optical depth (AOD), GLOMAP-mode is better able to capture the observed size distribution, single scattering albedo, and Ångström exponent across different tropical biomass burning source regions. Both aerosol schemes overestimate the uptake of water compared to recent observations, CLASSIC more so than GLOMAP-mode, leading to a likely overestimation of aerosol scattering, AOD, and single scattering albedo at high relative humidity. Observed aerosol vertical distributions were well captured when biomass burning aerosol emissions were injected uniformly from the surface to 3 km. Finally, good agreement between observed and modelled AOD was gained only after scaling up GFED3 emissions by a factor of 1.6 for CLASSIC and 2.0 for GLOMAP-mode. We attribute this difference in scaling factor mainly to different assumptions for the water uptake and growth of aerosol mass during ageing via oxidation and condensation of organics. We also note that similar agreement with observed AOD could have been achieved with lower scaling factors if the ratio of organic carbon to primary organic matter was increased in the models toward the upper range of observed values. Improved knowledge from measurements is required to reduce uncertainties in emission ratios for black carbon and organic carbon, and the ratio of organic carbon to primary organic matter for primary emissions from biomass burning.

Short summary
Biomass burning is a large source of carbonaceous aerosols, which scatter and absorb solar radiation, and modify cloud properties. We evaluate the simulation of biomass burning aerosol processes and properties in the HadGEM3 climate model using observations, including those from the South American Biomass Burning Analysis. We find that modelled aerosol optical depths are underestimated unless aerosol emissions (Global Fire Emission Database v3) are increased by a factor of 1.6–2.0.
Final-revised paper