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We introduce the Coupled Aerosol and Tracer Transport model to the Braziliandevelopments on the Regional Atmospheric Modeling System (CATT-BRAMS).CATT-BRAMS is an on-line transport model fully consistent with the simulatedatmospheric dynamics. Emission sources from biomass burning andurban-industrial-vehicular activities for trace gases and from biomassburning aerosol particles are obtained from several published datasets andremote sensing information. The tracer and aerosol mass concentrationprognostics include the effects of sub-grid scale turbulence in theplanetary boundary layer, convective transport by shallow and deep moistconvection, wet and dry deposition, and plume rise associated withvegetation fires in addition to the grid scale transport. The radiationparameterization takes into account the interaction between the simulatedbiomass burning aerosol particles and short and long wave radiation. Theatmospheric model BRAMS is based on the Regional Atmospheric Modeling System(RAMS), with several improvements associated with cumulus convectionrepresentation, soil moisture initialization and surface scheme tuned forthe tropics, among others. In this paper the CATT-BRAMS model is used tosimulate carbon monoxide and particulate material (PM<sub>2.5</sub>) surface fluxes andatmospheric transport during the 2002 LBA field campaigns, conducted duringthe transition from the dry to wet season in the southwest Amazon Basin.Model evaluation is addressed with comparisons between model results andnear surface, radiosondes and airborne measurements performed during thefield campaign, as well as remote sensing derived products. We show thematching of emissions strengths to observed carbon monoxide in the LBAcampaign. A relatively good comparison to the MOPITT data, in spite of thefact that MOPITT a priori assumptions imply several difficulties, is alsoobtained

atmospheric chemistry and physics

The Coupled Aerosol and Tracer Transport model to the Brazilian developments on the Regional Atmospheric Modeling System (CATT-BRAMS) – Part 1: Model description and evaluation