The South AMerican Biomass Burning Analyses (SAMBBA) programme is a major international consortium programme. The programme has delivered a suite of ground, aircraft and satellite measurements of Amazonian Biomass Burning Aerosol during a field study that took place in September 2012. SAMBBA has used this data in a suite of analyses that aims to:
- improve our knowledge of BB emissions;
- challenge and improve the latest aerosol process models;
- challenge and improve satellite retrievals;
- test predictions of aerosol influences on regional climate and weather over Amazonia and the surrounding regions made using the next generation of climate and NWP models with extensive prognostic aerosol schemes; and
- assess the impact of .biomass burning on the Amazonian biosphere.
The main field experiment was based in Porto Velho, Brazil and investigated the dry season and onset of the wet season. The UK large research aircraft (FAAM) sampled aerosol chemical, physical and optical properties and gas phase precursor concentrations. Measurements of radiation were also made using advanced radiometers on board the aircraft and satellite data are also being used. The influences of biomass burning aerosols are highly significant at local, weather, seasonal, and climate temporal scales necessitating the use of a hierarchy of models to establish and test key processes and quantify impacts. The study is challenging models carrying detailed process descriptions of biomass burning aerosols with the new, comprehensive observations being made during SAMBBA to evaluate model performance and to improve parameterisations. Numerical Weather Prediction and Climate model simulations with a range of complexity and spatial resolution are being used to investigate the ways in which absorbing aerosol may influence dynamics and climate on regional and wider scales. At the heart of the approach is the use of a new range of models that can investigate such interactions using coupled descriptions of aerosols and clouds to fully investigate feedbacks at spatial scales that are sufficiently well resolved to assess such processes.