Study of simulations using ECHAM-HAM and CAM5-MAM3 using ground-based and satellite data for Brazil

Thursday, 17 December 2015
Poster Hall (Moscone South)
Debora Souza Alvim Sr1, Paulo Nobre Nobre1, Silvio Nilo1, Sergio Machado Correa2, Jayant Pendharkar1, Vinicius Capistrano1, Ariane F Dos Santos1, Paulo yoshio Kubota1 and Josiane Silva1, (1)CPTEC Center for Weather Forecasts and Climate Research, Cachoeira Paulista, Brazil, (2)UERJ Rio de Janeiro State University, Resende, Brazil
Brazil is developing its own atmosphere-ocean-biosphere-cryosphere Global Circulation Model - the Brazilian Earth System Model (BESM). BESM simulations demonstrate potential results on global climate change. Brazilian climate modeling community can significantly contribute to the international efforts on global climate change research. Currently, the Center for Weather Forecasting and Climate Studies of the National Institute for Space Research (CPTEC/INPE), Brazil is implementing and testing the aerosol component in BESM. A priori knowledge of the overall performance of the existing state-of-the-art aerosol models is necessary for the implementation. This work analyzes the performance of the aerosol component, their distribution over Brazil in particular, of two Atmospheric General Circulation Models (AGCM), the European Centre‚Äôs Model - Hamburg Aerosol Model (ECHAM-HAM) and the Community Atmosphere Model - Modal Aerosol Model (CAM5-MAM3) against the observations. We evaluated the aerosol optical depth (AOD) from both the simulations and Angström exponent from ECHAM-HAM. The results are compared with Aerosol Robotic Network (AERONET) ground station measurements, and satellite observations from Moderate Resolution Imaging Spectroradiometer (MODIS). This study was done for four cities in Brazil - São Paulo, Cuiabá, Rio Branco, and Alta Floresta during 2001-2006. Both models underestimate AOD for all the four cities. However, CAM5-MAM3 has greater negative bias in the Northern and Northeastern regions of Brazil where biomass burning is more frequent during the dry season. Better performance is seen during January-June and November-December, but not consistent during July to October (i.e., the dry season), when fire occurrences are more frequent. CAM5-MAM3 model has small negative bias for this period. The Angström parameter is reasonably reproduced by ECHAM-HAM, except for Cuiabá, indicating that the particle size distribution is correctly represented in most cities.