A GCM investigation of impact of aerosols on the precipitation in Amazon during the dry to wet transition
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The climatic effects of aerosols on the precipitation over the Amazon during the dry to wet transition period have been investigated using an atmospheric general circulation model, NCEP/AGCM, and the aerosol climatology data. We found increased instability during the dry season and delayed wet season onset with aerosols included in the model simulation, leading to the delay of the maximum precipitation over the Amazon by about half a month. In particular, our GCM simulations show that surface solar flux is reduced in the Amazon due to the absorption and scattering of the solar radiation by aerosols, leading to decreased surface temperature. Reduced surface solar flux is balanced by decreases in both surface sensible heat and latent heat fluxes. During the wet season, the subtropical system over the Amazon has a shallower convection. With the inclusion of aerosols in the simulation, precipitation in the rainy season over the Amazon decreases in the major rainfall band, which partially corrects the overestimate of the simulated precipitation in that region. The reduced surface temperature by aerosols is also coupled with a warming in the middle troposphere, leading to increased atmosphere stability and moisture divergence over the Amazon. However, during the dry season when the convective system is stronger over the Amazon, rainfall increases in that region due to the warming of the air over the upper troposphere produced by biomass burning aerosols, which produces an anomalous upward motion and a convergence of moisture flux over the Amazon and draws the moisture and precipitation further inland. Therefore, aerosol effects on precipitation depend on the large-scale atmospheric stability, resulting in their different roles over the Amazon during the dry and wet seasons.
KeywordsOutgoing Longwave Radiation Atmospheric General Circulation Model Simulated Precipitation Aerosol Effect Surface Solar Radiation
The authors appreciate the funding support by the GoAmazon project Award Number DE-SC0011117, NASA ROSES14-ACMAP programs, and NSF Grants AGS-1419526. Author J.H.J. also acknowledge the support from the NASA-sponsored Jet Propulsion Laboratory, California Institute of Technology.
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