气候变化领域集成服务门户(CCPortal): Characterization of the radiative impact of aerosols on CO2 and energy fluxes in the Amazon deforestation arch using artificial neural networks

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DOI	10.5194/acp-20-3439-2020
	Characterization of the radiative impact of aerosols on CO2 and energy fluxes in the Amazon deforestation arch using artificial neural networks
	Kerches Braghiere R.; Akemi Yamasoe M.; Manuel Évora Do Rosário N.; Ribeiro Da Rocha H.; De Souza Nogueira J.; Carioca De Araújo A.
发表日期	2020
ISSN	1680-7316
起始页码	3439
结束页码	3458
卷号	20 期号:6
英文摘要	In vegetation canopies with complex architectures, diffuse solar radiation can enhance carbon assimilation through photosynthesis because isotropic light is able to reach deeper layers of the canopy. Although this effect has been studied in the past decade, the mechanisms and impacts of this enhancement over South America remain poorly understood. Over the Amazon deforestation arch large amounts of aerosols are released into the atmosphere due to biomass burning, which provides an ideal scenario for further investigation of this phenomenon in the presence of canopies with complex architecture. In this paper, the relation of aerosol optical depth and surface fluxes of mass and energy are evaluated over three study sites with artificial neural networks and radiative transfer modeling. Results indicate a significant effect of the aerosol on the flux of carbon dioxide between the vegetation and the atmosphere, as well as on energy exchange, including that surface fluxes are sensitive to second-order radiative impacts of aerosols on temperature, humidity, and friction velocity. CO2 exchanges increased in the presence of aerosol in up to 55 % in sites with complex canopy architecture. A decrease of approximately 12 % was observed for a site with shorter vegetation. Energy fluxes were negatively impacted by aerosols over all study sites.. © 2020 BMJ Publishing Group. All rights reserved.
语种	英语
scopus关键词	aerosol property; artificial neural network; atmospheric modeling; biomass burning; canopy architecture; carbon dioxide; carbon flux; complexity; deforestation; energy flux; optical depth; radiative transfer; South America
来源期刊	ATMOSPHERIC CHEMISTRY AND PHYSICS
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/247899
作者单位	Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Drive, Pasadena, CA 91109, United States; Joint Institute for Regional Earth System Science and Engineering, University of California at Los Angeles, Los Angeles, CA 90095, United States; Departamento de Ciências Atmosféricas, Instituto de Astronomia, Geofísica e Ciências Atmosféricas, Universidade de São Paulo, São Paulo, Brazil; Laboratório de Clima e Poluição Do Ar (LabClip), Instituto de Ciências Ambientais, Químicas e Farmacêuticas, Universidade Federal de São Paulo, Diadema, Brazil; Instituto de Física, Universidade Federal de Mato Grosso, Mato Grosso, Brazil; Embrapa Amazônia Oriental, Travessa Dr. Enéas Pinheiro, s/n, Marco, Caixa Postal 48, Belém, Pará, 66095-100, Brazil; Instituto Nacional de Pesquisas da Amazônia (INPA), Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA), Avenida André Araújo, 2936, Manaus, Amazonas, 69060-001, Brazil; NASA Jet Propulsion Laboratory, M/S 233-305F, 4800 Oak Grove Drive, Pa...
推荐引用方式 GB/T 7714	Kerches Braghiere R.,Akemi Yamasoe M.,Manuel Évora Do Rosário N.,et al. Characterization of the radiative impact of aerosols on CO2 and energy fluxes in the Amazon deforestation arch using artificial neural networks[J],2020,20(6).
APA	Kerches Braghiere R.,Akemi Yamasoe M.,Manuel Évora Do Rosário N.,Ribeiro Da Rocha H.,De Souza Nogueira J.,&Carioca De Araújo A..(2020).Characterization of the radiative impact of aerosols on CO2 and energy fluxes in the Amazon deforestation arch using artificial neural networks.ATMOSPHERIC CHEMISTRY AND PHYSICS,20(6).
MLA	Kerches Braghiere R.,et al."Characterization of the radiative impact of aerosols on CO2 and energy fluxes in the Amazon deforestation arch using artificial neural networks".ATMOSPHERIC CHEMISTRY AND PHYSICS 20.6(2020).