航空网
气溶胶
组分(热力学)
环境科学
抓住
气象学
价值(数学)
大气科学
计算机科学
地理
数学
地质学
物理
统计
热力学
程序设计语言
作者
Xindan Zhang,Lei Li,Huizheng Che,Oleg Dubovik,Yevgeny Derimian,Brent Holben,Pawan Gupta,T. F. Eck,Elena Lind,Carlos Toledano,Xiangao Xia,Yu Zheng,Ke Gui,Xiaoye Zhang
标识
DOI:10.1175/bams-d-23-0260.1
摘要
Abstract Aerosols affect Earth’s climate both directly and indirectly, which is the largest uncertainty in the assessment of radiative forcings affecting anthropogenic climate change. The standard Aerosol Robotic Network (AERONET) aerosol products have been widely used for more than 30 years. Currently, there is strong community interest in the possibility of determining aerosol composition directly from remote sensing observations. This work presents the results of applying such a recently developed approach by Li et al. to extended datasets of the directional sky radiances and spectral aerosol optical depth (AOD) measured by AERONET for the retrievals of aerosol components. First, the validation of aerosol optical properties retrieved by this component approach with AERONET standard products shows good agreement. Then, spatiotemporal variations of the obtained aerosol component concentration are characterized globally, especially the absorbing aerosol species (black carbon, brown carbon, and iron oxides) and scattering aerosol species (organic carbon, quartz, and inorganic salts). Finally, we compared the black carbon (BC) and dust column concentration retrievals to the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), products in several regions of interest (Amazon zone, Indo-China Peninsula, North India, southern Africa, sub-Sahel, Gobi Desert, Middle East, Sahara Desert, and Taklamakan Desert) for new insights on the quantitative assessment of MERRA-2 aerosol composition products ( R = 0.60–0.85 for BC; R = 0.75–0.90 for dust). The new value-added and long-term aerosol composition product globally is available online ( https://doi.org/10.6084/m9.figshare.25415239.v1 ), which provides important measurements for the improvement and optimization of aerosol modeling to enhance estimation of the aerosol radiative forcing.
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