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Yerong Wu

Researcher at Chinese Academy of Sciences

Publications -  6
Citations -  460

Yerong Wu is an academic researcher from Chinese Academy of Sciences. The author has contributed to research in topics: Moderate-resolution imaging spectroradiometer & Aerosol. The author has an hindex of 6, co-authored 6 publications receiving 400 citations. Previous affiliations of Yerong Wu include Beijing Normal University & Delft University of Technology.

Papers
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Spatio-temporal variation trends of satellite-based aerosol optical depth in China during 1980-2008

TL;DR: In this article, the authors analyzed TOMS AOD at 500 nm (1980e2001), along with MODIS data (2000e2008) at 550 nm to investigate variations at one-degree grid over eight typical regions in China and the trends in AODs, temporally and spatially.
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Synergy of satellite and ground based observations in estimation of particulate matter in eastern China

TL;DR: A back-propagation artificial neural network (BP ANN) algorithm trained with bayesian regularization that benefited from the synergy of satellite- and ground-based observations was developed to estimate PM in eastern China and implied that the ANN algorithm basically reproduced the observed PM concentration.
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Three-dimensional structure of aerosol in China: A perspective from multi-satellite observations

TL;DR: In this article, a three-dimensional distribution of the frequency of occurrence (FoO) of aerosols over China was derived using eight years (2006-2014) of passive (MODIS/Aqua and OMI/Aura) and active (CALIOP/CALIPSO) satellite measurements.
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Satellite observed aerosol-induced variability in warm cloud properties under different meteorological conditions over eastern China

TL;DR: In this article, the authors studied aerosol indirect effect on summertime warm clouds over the Yangtze River Delta (YRD) and East China Sea (ECS) and found that the horizontal extension of cloud is prone to be driven by aerosol rather than meteorological conditions.
Journal Article

Estimation of PM2.5 over eastern China from MODIS aerosol optical depth using the back propagation neural network

TL;DR: Two years of AOD data from moderate resolution imaging spectroradiometer (MODIS) onboard Terra at five observational sites of China combined with five meteorological factors were used as important input to establish the Back Propagation (BP) neural networks model, which was applied to estimate PM2.5.