scholarly journals Improved retrievals of aerosol optical depth and fine mode fraction from GOCI geostationary satellite data using machine learning over East Asia

2022 ◽  
Vol 183 ◽  
pp. 253-268
Author(s):  
Yoojin Kang ◽  
Miae Kim ◽  
Eunjin Kang ◽  
Dongjin Cho ◽  
Jungho Im
Keyword(s):  
Machine Learning ◽  
East Asia ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Satellite Data ◽  
Geostationary Satellite ◽  
Fine Mode

scholarly journals Synergistic Retrieval of Multitemporal Aerosol Optical Depth Over North China Plain Using Geostationary Satellite Data of Himawari-8

2018 ◽  
Vol 123 (10) ◽  
pp. 5525-5537 ◽  
Author(s):  
Shuaiyi Shi ◽  
Tianhai Cheng ◽  
Xingfa Gu ◽  
Husi Letu ◽  
Hong Guo ◽  
...  
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Satellite Data ◽  
North China Plain ◽  
North China ◽  
Geostationary Satellite

Joint Retrieval of Aerosol Optical Depth and Surface Reflectance Over Land Using Geostationary Satellite Data

2019 ◽  
Vol 57 (3) ◽  
pp. 1489-1501 ◽  
Author(s):  
Lu She ◽  
Yong Xue ◽  
Xihua Yang ◽  
John Leys ◽  
Jie Guang ◽  
...  
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Satellite Data ◽  
Geostationary Satellite ◽  
Surface Reflectance ◽  
Land Using

Retrieval of Aerosol Optical Depth Over Land Using Fy-4Aagri Geostationary Satellite Data

2021 ◽  
Author(s):  
Xingxing Jiang ◽  
Yong Xue ◽  
Chunlin Jin ◽  
Rui Bai ◽  
Na Li ◽  
...  
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Satellite Data ◽  
Geostationary Satellite ◽  
Land Using

scholarly journals Icing Detection over East Asia from Geostationary Satellite Data Using Machine Learning Approaches

2018 ◽  
Vol 10 (4) ◽  
pp. 631 ◽  
Author(s):  
Seongmun Sim ◽  
Jungho Im ◽  
Sumin Park ◽  
Haemi Park ◽  
Myoung Ahn ◽  
...  
Keyword(s):  
Machine Learning ◽  
East Asia ◽  
Satellite Data ◽  
Geostationary Satellite ◽  
Learning Approaches

scholarly journals Aerosol optical depth and fine-mode fraction retrieval over East Asia using multi-angular total and polarized remote sensing

2012 ◽  
Vol 5 (3) ◽  
pp. 501-516 ◽  
Author(s):  
T. Cheng ◽  
X. Gu ◽  
D. Xie ◽  
Z. Li ◽  
T. Yu ◽  
...  
Keyword(s):  
East Asia ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Lookup Table ◽  
Retrieval Algorithm ◽  
Spatial And Temporal Variability ◽  
Aerosol Retrieval ◽  
Fine Mode ◽  
Sun Photometer ◽  
The Impact

Abstract. A new aerosol retrieval algorithm using multi-angular total and polarized measurements is presented. The algorithm retrieves aerosol optical depth (AOD), fine-mode fraction (FMF) for studying the impact of aerosol on climate change. The retrieval algorithm is based on a lookup table (LUT) method, which assumes that one fine and one coarse lognormal aerosol modes can be combined with proper weightings to represent the ambient aerosol properties. To reduce the ambiguity in retrieval algorithm, the key characteristics of aerosol model over East Asia are constrained using the cluster analysis technique based on the AERONET sun-photometer observation over East Asia, and the fine and coarse modes are not fixed but can vary. A mixing model of bare soil and green vegetation spectra and the Nadal and Breon model for the bidirectional polarized reflectance factor (BPDF) were used to simulate total and polarized surface reflectance of East Asia. By applying the present algorithm to POLDER measurements, three different aerosol cases of clear, polluted and dust are analyzed to test the algorithm. The comparison of retrieved aerosol optical depth (AOD) and fine-mode fraction (FMF) with those of AERONET sun-photometer observations show reliable results. Preliminary validation is encouraging. Using the new aerosol retrieval algorithm for multi-angular total and polarized measurements, the spatial and temporal variability of anthropogenic aerosol optical properties over East Asia, which were observed during a heavy polluted event, were analyzed. Exceptionally high values of aerosol optical depth contributed by fine mode of up to 0.5 (at 0.865 μm), and high values of fine-mode fraction of up to 0.9, were observed in this case study.

scholarly journals Aerosol optical depth and fine-mode fraction retrieval over East Asia using multi-angular total and polarized remote sensing

2011 ◽  
Vol 4 (5) ◽  
pp. 5689-5716
Author(s):  
T. Cheng ◽  
X. Gu ◽  
D. Xie ◽  
Z. Li ◽  
T. Yu ◽  
...  
Keyword(s):  
East Asia ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Lookup Table ◽  
Retrieval Algorithm ◽  
Spatial And Temporal Variability ◽  
Aerosol Retrieval ◽  
Fine Mode ◽  
Sun Photometer ◽  
The Impact

Abstract. A new aerosol retrieval algorithm using multi-angular total and polarized measurements is presented. The algorithm retrieves aerosol optical depth (AOD), fine-mode fraction (FMF) for studying the impact of aerosol on climate change. The retrieval algorithm is based on a lookup table (LUT) method, which assumes that one fine and one coarse lognormal aerosol modes can be combined with proper weightings to represent the ambient aerosol properties. To reduce the ambiguity in retrieval algorithm, the key characteristics of aerosol model over East Asia are constrained using the cluster analysis technique based on the AERONET sun-photometer observation over East Asia. A mixing model of bare soil and green vegetation spectra and the Nadal and Breon model for the bidirectional polarized reflectance factor (BPDF) were used to simulate total and polarized surface reflectance of East Asia. By applying the present algorithm to POLDER measurements, three different aerosol cases of clear, polluted and dust are analyzed to test the algorithm. The comparison of retrieved aerosol optical depth (AOD) and fine-mode fraction (FMF) with those of AERONET sun-photometer observations show reliable results. Preliminary validation is encouraging. Using the new aerosol retrieval algorithm for multi-angular total and polarized measurements, the spatial and temporal variability of anthropogenic aerosol optical properties over East Asia, which were observed during a heavy polluted event, were analyzed. Exceptionally high values of aerosol optical depth contributed by fine mode of up to 0.5 (at 0.865 μm), and high values of fine-mode fraction of up to 0.9, were observed in this case study.

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