Aerosols over East and South Asia: Type Identification, Optical Properties, and Implications for Radiative Forcing
Identification of aerosol types has long been a difficult problem over East and South Asia due to various limitations. In this study, we use 2-dimensional (2-D) and multi-dimensional Mahalanobis distance (MD) clustering algorithms to identify aerosol characteristics based on the data from the Aeroso...
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ftmdpi:oai:mdpi.com:/2072-4292/14/9/2058/ 2023-08-20T03:59:13+02:00 Aerosols over East and South Asia: Type Identification, Optical Properties, and Implications for Radiative Forcing Yushan Liu Bingqi Yi agris 2022-04-25 application/pdf https://doi.org/10.3390/rs14092058 EN eng Multidisciplinary Digital Publishing Institute Atmospheric Remote Sensing https://dx.doi.org/10.3390/rs14092058 https://creativecommons.org/licenses/by/4.0/ Remote Sensing; Volume 14; Issue 9; Pages: 2058 aerosol classification 2-dimensional clustering Mahalanobis distance hierarchical clustering radiative forcing Text 2022 ftmdpi https://doi.org/10.3390/rs14092058 2023-08-01T04:52:00Z Identification of aerosol types has long been a difficult problem over East and South Asia due to various limitations. In this study, we use 2-dimensional (2-D) and multi-dimensional Mahalanobis distance (MD) clustering algorithms to identify aerosol characteristics based on the data from the Aerosol Robotic Network from March 1998 to February 2018 over the South and East Asian region (10°N~50°N, 70°E~135°E). The single scattering albedo (SSA), absorption Angstrom exponent (AAE), extinction Angstrom exponent (EAE), real index of refraction (RRI), and imaginary index of refraction (IRI) are utilized for classification of aerosols. Sub-regions with similar background conditions over East and South Asia are identified by hierarchical clustering algorithm to illustrate distinctive meteorological states in different areas. The East and South Asian aerosols are found to have distinct regional and seasonal features relating to the meteorological conditions, land cover, and industrial infrastructure. It is found that the proportions of dust aerosol are the highest in spring at the SACOL site and in summer at the sites near the Northern Indo-Gangetic Plain area. In spring, biomass-burning aerosols are dominant over the central Indo-China Peninsula area. The aerosol characteristics at coastal sites are also analyzed and compared with previous results. The 2-D clustering method is useful when limited aerosol parameters are available, but the results are highly dependent on the sets of parameters used for identification. Comparatively, the MD method, which considers multiple aerosol parameters, could provide more comprehensive classification of aerosol types. It is estimated that only about 50% of the data samples that are identifiable by the MD method could be classified by the 2-D methods, and a lot of undetermined data samples could be mis-classified by the 2-D methods. The aerosol radiative forcing (ARF) and the aerosol radiative forcing efficiency (ARFE) of various aerosol types at the top and the bottom of the ... Text Aerosol Robotic Network MDPI Open Access Publishing Remote Sensing 14 9 2058 |
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MDPI Open Access Publishing |
op_collection_id |
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language |
English |
topic |
aerosol classification 2-dimensional clustering Mahalanobis distance hierarchical clustering radiative forcing |
spellingShingle |
aerosol classification 2-dimensional clustering Mahalanobis distance hierarchical clustering radiative forcing Yushan Liu Bingqi Yi Aerosols over East and South Asia: Type Identification, Optical Properties, and Implications for Radiative Forcing |
topic_facet |
aerosol classification 2-dimensional clustering Mahalanobis distance hierarchical clustering radiative forcing |
description |
Identification of aerosol types has long been a difficult problem over East and South Asia due to various limitations. In this study, we use 2-dimensional (2-D) and multi-dimensional Mahalanobis distance (MD) clustering algorithms to identify aerosol characteristics based on the data from the Aerosol Robotic Network from March 1998 to February 2018 over the South and East Asian region (10°N~50°N, 70°E~135°E). The single scattering albedo (SSA), absorption Angstrom exponent (AAE), extinction Angstrom exponent (EAE), real index of refraction (RRI), and imaginary index of refraction (IRI) are utilized for classification of aerosols. Sub-regions with similar background conditions over East and South Asia are identified by hierarchical clustering algorithm to illustrate distinctive meteorological states in different areas. The East and South Asian aerosols are found to have distinct regional and seasonal features relating to the meteorological conditions, land cover, and industrial infrastructure. It is found that the proportions of dust aerosol are the highest in spring at the SACOL site and in summer at the sites near the Northern Indo-Gangetic Plain area. In spring, biomass-burning aerosols are dominant over the central Indo-China Peninsula area. The aerosol characteristics at coastal sites are also analyzed and compared with previous results. The 2-D clustering method is useful when limited aerosol parameters are available, but the results are highly dependent on the sets of parameters used for identification. Comparatively, the MD method, which considers multiple aerosol parameters, could provide more comprehensive classification of aerosol types. It is estimated that only about 50% of the data samples that are identifiable by the MD method could be classified by the 2-D methods, and a lot of undetermined data samples could be mis-classified by the 2-D methods. The aerosol radiative forcing (ARF) and the aerosol radiative forcing efficiency (ARFE) of various aerosol types at the top and the bottom of the ... |
format |
Text |
author |
Yushan Liu Bingqi Yi |
author_facet |
Yushan Liu Bingqi Yi |
author_sort |
Yushan Liu |
title |
Aerosols over East and South Asia: Type Identification, Optical Properties, and Implications for Radiative Forcing |
title_short |
Aerosols over East and South Asia: Type Identification, Optical Properties, and Implications for Radiative Forcing |
title_full |
Aerosols over East and South Asia: Type Identification, Optical Properties, and Implications for Radiative Forcing |
title_fullStr |
Aerosols over East and South Asia: Type Identification, Optical Properties, and Implications for Radiative Forcing |
title_full_unstemmed |
Aerosols over East and South Asia: Type Identification, Optical Properties, and Implications for Radiative Forcing |
title_sort |
aerosols over east and south asia: type identification, optical properties, and implications for radiative forcing |
publisher |
Multidisciplinary Digital Publishing Institute |
publishDate |
2022 |
url |
https://doi.org/10.3390/rs14092058 |
op_coverage |
agris |
genre |
Aerosol Robotic Network |
genre_facet |
Aerosol Robotic Network |
op_source |
Remote Sensing; Volume 14; Issue 9; Pages: 2058 |
op_relation |
Atmospheric Remote Sensing https://dx.doi.org/10.3390/rs14092058 |
op_rights |
https://creativecommons.org/licenses/by/4.0/ |
op_doi |
https://doi.org/10.3390/rs14092058 |
container_title |
Remote Sensing |
container_volume |
14 |
container_issue |
9 |
container_start_page |
2058 |
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1774723174582190080 |