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Combined use of satellite and surface observations to study aerosol optical depth in different regions of China

Aerosol optical depth (AOD) is one of essential atmosphere parameters for climate change assessment as well as for total ecological situation study. This study presents long-term data (2000–2017) on time-space distribution and trends in AOD over various ecological regions of China, received from Mod...

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Autores principales: Filonchyk, Mikalai, Yan, Haowen, Zhang, Zhongrong, Yang, Shuwen, Li, Wei, Li, Yanming
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6467898/
https://www.ncbi.nlm.nih.gov/pubmed/30992472
http://dx.doi.org/10.1038/s41598-019-42466-6
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author Filonchyk, Mikalai
Yan, Haowen
Zhang, Zhongrong
Yang, Shuwen
Li, Wei
Li, Yanming
author_facet Filonchyk, Mikalai
Yan, Haowen
Zhang, Zhongrong
Yang, Shuwen
Li, Wei
Li, Yanming
author_sort Filonchyk, Mikalai
collection PubMed
description Aerosol optical depth (AOD) is one of essential atmosphere parameters for climate change assessment as well as for total ecological situation study. This study presents long-term data (2000–2017) on time-space distribution and trends in AOD over various ecological regions of China, received from Moderate Resolution Imaging Spectroradiometer (MODIS) (combined Dark Target and Deep Blue) and Multi-angle Imaging Spectroradiometer (MISR), based on satellite Terra. Ground-based stations Aerosol Robotic Network (AERONET) were used to validate the data obtained. AOD data, obtained from two spectroradiometers, demonstrate the significant positive correlation relationships (r = 0.747), indicating that 55% of all data illustrate relationship among the parameters under study. Comparison of results, obtained with MODIS/MISR Terra and AERONET, demonstrate high relation (r = 0.869 - 0.905), while over 60% of the entire sampling fall within the range of the expected tolerance, established by MODIS and MISR over earth (±0.05 ± 0.15 × AOD(AERONET) and 0.05 ± 0.2 × AOD(AERONET)) with root-mean-square error (RMSE) of 0.097–0.302 and 0.067–0.149, as well as low mean absolute error (MAE) of 0.068–0.18 and 0.067–0.149, respectively. The MODIS search results were overestimated for AERONET stations with an average overestimation ranging from 14 to 17%, while there was an underestimate of the search results using MISR from 8 to 22%.
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spelling pubmed-64678982019-04-23 Combined use of satellite and surface observations to study aerosol optical depth in different regions of China Filonchyk, Mikalai Yan, Haowen Zhang, Zhongrong Yang, Shuwen Li, Wei Li, Yanming Sci Rep Article Aerosol optical depth (AOD) is one of essential atmosphere parameters for climate change assessment as well as for total ecological situation study. This study presents long-term data (2000–2017) on time-space distribution and trends in AOD over various ecological regions of China, received from Moderate Resolution Imaging Spectroradiometer (MODIS) (combined Dark Target and Deep Blue) and Multi-angle Imaging Spectroradiometer (MISR), based on satellite Terra. Ground-based stations Aerosol Robotic Network (AERONET) were used to validate the data obtained. AOD data, obtained from two spectroradiometers, demonstrate the significant positive correlation relationships (r = 0.747), indicating that 55% of all data illustrate relationship among the parameters under study. Comparison of results, obtained with MODIS/MISR Terra and AERONET, demonstrate high relation (r = 0.869 - 0.905), while over 60% of the entire sampling fall within the range of the expected tolerance, established by MODIS and MISR over earth (±0.05 ± 0.15 × AOD(AERONET) and 0.05 ± 0.2 × AOD(AERONET)) with root-mean-square error (RMSE) of 0.097–0.302 and 0.067–0.149, as well as low mean absolute error (MAE) of 0.068–0.18 and 0.067–0.149, respectively. The MODIS search results were overestimated for AERONET stations with an average overestimation ranging from 14 to 17%, while there was an underestimate of the search results using MISR from 8 to 22%. Nature Publishing Group UK 2019-04-16 /pmc/articles/PMC6467898/ /pubmed/30992472 http://dx.doi.org/10.1038/s41598-019-42466-6 Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Filonchyk, Mikalai
Yan, Haowen
Zhang, Zhongrong
Yang, Shuwen
Li, Wei
Li, Yanming
Combined use of satellite and surface observations to study aerosol optical depth in different regions of China
title Combined use of satellite and surface observations to study aerosol optical depth in different regions of China
title_full Combined use of satellite and surface observations to study aerosol optical depth in different regions of China
title_fullStr Combined use of satellite and surface observations to study aerosol optical depth in different regions of China
title_full_unstemmed Combined use of satellite and surface observations to study aerosol optical depth in different regions of China
title_short Combined use of satellite and surface observations to study aerosol optical depth in different regions of China
title_sort combined use of satellite and surface observations to study aerosol optical depth in different regions of china
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6467898/
https://www.ncbi.nlm.nih.gov/pubmed/30992472
http://dx.doi.org/10.1038/s41598-019-42466-6
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