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Modelling of XCO(2) Surfaces Based on Flight Tests of TanSat Instruments

The TanSat carbon satellite is to be launched at the end of 2016. In order to verify the performance of its instruments, a flight test of TanSat instruments was conducted in Jilin Province in September, 2015. The flight test area covered a total area of about 11,000 km(2) and the underlying surface...

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Autores principales: Zhang, Li Li, Yue, Tian Xiang, Wilson, John P., Wang, Ding Yi, Zhao, Na, Liu, Yu, Liu, Dong Dong, Du, Zheng Ping, Wang, Yi Fu, Lin, Chao, Zheng, Yu Quan, Guo, Jian Hong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5134477/
https://www.ncbi.nlm.nih.gov/pubmed/27809272
http://dx.doi.org/10.3390/s16111818
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author Zhang, Li Li
Yue, Tian Xiang
Wilson, John P.
Wang, Ding Yi
Zhao, Na
Liu, Yu
Liu, Dong Dong
Du, Zheng Ping
Wang, Yi Fu
Lin, Chao
Zheng, Yu Quan
Guo, Jian Hong
author_facet Zhang, Li Li
Yue, Tian Xiang
Wilson, John P.
Wang, Ding Yi
Zhao, Na
Liu, Yu
Liu, Dong Dong
Du, Zheng Ping
Wang, Yi Fu
Lin, Chao
Zheng, Yu Quan
Guo, Jian Hong
author_sort Zhang, Li Li
collection PubMed
description The TanSat carbon satellite is to be launched at the end of 2016. In order to verify the performance of its instruments, a flight test of TanSat instruments was conducted in Jilin Province in September, 2015. The flight test area covered a total area of about 11,000 km(2) and the underlying surface cover included several lakes, forest land, grassland, wetland, farmland, a thermal power plant and numerous cities and villages. We modeled the column-average dry-air mole fraction of atmospheric carbon dioxide (XCO(2)) surface based on flight test data which measured the near- and short-wave infrared (NIR) reflected solar radiation in the absorption bands at around 760 and 1610 nm. However, it is difficult to directly analyze the spatial distribution of XCO(2) in the flight area using the limited flight test data and the approximate surface of XCO(2), which was obtained by regression modeling, which is not very accurate either. We therefore used the high accuracy surface modeling (HASM) platform to fill the gaps where there is no information on XCO(2) in the flight test area, which takes the approximate surface of XCO(2) as its driving field and the XCO(2) observations retrieved from the flight test as its optimum control constraints. High accuracy surfaces of XCO(2) were constructed with HASM based on the flight’s observations. The results showed that the mean XCO(2) in the flight test area is about 400 ppm and that XCO(2) over urban areas is much higher than in other places. Compared with OCO-2’s XCO(2), the mean difference is 0.7 ppm and the standard deviation is 0.95 ppm. Therefore, the modelling of the XCO(2) surface based on the flight test of the TanSat instruments fell within an expected and acceptable range.
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spelling pubmed-51344772017-01-03 Modelling of XCO(2) Surfaces Based on Flight Tests of TanSat Instruments Zhang, Li Li Yue, Tian Xiang Wilson, John P. Wang, Ding Yi Zhao, Na Liu, Yu Liu, Dong Dong Du, Zheng Ping Wang, Yi Fu Lin, Chao Zheng, Yu Quan Guo, Jian Hong Sensors (Basel) Article The TanSat carbon satellite is to be launched at the end of 2016. In order to verify the performance of its instruments, a flight test of TanSat instruments was conducted in Jilin Province in September, 2015. The flight test area covered a total area of about 11,000 km(2) and the underlying surface cover included several lakes, forest land, grassland, wetland, farmland, a thermal power plant and numerous cities and villages. We modeled the column-average dry-air mole fraction of atmospheric carbon dioxide (XCO(2)) surface based on flight test data which measured the near- and short-wave infrared (NIR) reflected solar radiation in the absorption bands at around 760 and 1610 nm. However, it is difficult to directly analyze the spatial distribution of XCO(2) in the flight area using the limited flight test data and the approximate surface of XCO(2), which was obtained by regression modeling, which is not very accurate either. We therefore used the high accuracy surface modeling (HASM) platform to fill the gaps where there is no information on XCO(2) in the flight test area, which takes the approximate surface of XCO(2) as its driving field and the XCO(2) observations retrieved from the flight test as its optimum control constraints. High accuracy surfaces of XCO(2) were constructed with HASM based on the flight’s observations. The results showed that the mean XCO(2) in the flight test area is about 400 ppm and that XCO(2) over urban areas is much higher than in other places. Compared with OCO-2’s XCO(2), the mean difference is 0.7 ppm and the standard deviation is 0.95 ppm. Therefore, the modelling of the XCO(2) surface based on the flight test of the TanSat instruments fell within an expected and acceptable range. MDPI 2016-11-01 /pmc/articles/PMC5134477/ /pubmed/27809272 http://dx.doi.org/10.3390/s16111818 Text en © 2016 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Zhang, Li Li
Yue, Tian Xiang
Wilson, John P.
Wang, Ding Yi
Zhao, Na
Liu, Yu
Liu, Dong Dong
Du, Zheng Ping
Wang, Yi Fu
Lin, Chao
Zheng, Yu Quan
Guo, Jian Hong
Modelling of XCO(2) Surfaces Based on Flight Tests of TanSat Instruments
title Modelling of XCO(2) Surfaces Based on Flight Tests of TanSat Instruments
title_full Modelling of XCO(2) Surfaces Based on Flight Tests of TanSat Instruments
title_fullStr Modelling of XCO(2) Surfaces Based on Flight Tests of TanSat Instruments
title_full_unstemmed Modelling of XCO(2) Surfaces Based on Flight Tests of TanSat Instruments
title_short Modelling of XCO(2) Surfaces Based on Flight Tests of TanSat Instruments
title_sort modelling of xco(2) surfaces based on flight tests of tansat instruments
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5134477/
https://www.ncbi.nlm.nih.gov/pubmed/27809272
http://dx.doi.org/10.3390/s16111818
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