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基于碳卫星仪器飞行试验的XCO₂ 表面建模

Modelling of XCO₂ Surfaces Based on Flight Tests of TanSat Instruments.

作者信息

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

机构信息

State Key Laboratory of Resources and Environment Information System, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China.

Spatial Sciences Institute, Dana and David Dornsife College of Letters, Arts, and Sciences, University of Southern California, Los Angeles, CA 90089-0374, USA.

出版信息

Sensors (Basel). 2016 Nov 1;16(11):1818. doi: 10.3390/s16111818.

DOI:10.3390/s16111818
PMID:27809272
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5134477/
Abstract

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 km² 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 (XCO₂) 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 XCO₂ in the flight area using the limited flight test data and the approximate surface of XCO₂, 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 XCO₂ in the flight test area, which takes the approximate surface of XCO₂ as its driving field and the XCO₂ observations retrieved from the flight test as its optimum control constraints. High accuracy surfaces of XCO₂ were constructed with HASM based on the flight's observations. The results showed that the mean XCO₂ in the flight test area is about 400 ppm and that XCO₂ over urban areas is much higher than in other places. Compared with OCO-2's XCO₂, the mean difference is 0.7 ppm and the standard deviation is 0.95 ppm. Therefore, the modelling of the XCO₂ surface based on the flight test of the TanSat instruments fell within an expected and acceptable range.

摘要

碳卫星计划于2016年底发射。为了验证其仪器性能,2015年9月在吉林省进行了碳卫星仪器的飞行测试。飞行测试区域总面积约11000平方公里,下垫面覆盖了多个湖泊、林地、草地、湿地、农田、一座热电厂以及众多城镇和村庄。我们基于飞行测试数据对大气二氧化碳柱平均干空气摩尔分数(XCO₂)地表进行了建模,该数据测量了760和1610纳米附近吸收波段的近红外和短波红外(NIR)太阳反射辐射。然而,利用有限的飞行测试数据和通过回归建模获得的不太准确的XCO₂近似地表,很难直接分析飞行区域内XCO₂的空间分布。因此,我们使用高精度地表建模(HASM)平台来填补飞行测试区域中没有XCO₂信息的空白,该平台以XCO₂近似地表作为驱动场,以从飞行测试中反演得到的XCO₂观测值作为最优控制约束。基于飞行观测,利用HASM构建了高精度的XCO₂地表。结果表明,飞行测试区域的平均XCO₂约为400ppm,城市地区的XCO₂远高于其他地区。与OCO - 2的XCO₂相比,平均差值为0.7ppm,标准差为0.95ppm。因此,基于碳卫星仪器飞行测试的XCO₂地表建模结果在预期和可接受范围内。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7965/5134477/02046ed860e2/sensors-16-01818-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7965/5134477/e2263b4b6477/sensors-16-01818-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7965/5134477/9234390196cc/sensors-16-01818-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7965/5134477/4fee1f045b15/sensors-16-01818-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7965/5134477/97af7cbc3962/sensors-16-01818-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7965/5134477/e006bbb8d7bd/sensors-16-01818-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7965/5134477/1923d4763a03/sensors-16-01818-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7965/5134477/d85f7a84658b/sensors-16-01818-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7965/5134477/7342dbff2041/sensors-16-01818-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7965/5134477/16b37d14aa2c/sensors-16-01818-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7965/5134477/02046ed860e2/sensors-16-01818-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7965/5134477/e2263b4b6477/sensors-16-01818-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7965/5134477/9234390196cc/sensors-16-01818-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7965/5134477/4fee1f045b15/sensors-16-01818-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7965/5134477/97af7cbc3962/sensors-16-01818-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7965/5134477/e006bbb8d7bd/sensors-16-01818-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7965/5134477/1923d4763a03/sensors-16-01818-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7965/5134477/d85f7a84658b/sensors-16-01818-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7965/5134477/7342dbff2041/sensors-16-01818-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7965/5134477/16b37d14aa2c/sensors-16-01818-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7965/5134477/02046ed860e2/sensors-16-01818-g010.jpg

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本文引用的文献

1
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Sci Total Environ. 2016 Feb 1;543(Pt A):609-619. doi: 10.1016/j.scitotenv.2015.11.077. Epub 2015 Nov 22.
2
The total carbon column observing network.大气总碳柱观测网络。
Philos Trans A Math Phys Eng Sci. 2011 May 28;369(1943):2087-112. doi: 10.1098/rsta.2010.0240.