Retrieval and Validation of XCO2 from TanSat Target Mode Observations in Beijing

Bao, Zhengyi; Zhang, Xingying; Yue, Tianxiang; Zhang, Lili; Zong, Wang; Yan, Jiao; Bai, Wenguang; Meng, Xiangzhi

doi:10.3390/rs12183063

Cited by 8 publications

(6 citation statements)

References 42 publications

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“…The TanSat and GF-5 series GHGs satellite payloads developed by China have successfully obtained high precision of global CO2 distributions (Li et al, 2016;Wu et al, 2018;Zhang et al, 2020a;Zhao et al, 2021). The comparisons with the TCCON, GOSAT, and OCO-2 data show that some key performance indicators such as accuracy, precision, and spatiotemporal resolution of these Chinese GHGs satellites have reached the envisaged requirements (Liu et al, 2013;Liu et al, 2014;Cai et al, 2014;Du et al, 2018;Yang et al, 2018a;Yang et al, 2018b, c;Zhang et al, 2019;Zhao et al, 2019;Bao et al, 2020;Wang et al, 2020c;Yang et al, 2020a, b;Yang et al, 2020d;Boesch et al, 2021;Yang et al, 2021a;Yang et al, 2021b). Both 2.…”

Section: Advances In Ghgs Monitoring In Chinamentioning

confidence: 92%

Monitoring greenhouse gases (GHGs) in China: status and perspective

Sun

Yin²,

Wang³

et al. 2022

Preprint

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Abstract. In order to establish a creditable greenhouse gases (GHGs) monitoring network to support the goals of carbon peak/neutrality, it is necessary to know what we have done and what we have to do in the future. In this study, we summarize an overview to the status and perspective of GHGs monitoring in China. With decades of effort, China has made a great breakthrough in GHGs monitoring capacity and steadily improved the performance of homemade GHGs monitoring instruments. However, most GHGs monitoring studies are hitherto research-oriented, temporal, sparse, and uncoordinated. It is suggested to take full advantages of various monitoring technologies, monitoring platforms, numerical simulations, and inventory compilation techniques to form a creditable GHGs stereoscopic monitoring and assessment system at an operational level. We envisage that this system can routinely quantify GHGs on national, provincial, regional and even individual scales with high spatiotemporal resolution and wide coverage to support low-carbon policy in China.

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Section: Advances In Ghgs Monitoring In Chinamentioning

confidence: 92%

Monitoring greenhouse gases (GHGs) in China: status and perspective

Sun

Yin²,

Wang³

et al. 2022

Preprint

View full text Add to dashboard Cite

show abstract

“…Comparisons with the TCCON, GOSAT, and OCO-2 data show that some key performance indicators such as accuracy, precision, and spatiotemporal resolution of these Chinese GHG satellites have reached the envisaged requirements (Liu et al, 2013(Liu et al, , 2014(Liu et al, , 2018Cai et al, 2014;Du et al, 2018;Z. D. Yang et al, 2018b;Zhang et al, 2019;Zhao et al, 2021;Bao et al, 2020;Boesch et al, 2021;Yang et al, 2021a, b). Both TanSat and GF-5 series GHG payloads use passive remote sensing technology to derive global CO 2 distributions from scattered sunlight.…”

Section: Advances In Ghg Monitoring In Chinamentioning

confidence: 97%

“…D. Yang et al, 2018b;Zhang et al, 2019;Z. D. Yang et al, 2020;Bao et al, 2020;Yang et al, 2021a, b) and Gaofen-5 (GF-5) series satellites from China (Li et al, 2016;Wu et al, 2018;Zhao et al, 2021), GHGSat from Canada (Varon et al, 2019;Jervis et al, 2021), etc., have been launched to derive the global distributions of GHGs. These satellites mainly measure total columns of GHGs by means of infrared grating or Fourier transform infrared (FTIR) spectrometers through atmospheric limb or nadir observations.…”

Section: History Of Ghg Monitoring Around the Globementioning

confidence: 99%

Monitoring greenhouse gases (GHGs) in China: status and perspective

et al. 2022

View full text Add to dashboard Cite

Abstract. In order to establish a creditable greenhouse gas (GHG) monitoring network to support the goals of carbon peak/neutrality, it is necessary to know what we have done and what we have to do in the future. In this study, we summarize an overview of the status and perspective of GHG monitoring in China. With decades of effort, China has made a great breakthrough in GHG monitoring capacity and steadily improved the performance of homemade GHG monitoring instruments. However, most GHG monitoring studies have been research-oriented, temporal, sparse, and uncoordinated. It is suggested to take full advantage of various monitoring technologies, monitoring platforms, numerical simulations, and inventory compilation techniques to form a creditable GHG stereoscopic monitoring and assessment system at an operational level. We envisage that this system can routinely quantify GHGs on national, provincial, regional, and even individual scales with high spatiotemporal resolution and wide coverage to support low-carbon policy in China.

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“…The TanSat global XCO 2 product is retrieved by the IAPCAS (the Institute of Atmospheric Physics Carbon Dioxide Retrieval Algorithm for Satellite Remote Sensing) algorithm, which was developed by the Institute of Atmospheric Physics (IAP). It has a general accuracy of 2.11 ppm and the absolute biases over TCCON stations such as Sodankyla and Karlsruhe are more than 2.9 ppm [43,44]. The ACOS XCO 2 retrieval algorithm was used to process the TANSAT L1B data, noting that the average bias of ACOS algorithm is smaller than that of OCO-2, which is 0.85 ppm [32].…”

Section: Tansat Datamentioning

confidence: 99%

Study on the Ground-Based FTS Measurements at Beijing, China and the Colocation Sensitivity of Satellite Data

et al. 2021

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The Fourier Transform Spectrometer (FTS) at the Beijing Satellite Meteorological Ground Station observed XCO2 (the dry carbon dioxide column) from 2 March 2016 to 4 December 2018. The validation results of ground-based XCO2, as well as GOSAT, OCO-2, and TanSat XCO2, show that the best temporal matching setting for ground-based XCO2 and satellite XCO2 is ±1 h, and the best spatial matching setting for GOSAT is 0.5° × 0.5°. Consistent with OCO-2, the best spatial matching setting of TanSat is 5° × 5° or 6° × 6°. Among GOSAT, OCO-2, and TanSat, the satellite observation validation characteristics near 5° × 5° from the ground-based station are obviously different from other spatial matching grids, which may be due to the different observation characteristics of satellites near 5° × 5°. To study the influence of local CO2 sources on the characteristics of satellite observation validation, we classified the daily XCO2 observation sequence into concentrated, dispersive, increasing, and decreasing types, respectively, and then validated the satellite observations. The results showed that the concentrated and decreasing sub-datasets have better validation performance. Our results suggest that it is best to use concentrated and decreasing sub-datasets when using the Beijing Satellite Meteorological Ground Station XCO2 for satellite validation. The temporal matching setting should be ±1 h, and the spatial matching setting should consider the satellites observation characteristics of 5° × 5° distance from the ground-based station.

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Retrieval and Validation of XCO2 from TanSat Target Mode Observations in Beijing

Cited by 8 publications

References 42 publications

Monitoring greenhouse gases (GHGs) in China: status and perspective

Monitoring greenhouse gases (GHGs) in China: status and perspective

Monitoring greenhouse gases (GHGs) in China: status and perspective

Study on the Ground-Based FTS Measurements at Beijing, China and the Colocation Sensitivity of Satellite Data

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