Research on the construction method of sample set in CO2 retrieval based on statistical analysis method

Jiang Yun; Huaduan Feng; Pan Yue; Wang Gen

doi:10.1117/12.3045868

13 December 2024 Research on the construction method of sample set in CO₂ retrieval based on statistical analysis method

Jiang Yun, Huaduan Feng, Pan Yue, Wang Gen

Author Affiliations +

Proceedings Volume 13504, AOPC 2024: Atmospheric and Environmental Optics; 1350406 (2024) https://doi.org/10.1117/12.3045868
Event: Applied Optics and Photonics China 2024 (AOPC2024), 2024, Beijing, China

Abstract

China's carbon reduction and emission reduction under the ‘double carbon’ target requires high-precision atmospheric CO₂ inversion data. High-precision atmospheric CO2 satellite observation is the basis for accurate positioning of emission sources. Aiming at the problem that the inversion algorithm is difficult to converge in the existing inversion methods, a statistical method integrating multi-source information is explored to obtain accurate prior profiles. It provides relatively accurate initial values for subsequent high-precision CO₂ inversion algorithms in order to improve the accuracy of CO₂ inversion. The statistical inversion method establishes a regression relationship model between satellite spectrum and atmospheric CO₂ concentration, and the inversion accuracy is affected by the representativeness of the sample and the regression analysis method. According to the difference of regional characteristics, the CO₂ profile samples are counted, and the sensitivity of environmental parameters is analyzed to construct a representative sample set. It is verified that the profile obtained by inversion is very close to the real profile, which verifies the feasibility of the method.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Jiang Yun, Huaduan Feng, Pan Yue, and Wang Gen "Research on the construction method of sample set in CO₂ retrieval based on statistical analysis method", Proc. SPIE 13504, AOPC 2024: Atmospheric and Environmental Optics, 1350406 (13 December 2024); https://doi.org/10.1117/12.3045868

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