期刊
JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES
卷 125, 期 22, 页码 -出版社
AMER GEOPHYSICAL UNION
DOI: 10.1029/2020JD032794
关键词
TanSat; CO2; satellite; retrieval algorithm
资金
- National Key R&D Program of China [2016YFA0600203]
- Key Research Program of the Chinese Academy of Sciences [ZDRW-ZS-2019-1]
- International Partnership Program of Chinese Academy of Sciences [GJHZ201903]
- National Natural Science Foundation of China [41905029]
- ESA Climate Change Initiative CCI + (GhG theme), Earthnet Data Assessment Pilot (EDAP) project
- ESA-MOST Dragon-4 programme [32301]
- UK NERC National Centre for Earth Observation (NCEO) [nceo020005]
- International Reanalysis Cooperation on Carbon Satellites Data (IRCSD)
- French research center CNRS
- French space agency CNES
- Region Ile-de-France
- Energy Development Corporation (EDC, Philippines)
- Darwin
- Australian Research Council [DP0879468, DP110103118, DP140101552, DP160101598, LE0668470, DE140100178]
- Australian Bureau of Meteorology
- NASA
- Australian Research Council Future Fellowship [FT180100327]
- UOW/SMAH PEPA grant
- NERC [nceo020005] Funding Source: UKRI
- Australian Research Council [DE140100178] Funding Source: Australian Research Council
TanSat is the 1st Chinese carbon dioxide (CO2) measurement satellite, launched in 2016. In this study, the University of Leicester Full Physics (UoL-FP) algorithm is implemented for TanSat nadir mode XCO2 retrievals. We develop a spectrum correction method to reduce the retrieval errors by the online fitting of an 8(th) order Fourier series. The spectrum-correction model and its a priori parameters are developed by analyzing the solar calibration measurement. This correction provides a significant improvement to the O-2 A band retrieval. Accordingly, we extend the previous TanSat single CO2 weak band retrieval to a combined O-2 A and CO2 weak band retrieval. A Genetic Algorithm (GA) has been applied to determine the threshold values of post-screening filters. In total, 18.3% of the retrieved data is identified as high quality compared to the original measurements. The same quality control parameters have been used in a footprint independent multiple linear regression bias correction due to the strong correlation with the XCO2 retrieval error. Twenty sites of the Total Column Carbon Observing Network (TCCON) have been selected to validate our new approach for the TanSat XCO2 retrieval. We show that our new approach produces a significant improvement on the XCO2 retrieval accuracy and precision when compared to TCCON with an average bias and RMSE of -0.08 ppm and 1.47 ppm, respectively. The methods used in this study can help to improve the XCO2 retrieval from TanSat and subsequently the Level-2 data production, and hence will be applied in the TanSat operational XCO2 processing.
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