A Theoretical Analysis for Improving Aerosol-Induced CO 2 Retrieval Uncertainties Over Land Based on TanSat Nadir Observations Under Clear Sky Conditions

• Published in: Remote Sensing
• Main Authors: Xi Chen, Yi Liu, Dongxu Yang, Zhaonan Cai, Hongbin Chen, Maohua Wang
• Format: Article in Journal/Newspaper
• Language: English
• Published: MDPI AG 2019
• Subjects: TanSat; aerosol; DFS; error; CO 2; Science; Q; Aerosol Robotic Network
• Online Access: https://doi.org/10.3390/rs11091061; https://doaj.org/article/9e6efe61731742d6bed6fe3993156da1

Aerosols significantly affect carbon dioxide (CO 2 ) retrieval accuracy and precision by modifying the light path. Hyperspectral measurements in the near infrared and shortwave infrared (NIR/SWIR) bands from the generation of new greenhouse gas satellites (e.g., the Chinese Global Carbon Dioxide Monitoring Scientific Experimental Satellite, TanSat) contain aerosol information for correction of scattering effects in the retrieval. Herein, a new approach is proposed for optimizing the aerosol model used in the TanSat CO 2 retrieval algorithm to reduce CO 2 uncertainties associated with aerosols. The weighting functions of hyperspectral observations with respect to elements in the state vector are simulated by a forward radiative transfer model. Using the optimal estimation method (OEM), the information content and each component of the CO 2 column-averaged dry-air mole fraction (XCO 2 ) retrieval errors from the TanSat simulations are calculated for typical aerosols which are described by Aerosol Robotic Network (AERONET) inversion products at selected sites based on the a priori and measurement assumptions. The results indicate that the size distribution parameters (r eff , v eff ), real refractive index coefficient of fine mode (a r f ) and fine mode fraction (fmf) dominate the interference errors, with each causing 0.2−0.8 ppm of XCO 2 errors. Given that only 4−7 degrees of freedom for signal (DFS) of aerosols can be obtained simultaneously and CO 2 information decreases as more aerosol parameters are retrieved, four to seven aerosol parameters are suggested as the most appropriate for inclusion in CO 2 retrieval. Focusing on only aerosol-induced XCO 2 errors, forward model parameter errors, rather than interference errors, are dominant. A comparison of these errors across different aerosol parameter combination groups reveals that fewer aerosol-induced XCO 2 errors are found when retrieving seven aerosol parameters. Therefore, the model selected as the optimal aerosol model includes aerosol optical depth ...