CO2 Flux Inversion With a Regional Joint Data Assimilation System Based on CMAQ, EnKS, and Surface Observations. Issue 3 (27th January 2023)

• Record Type: Journal Article
• Authors: Peng, Zhen; Kou, Xingxia; Zhang, Meigen; Lei, Lili; Miao, Shiguang; Wang, Hengmao; Jiang, Fei; Han, Xiao; Fang, Shuangxi
• Is Part Of: Journal of geophysical research. Volume 128:Issue 3(2023)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2023-01-27
• Subjects: Atmospheric physics -- Periodicals; Geophysics -- Periodicals; 551.5
• DOI: 10.1029/2022JD037154
• Languages: English
• ISSNs: 2169-897X

Abstract

Abstract: Most of China's carbon sink inversion research uses global atmospheric transport models to assimilate natural fluxes, which quantifies the biosphere and ocean carbon budget with a relative coarse spatial resolution and long timescale from a weekly or monthly perspective. Toward high‐resolution inversion of CO2 fluxes, a novel carbon flux forecast model was developed in this study, which was then further used to carry out carbon assimilation based on a regional chemical transport model (CMAQ) at higher spatial (64 × 64 km 2 ) and temporal (1 hr) resolutions. An Ensemble Kalman Smoother was applied as the assimilation algorithm and further extended to assimilate surface CO2 observations. Concentrations and fluxes were simultaneously assimilated as state variables to help reduce the uncertainty in the initial CO2 fields with the joint data assimilation framework (JDAS). In general, the posterior fluxes reproduced the seasonal, daily and hourly variation effectively, demonstrating the ability to fully absorb and utilize observations. Moreover, the influence of the choice of assimilation window on the carbon flux inversion was assessed via sensitivity experiments, revealing 36 hr to be the optimum length. Evaluation of the prior and posterior flux simulations also indicated that JDAS offers reasonable improvements, making it suitable for fine‐scale flux optimization and estimation. In addition, the posterior biosphere estimation in mainland China (−682 TgC yr −1 ) tends to be the optimal mathematical solution under current sparse observation coverage with daytime photosynthetic uptake, which likely leads to the overestimation of the optimized CO2 sink. This study serves as a basis for future regional and urban assessment. Plain Language Summary: Top‐down methods are used increasingly to constrain the carbon budget under the Monitoring and Verification Support framework by the United Nations Framework Convention on Climate Change. Different to previous attempts to assimilate China's carbon sink from a weekly or monthly perspective, we developed a novel regional carbon inversion system based on Community Multiscale Air Quality (CMAQ) and Ensemble Kalman Smoother with surface observations toward high‐resolution inversion of CO2 fluxes. Besides the forward, fine‐scale simulation by CMAQ, a flux forecast model with diurnal variation capability was also introduced to facilitate illustrating the hourly evolution of ensemble fluxes. The results indicate that our posterior fluxes reproduced the seasonal, daily and hourly variation effectively, which suggests the method provides a promising tool for future monitoring of the effectiveness of progress toward carbon neutrality. Key Points: An Ensemble Kalman Smoother‐based regional carbon data assimilation system was developed with Community Multiscale Air Quality to resolve fine‐scale CO2 flux variability The seasonal, daily and hourly variations of posterior fluxes were reproduced effectively Sensitivity experiments further highlighted the valuable impact of the choice of assimilation window