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CMAQ simulation of atmospheric CO2 concentration in East Asia: Comparison with GOSAT observations and ground measurements

Author:
Li, Rong, Zhang, Meigen, Chen, Liangfu, Kou, Xingxia, Skorokhod, Andrei
Source:
Atmospheric environment 2017 v.160 pp. 176-185
ISSN:
1352-2310
Subject:
atmospheric chemistry, carbon, carbon dioxide, correlation, gases, greenhouse gases, satellites, simulation models, uncertainty, East Asia
Abstract:
Satellite observations are widely used in global CO2 assimilations, but their quality for use in regional assimilation systems has not yet been thoroughly determined. Validation of satellite observations and model simulations of CO2 is crucial for carbon flux inversions. In this study, we focus on evaluating the uncertainties of model simulations and satellite observations. The atmospheric CO2 distribution in East Asia during 2012 was simulated using a regional chemical transport model (RAMS-CMAQ) and compared with both CO2 column density (XCO2) from the Gases Observing SATellite (GOSAT) and CO2 concentrations from the World Data Centre for Greenhouse Gases (WDCGG). The results indicate that simulated XCO2 is generally lower than GOSAT XCO2 by 1.19 ppm on average, and their monthly differences vary from 0.05 to 2.84 ppm, with the corresponding correlation coefficients ranging between 0.1 and 0.67. CMAQ simulations are good to capture the CO2 variation as ground-based observations, and their correlation coefficients are from 0.62 to 0.93, but the average value of CMAQ simulation is 2.4 ppm higher than ground-based observation. Thus, we inferred that the GOSAT retrievals may overestimate XCO2, which is consistent with the validation of GOSAT XCO2 using Total Carbon Column Observing Network measurements. The near-surface CO2 concentration was obviously overestimated in GOSAT XCO2. Compared with the relatively small difference between CMAQ and GOSAT XCO2, the large difference in CO2 near surface or their vertical profiles indicates more improvements are needed to reduce the uncertainties in both satellite observations and model simulations.
Agid:
5674663