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. The dynamics of atmospheric CO2 has received considerable attention in the literature, yet significant uncertainties remain within theestimates of contribution from the terrestrial flux and the influence of atmospheric mixing. In this study we apply the WRF-Chem model configured withthe Vegetation Photosynthesis and Respiration Model (VPRM) option for biomass fluxes in China to characterize the dynamics of CO2 in theatmosphere. The online coupled WRF-Chem model is able to simulate biosphere processes (photosynthetic uptake and ecosystem respiration) and meteorology inone coordinate system. We apply WRF-Chem for a multi-year simulation (2016–2018) with integrated data from a satellite product, flask samplings,and tower measurements to diagnose the spatio-temporal variations of CO2 fluxes and concentrations in China. We find that the spatialdistribution of CO2 was dominated by anthropogenic emissions, while its seasonality (with maxima in April 15 ppmv higher thanminima in August) was dominated by the terrestrial flux and background CO2. Observations and simulations revealed a consistent increasingtrend in column-averaged CO2 (XCO2) of 2.46 ppmv (0.6 % yr−1) resulting from anthropogenic emissiongrowth and biosphere uptake. WRF-Chem successfully reproduced ground-based measurements of surface CO2 concentration with a mean bias of−0.79 ppmv and satellite-derived XCO2 with a mean bias of 0.76 ppmv. The model-simulated seasonality was also consistentwith observations, with correlation coefficients of 0.90 and 0.89 for ground-based measurements and satellite data, respectively. Tower observationsfrom a background site at Lin'an (30.30∘ N, 119.75∘ E) revealed a strong correlation (−0.98) between vertical CO2 andtemperature gradients, suggesting a significant influence of boundary layer thermal structure on the accumulation and depletion of atmosphericCO2.

Analysis of CO&lt;sub&gt;2&lt;/sub&gt; spatio-temporal variations in China using a weather–biosphere online coupled model

Analysis of CO<sub>2</sub> spatio-temporal variations in China using a weather–biosphere online coupled model