Analysis of CO<sub>2</sub> spatiotemporal variations in China using tower data and a weather-biosphere-online-coupled model, WRF-VPRM

Abstract. Dynamics of CO2 has received considerable attention in the literature, yet significant uncertainties remain within the estimates of contribution from terrestrial flux and the influence of atmospheric mixing. In this study we apply the Weather Research and Forecasting model coupled with Vegetation Photosynthesis and Respiration Model (WRF-VPRM) in China to characterize CO2 dynamics with tower data collected at a background site Lin’an (30.30° N, 119.75° E). The online coupled weather-biosphere WRF-VPRM simulations are able to simulate biosphere processes (photosynthetic uptake and ecosystem respiration) and meteorology in one coordinate system. Simulations are conducted for three years (2016–2018) with fine grid resolution (20 km) to detail the spatiotemporal variations of CO2 fluxes and concentrations. This is the first attempt to apply the weather-biosphere model for a multi-year simulation with integrated data from a satellite product, flask samplings, and tower measurements to diagnose the dynamics of CO2 in China. We find that the spatial distribution of CO2 is determined by anthropogenic emissions, while its seasonality (with maximum concentrations in April 15 ppmv higher than minimums in August) is dominated by terrestrial flux and background CO2. Observations and simulations reveal a consistent increasing trend in column-averaged CO2 (XCO2) of 0.6 %/yr resulting from anthropogenic emission growth and biosphere uptake. WRF-VPRM successfully reproduces ground-based measurements of surface CO2 concentration with mean bias of −0.79 ppmv (−0.20 %) and satellite derived XCO2 with mean bias of 0.76 ppmv (0.19 %). The model-simulated seasonality is also consistent with observations, with correlation coefficients of 0.90 and 0.89 for ground-based measurements and Orbiting Carbon Observatory-2 (OCO-2) satellite data, respectively. However, evaluation against Lin'an tower data reveals uncertainty within the model for simulating the intensity and diurnal variation of terrestrial flux, which contributes to overestimation by ~5.35 ppmv (1.26 %). Lin'an tower observations also reveal a strong correlation (−0.85) between vertical CO2 and temperature gradients, suggesting a significant influence of boundary layer thermal structure on the accumulation and depletion of atmospheric CO2.