A WRF-Chem study of the greenhouse gas column and in situ surface mole fractions observed at Xianghe, China-Part 2: Sensitivity of carbon dioxide (CO2) simulations to critical model parameters - 2026
A WRF-Chem study of the greenhouse gas column and in situ surface mole fractions observed at Xianghe, China-Part 2: Sensitivity of carbon dioxide (CO2) simulations to critical model parameters
[en] Understanding the variability and sources of atmospheric CO2 is essential for improving greenhouse gas monitoring and model performance. This study investigates temporal CO2 variability at the Xianghe site in China, which hosts both remote sensed (TCCON-affiliated) and in situ (PICARRO) observations. Using the Weather Research and Forecast model coupled with Chemistry, in its greenhouse gas option (WRF-GHG), we performed a one-year simulation of surface and column-averaged CO2 mole fractions, evaluated model performance and conducted sensitivity experiments to assess the influence of key model configuration choices. The model captured the temporal variability of column-averaged mole fraction of CO2 (XCO2) reasonably well (r=0.7), although a persistent bias in background values was found. A July 2019 heatwave case study further demonstrated the model’s ability to reproduce a synoptically driven anomaly. Near the surface, performance was good during afternoon hours (r=0.75, MBE =2.44 ppm), nighttime mole fractions were overestimated (MBE = 7.86 ppm), resulting in an exaggerated diurnal amplitude. Sensitivity tests revealed that land cover data, vertical emission profiles, and adjusted VPRM-parameters (Vegetation Photosynthesis and Respiration Model) can significantly influence modeled mole fractions, particularly at night. Tracer analysis identified industry and energy as dominant sources, while biospheric fluxes introduced seasonal variability-acting as a moderate sink in summer for XCO2 and a net source in most months near the surface. These findings demonstrate the utility of WRF-GHG for interpreting temporal patterns and sectoral contributions to CO2 variability at Xianghe, while emphasizing the importance of careful model configuration to ensure reliable simulations.
Disciplines :
Earth sciences & physical geography
Author, co-author :
Callewaert, Sieglinde ; Université de Liège - ULiège > Sphères ; Royal Belgian Institute for Space Aeronomy, BIRA-IASB, Brussels, Belgium
Zhou, Minqiang ; Royal Belgian Institute for Space Aeronomy, BIRA-IASB, Brussels, Belgium ; State Key Laboratory of Atmospheric Environment and Extreme Meteorology, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
Langerock, Bavo ; Royal Belgian Institute for Space Aeronomy, BIRA-IASB, Brussels, Belgium
Wang, Pucai; CNRC, LAGEO, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
Wang, Ting; CNRC, LAGEO, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
Mahieu, Emmanuel ; Université de Liège - ULiège > Sphères ; Université de Liège - ULiège > Département d'astrophysique, géophysique et océanographie (AGO) > Groupe infra-rouge de physique atmosphérique et solaire (GIRPAS)
De Mazière, Martine; Royal Belgian Institute for Space Aeronomy, BIRA-IASB, Brussels, Belgium
Language :
English
Title :
A WRF-Chem study of the greenhouse gas column and in situ surface mole fractions observed at Xianghe, China-Part 2: Sensitivity of carbon dioxide (CO2) simulations to critical model parameters
We would like to thank all staff at the Xianghe site for operating the FTIR and PICARRO measurements.Emmanuel Mahieu is a research director with the F.R.S.-FNRS.The authors acknowledge all providers of observational data andemission inventories. We thank the IT team at BIRA-IASB for theirsupport on data storage and HPC maintenance. Christophe Gerbig,Roberto Kretschmer, and Thomas Koch (MPI BGC) are thankedfor distributing the VPRM preprocessor code. Finally, we are grateful for fruitful discussions with Jean-Fran\u00E7ois M\u00FCller (BIRA-IASB)and Bernard Heinesch (ULi\u00E8ge).This work is supported by the NationalKey Research and Development Program of China (grant nos.2023YFB3907500, 2023YFB3907505). This research has beensupported by the Belgian Federal Government and the Belgian tax exemption law for promoting scientific research (Art. 275/3 ofCIR92).This work is supported by the National Key Research and Development Program of China (grant nos. 2023YFB3907500, 2023YFB3907505). This research has been supported by the Belgian Federal Government and the Belgian tax exemption law for promoting scientific research (Art. 275/3 of CIR92).
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