TY - JOUR
T1 - Development of the CMA-ChemRA
T2 - China Regional Weakly Coupled Chemical-Weather Reanalysis System with product since 2007
AU - Zhang, Tao
AU - Zhou, Zijiang
AU - Zhang, Zhisen
AU - Zhong, Junting
AU - Liu, Zhiquan
AU - Zhang, Xiaoye
AU - Xu, Wenhui
AU - Jiang, Lipeng
AU - Liao, Jie
AU - Ma, Yaping
AU - Zhou, Yike
AU - Wang, Huiying
AU - Chen, Jie
AU - Zhang, Lu
AU - Yao, Yan
AU - Jiang, Hui
AU - Jiang, Wenjing
N1 - Publisher Copyright:
© 2024 Elsevier B.V.
PY - 2024/12/20
Y1 - 2024/12/20
N2 - The CMA-ChemRA (China Regional Weakly Coupled Chemical-Weather Reanalysis System) was developped using China's first-generation global atmospheric reanalysis product (CRA-40) as initial fields and boundary conditions, coupled with the WRF-Chem atmospheric chemical model and the WRFDA/3DVar assimilation system. By constructing a joint background error covariance matrix, CMA-ChemRA achieves weak coupling between atmospheric chemistry and meteorological variables, enabling simultaneous assimilation of diverse data sources, including hourly observations from ground stations, wind profilers, upper-air soundings, aircraft reports, and atmospheric composition measurements. To extend the dataset to periods before 2013 when China lacked PM2.5 observations, the system incorporates a reconstructed PM2.5 dataset derived by AI from visibility inversion alongside various emission inventories. The CMA-ChemRA system produces a reanalysis product from 2007 to the present, with a spatial resolution of 15 km and an hourly temporal resolution. It includes three-dimensional isobaric and near-surface layers for 6 key elements PM2.5, PM10, O3, SO2, NO2, and CO, as well as meteorological variables. This product is updated in near real-time, with a 50-min lag for forecast updates. Evaluation of the system shows substantial improvements in accuracy, with significant reductions in root mean square error (RMSE) for the six elements in the near-surface atmospheric layer post-assimilation. The model's depiction of ground-level PM2.5 concentrations aligns well with independent observational data across five urban regions, showing a narrow RMSE range of 15.5 to 32.8 μg/m3. Additionally, CMA-ChemRA demonstrates strong performance in capturing the evolution of dust storms and pollution events, particularly in accurately modeling PM2.5 concentrations during severe pollution episodes. Our innovative approach in constructing a joint background error covariance matrix and the resulting high-resolution, real-time updating CMA-ChemRA product. This represents significant advancement in the field of atmospheric and chemical weather reanalysis. The product serves as an crucial tool for environmental monitoring and forecasting in China.
AB - The CMA-ChemRA (China Regional Weakly Coupled Chemical-Weather Reanalysis System) was developped using China's first-generation global atmospheric reanalysis product (CRA-40) as initial fields and boundary conditions, coupled with the WRF-Chem atmospheric chemical model and the WRFDA/3DVar assimilation system. By constructing a joint background error covariance matrix, CMA-ChemRA achieves weak coupling between atmospheric chemistry and meteorological variables, enabling simultaneous assimilation of diverse data sources, including hourly observations from ground stations, wind profilers, upper-air soundings, aircraft reports, and atmospheric composition measurements. To extend the dataset to periods before 2013 when China lacked PM2.5 observations, the system incorporates a reconstructed PM2.5 dataset derived by AI from visibility inversion alongside various emission inventories. The CMA-ChemRA system produces a reanalysis product from 2007 to the present, with a spatial resolution of 15 km and an hourly temporal resolution. It includes three-dimensional isobaric and near-surface layers for 6 key elements PM2.5, PM10, O3, SO2, NO2, and CO, as well as meteorological variables. This product is updated in near real-time, with a 50-min lag for forecast updates. Evaluation of the system shows substantial improvements in accuracy, with significant reductions in root mean square error (RMSE) for the six elements in the near-surface atmospheric layer post-assimilation. The model's depiction of ground-level PM2.5 concentrations aligns well with independent observational data across five urban regions, showing a narrow RMSE range of 15.5 to 32.8 μg/m3. Additionally, CMA-ChemRA demonstrates strong performance in capturing the evolution of dust storms and pollution events, particularly in accurately modeling PM2.5 concentrations during severe pollution episodes. Our innovative approach in constructing a joint background error covariance matrix and the resulting high-resolution, real-time updating CMA-ChemRA product. This represents significant advancement in the field of atmospheric and chemical weather reanalysis. The product serves as an crucial tool for environmental monitoring and forecasting in China.
KW - Assimilation
KW - Chemical-weather coupled reanalysis
KW - Operational production
UR - https://www.scopus.com/pages/publications/85209256208
U2 - 10.1016/j.scitotenv.2024.177552
DO - 10.1016/j.scitotenv.2024.177552
M3 - Article
AN - SCOPUS:85209256208
SN - 0048-9697
VL - 957
JO - Science of the Total Environment
JF - Science of the Total Environment
M1 - 177552
ER -