Articles | Volume 16, issue 13
https://doi.org/10.5194/gmd-16-3827-2023
https://doi.org/10.5194/gmd-16-3827-2023
Development and technical paper
 | 
11 Jul 2023
Development and technical paper |  | 11 Jul 2023

An approach to refining the ground meteorological observation stations for improving PM2.5 forecasts in the Beijing–Tianjin–Hebei region

Lichao Yang, Wansuo Duan, and Zifa Wang

Related authors

Toward targeted observations of the meteorological initial state for improving the PM2.5 forecast of a heavy haze event that occurred in the Beijing–Tianjin–Hebei region
Lichao Yang, Wansuo Duan, Zifa Wang, and Wenyi Yang
Atmos. Chem. Phys., 22, 11429–11453, https://doi.org/10.5194/acp-22-11429-2022,https://doi.org/10.5194/acp-22-11429-2022, 2022
Short summary

Related subject area

Atmospheric sciences
Validation and analysis of the Polair3D v1.11 chemical transport model over Quebec
Shoma Yamanouchi, Shayamilla Mahagammulla Gamage, Sara Torbatian, Jad Zalzal, Laura Minet, Audrey Smargiassi, Ying Liu, Ling Liu, Forood Azargoshasbi, Jinwoong Kim, Youngseob Kim, Daniel Yazgi, and Marianne Hatzopoulou
Geosci. Model Dev., 17, 3579–3597, https://doi.org/10.5194/gmd-17-3579-2024,https://doi.org/10.5194/gmd-17-3579-2024, 2024
Short summary
Assimilation of GNSS tropospheric gradients into the Weather Research and Forecasting (WRF) model version 4.4.1
Rohith Thundathil, Florian Zus, Galina Dick, and Jens Wickert
Geosci. Model Dev., 17, 3599–3616, https://doi.org/10.5194/gmd-17-3599-2024,https://doi.org/10.5194/gmd-17-3599-2024, 2024
Short summary
Identifying atmospheric rivers and their poleward latent heat transport with generalizable neural networks: ARCNNv1
Ankur Mahesh, Travis A. O'Brien, Burlen Loring, Abdelrahman Elbashandy, William Boos, and William D. Collins
Geosci. Model Dev., 17, 3533–3557, https://doi.org/10.5194/gmd-17-3533-2024,https://doi.org/10.5194/gmd-17-3533-2024, 2024
Short summary
Assessing acetone for the GISS ModelE2.1 Earth system model
Alexandra Rivera, Kostas Tsigaridis, Gregory Faluvegi, and Drew Shindell
Geosci. Model Dev., 17, 3487–3505, https://doi.org/10.5194/gmd-17-3487-2024,https://doi.org/10.5194/gmd-17-3487-2024, 2024
Short summary
Bergen metrics: composite error metrics for assessing performance of climate models using EURO-CORDEX simulations
Alok K. Samantaray, Priscilla A. Mooney, and Carla A. Vivacqua
Geosci. Model Dev., 17, 3321–3339, https://doi.org/10.5194/gmd-17-3321-2024,https://doi.org/10.5194/gmd-17-3321-2024, 2024
Short summary

Cited articles

Bei, N., Wu, J., Elser, M., Feng, T., Cao, J., El-Haddad, I., Li, X., Huang, R., Li, Z., Long, X., Xing, L., Zhao, S., Tie, X., Prévôt, A. S. H., and Li, G.: Impacts of meteorological uncertainties on the haze formation in Beijing–Tianjin–Hebei (BTH) during wintertime: a case study, Atmos. Chem. Phys., 17, 14579–14591, https://doi.org/10.5194/acp-17-14579-2017, 2017. 
Bengtsson, L. and Gustavsson, N.: Assimilation of nonsynoptic observations, Tellus, 24, 383–399, 1972. 
Birgin, E. G., Martinez, J. M., and Raydan, M.: Algorithm 813: SPG – software for convex-constrained optimization, ACM. Trans. Math. Softw., 27, 340–349, 2001. 
Bishop, C., Etherton, B. J., and Majumdar, S. J.: Adaptive sampling with the ensemble transform Kalman filter. Part I: Theoretical aspects, Mon. Weather Rev., 129, 420–436, 2001. 
Chen, B., Mu, M., and Qin, X. H.: The Impact of Assimilating Dropwindsonde Data Deployed at Different Sites on Typhoon Track Forecasts, Mon. Weather Rev., 141, 2669–2682, 2013. 
Download
Short summary
An approach is proposed to refine a ground meteorological observation network to improve the PM2.5 forecasts in the Beijing–Tianjin–Hebei region. A cost-effective observation network is obtained and makes the relevant PM2.5 forecasts assimilate fewer observations but achieve the forecasting skill comparable to or higher than that obtained by assimilating all ground station observations, suggesting that many of the current ground stations can be greatly scattered to avoid much unnecessary work.