Articles | Volume 16, issue 14
https://doi.org/10.5194/gmd-16-4171-2023
https://doi.org/10.5194/gmd-16-4171-2023
Development and technical paper
 | 
25 Jul 2023
Development and technical paper |  | 25 Jul 2023

Implementation and application of ensemble optimal interpolation on an operational chemistry weather model for improving PM2.5 and visibility predictions

Siting Li, Ping Wang, Hong Wang, Yue Peng, Zhaodong Liu, Wenjie Zhang, Hongli Liu, Yaqiang Wang, Huizheng Che, and Xiaoye Zhang

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Cited articles

Belyaev, K., Kuleshov, A., Smirnov, I., and Tanajura, C. A. S.: Generalized Kalman Filter and Ensemble Optimal Interpolation, Their Comparison and Application to the Hybrid Coordinate Ocean Model, Mathematics, 9, 2371, https://doi.org/10.3390/math9192371, 2021. 
Bocquet, M., Elbern, H., Eskes, H., Hirtl, M., Žabkar, R., Carmichael, G. R., Flemming, J., Inness, A., Pagowski, M., Pérez Camaño, J. L., Saide, P. E., San Jose, R., Sofiev, M., Vira, J., Baklanov, A., Carnevale, C., Grell, G., and Seigneur, C.: Data assimilation in atmospheric chemistry models: current status and future prospects for coupled chemistry meteorology models, Atmos. Chem. Phys., 15, 5325–5358, https://doi.org/10.5194/acp-15-5325-2015, 2015. 
Castruccio, F. S., Karspeck, A. R., Danabasoglu, G., Hendricks, J., Hoar, T., Collins, N., and Anderson, J. L.: An EnOI-Based Data Assimilation System With DART for a High-Resolution Version of the CESM2 Ocean Component, J. Adv. Model. Earth Sy., 12, e2020MS002176, https://doi.org/10.1029/2020ms002176, 2020. 
Chen, D., Xue, J., Yang, X., Zhang, H., Shen, X., Hu, J., Wang, Y., Ji, L., and Chen, J.: New generation of multi-scale NWP system (GRAPES): general scientific design, Chinese Sci. Bull., 53, 3433–3445, https://doi.org/10.1007/s11434-008-0494-z, 2008. 
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Short summary
Optimizing the initial state of atmospheric chemistry model input is one of the most essential methods to improve forecast accuracy. Considering the large computational load of the model, we introduce an ensemble optimal interpolation scheme (EnOI) for operational use and efficient updating of the initial fields of chemical components. The results suggest that EnOI provides a practical and cost-effective technique for improving the accuracy of chemical weather numerical forecasts.
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