Atmos. Chem. Phys. Discuss., 11, 7811-7849, 2011
www.atmos-chem-phys-discuss.net/11/7811/2011/
doi:10.5194/acpd-11-7811-2011
© Author(s) 2011. This work is distributed
under the Creative Commons Attribution 3.0 License.
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This discussion paper has been under review for the journal Atmospheric Chemistry and Physics (ACP). Please refer to the corresponding final paper in ACP.
Improvement of ozone forecast over Beijing based on ensemble Kalman filter with simultaneous adjustment of initial conditions and emissions
X. Tang, J. Zhu, Z. F. Wang, and A. Gbaguidi
LAPC and ICCES, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China

Abstract. We performed ozone data assimilation by simultaneously adjusting the ozone initial conditions, precursor initial conditions and emissions based on the Ensemble Kalman Filter (EnKF) and assessed its impacts on ozone modeling and forecasting in Beijing and nearby regions. A high-resolution regional air quality model and a newly established regional monitoring network covering Beijing and its surrounding areas were employed. At each assimilation cycle, the forecast error covariance was sampled from a set of forecast ensembles that were generated by perturbing ozone precursor initial conditions, emissions, photolysis rates and deposition velocity. A model-error module and a local analysis scheme have been introduced to reduce the impact of filter divergence and spurious correlation that accompanied with EnKF. The results showed significant improvement of 1-hour ozone forecast in Beijing and its surrounding areas through separately adjusting ozone initial conditions, precursor initial conditions and emissions with ozone observations. However, adjustment of precursor initial conditions and emissions had minor effect on the 1-hour ozone forecast in suburban area. The best ozone forecast skill was obtained through jointly adjusting ozone initial conditions, NOx and VOC initial conditions and emissions. The root mean square errors of 1-hour ozone forecast at urban sites and suburban sites decreased by 54% and 59% respectively compared with those in free run. Furthermore, the specific impacts of observations from urban and suburban sites on ozone data assimilation were evaluated by implementing sensitivity experiments. Both urban and suburban sites were found to be very important for the improvement of regional ozone forecast. The importance of observational data at urban sites was particularly highlighted through its role in constraining the uncertainty of precursor initial conditions and emission rates. Further improvement of regional ozone forecast might therefore be expected with more routine regional air pollution monitoring stations.

Citation: Tang, X., Zhu, J., Wang, Z. F., and Gbaguidi, A.: Improvement of ozone forecast over Beijing based on ensemble Kalman filter with simultaneous adjustment of initial conditions and emissions, Atmos. Chem. Phys. Discuss., 11, 7811-7849, doi:10.5194/acpd-11-7811-2011, 2011.
 
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