Articles | Volume 9, issue 8
Development and technical paper
10 Aug 2016
Development and technical paper |  | 10 Aug 2016

Background error covariance with balance constraints for aerosol species and applications in variational data assimilation

Zengliang Zang, Zilong Hao, Yi Li, Xiaobin Pan, Wei You, Zhijin Li, and Dan Chen

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Cited articles

Bannister, R. N.: A review of forecast error covariance statistics in atmospheric variational data assimilation. I: Characteristics and measurements of forecast error covariances, Q. J. Roy. Meteor. Soc., 134, 1951–1970, 2008a.
Bannister, R. N.: A review of forecast error covariance statistics in atmospheric variational data assimilation. II: Modelling the forecast error covariance statistics, Q. J. Roy. Meteor. Soc., 134, 1971–1996, 2008b.
Barker, D. M., Huang, W., Guo, Y. R., and Xiao, Q. N.: A Three-Dimensional (3DVAR) data assimilation system for use with MM5: implementation and initial results, Mon. Weather Rev., 132, 897–914, 2004.
Benedetti, A. and Fisher, M.: Background error statistics for aerosols, Q. J. Roy. Meteor. Soc., 133, 391–405, 2007.
Chen, Y., Rizvi, S., Huang, X., Min, J., and Zhang, X.: Balance characteristics of multivariate background error covariances and their impact on analyses and forecasts in tropical and Arctic regions, Meteorol. Atmos. Phys., 121, 79–98, 2013.
Short summary
The aerosol data assimilation and forecasts can be improved by adopting balance constraints that spread observation information across variables, thus producing balanced initial distributions. Surface and aircraft aerosol observations were assimilated to demonstrate the impact of the balance constraints. The results showed that the forecasting experiment with balance constraints is more skillful and durable than the experiment without balance constraints.