Articles | Volume 17, issue 11
Research article
15 Jun 2017
Research article |  | 15 Jun 2017

Assimilation of satellite NO2 observations at high spatial resolution using OSSEs

Xueling Liu, Arthur P. Mizzi, Jeffrey L. Anderson, Inez Y. Fung, and Ronald C. Cohen

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Cited articles

Aksoy, A., Zhang, F. and Nielsen-Gammon, J. W.: Ensemble-Based Simultaneous State and Parameter Estimation in a Two-Dimensional Sea-Breeze Model, Mon. Weather Rev., 134, 2951–2970,, 2006.
Anderson, J., Hoar, T., Raeder, K., Liu, H., Collins, N., Torn, R., and Avellano, A.: The Data Assimilation Research Testbed: A Community Facility, Bull. Am. Meteorol. Soc., 90, 1283–1296,, 2009.
Anderson, J. L.: An Ensemble Adjustment Kalman Filter for Data Assimilation, Mon. Weather Rev., 129, 2884–2902, 2001.
Anderson, J. L. and Collins, N.: Scalable Implementations of Ensemble Filter Algorithms for Data Assimilation, J. Atmos. Ocean. Tech., 24, 1452–1463,, 2007.
Arellano Jr., A. F., Raeder, K., Anderson, J. L., Hess, P. G., Emmons, L. K., Edwards, D. P., Pfister, G. G., Campos, T. L., and Sachse, G. W.: Evaluating model performance of an ensemble-based chemical data assimilation system during INTEX-B field mission, Atmos. Chem. Phys., 7, 5695–5710,, 2007.
Short summary
We describe a chemical ensemble data assimilation system with high spatial and temporal resolution that simultaneously adjusts meteorological and chemical variables and NOx emissions. We investigate the sensitivity of emission inversions to the accuracy and uncertainty of the wind analyses and the emission update scheme. The results provide insight into optimal uses of the observations from future geostationary satellite missions that will observe atmospheric composition.
Final-revised paper