Articles | Volume 13, issue 1
https://doi.org/10.5194/acp-13-269-2013
https://doi.org/10.5194/acp-13-269-2013
Research article
 | 
11 Jan 2013
Research article |  | 11 Jan 2013

Assimilation of ground versus lidar observations for PM10 forecasting

Y. Wang, K. N. Sartelet, M. Bocquet, and P. Chazette

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Cited articles

Baker, D. F., BÖsch, H., Doney, S. C., O'Brien, D., and Schimel, D. S.: Carbon source/sink information provided by column CO2 measurements from the Orbiting Carbon Observatory, Atmos. Chem. Phys., 10, 4145–4165, https://doi.org/10.5194/acp-10-4145-2010, 2010.
Balgovind, R., Dalcher, A., Ghil, M., and Kalnay, E.: A Stochastic- Dynamic Model for the Spatial Structure of Forecast Error Statistics, Mon. Weather Rev., 111, 701–722, 1983.
Barker, J. and Tingey, D. T. : Air Pollution Effects on Biodiversity, 304 pp., Springer, New York, USA, 1992.
Benedetti, A. and Fisher, M. : Background error statistics for aerosols, Q. J. Roy. Meteor. Soc., 133, 391–405, 2007.
Berthier, S., Chazette, P., Couvert, P., Pelon, J., Dulac, F., Thieuleux, F., Moulin, C., and Pain T. : Desert dust aerosol columnar properties over ocean and continental Africa from Lidar in-Space Technology Experiment (LITE) and Meteosat synergy, J. Geophys. Res., 111, D21202, https://doi.org/10.1029/2005JD006999, 2006.
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