Articles | Volume 12, issue 4
https://doi.org/10.5194/amt-12-2097-2019
https://doi.org/10.5194/amt-12-2097-2019
Research article
 | 
04 Apr 2019
Research article |  | 04 Apr 2019

Optimal estimation method retrievals of stratospheric ozone profiles from a DIAL

Ghazal Farhani, Robert J. Sica, Sophie Godin-Beekmann, and Alexander Haefele

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Cited articles

Andrews, D. G., Holton, J. R., and Leovy, C. B.: Middle atmosphere dynamics, 40, Academic press, London, UK, 1987. a
Ball, W. T., Alsing, J., Mortlock, D. J., Staehelin, J., Haigh, J. D., Peter, T., Tummon, F., Stübi, R., Stenke, A., Anderson, J., Bourassa, A., Davis, S. M., Degenstein, D., Frith, S., Froidevaux, L., Roth, C., Sofieva, V., Wang, R., Wild, J., Yu, P., Ziemke, J. R., and Rozanov, E. V.: Evidence for a continuous decline in lower stratospheric ozone offsetting ozone layer recovery, Atmos. Chem. Phys., 18, 1379–1394, https://doi.org/10.5194/acp-18-1379-2018, 2018. a
Donovan, D. P., Bird, J. C., Whiteway, J. A., Duck, T. J., Pal, S. R., and Carswell, A. I.: Lidar observations of stratospheric ozone and aerosol above the Canadian high arctic during the 1994–95 winter, Geophys. Res. Lett., 22, 3489–3492, 1995. a
Eriksson, P., Jimenez, C., and Buehler, S.: Qpack, a general tool for instrument simulation and retrieval work, J. Quant. Spectrosc. Ra., 91, 47–64, 2005. a, b
Farman, J. C., Gardiner, B. G., and Shanklin, J. D.: Large losses of total ozone in Antarctica reveal seasonal ClOx∕NOx interaction, Nature, 315, 207, 1985. a
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Short summary
This paper presents a new application of the optimal estimation method (OEM) for the retrieval of ozone density profiles from DIAL measurements. The OEM results show excellent agreement with coincident ozonesonde measurements, with improved resolution over the traditional technique. The method also provides averaging kernels (facilitating comparison with other instruments), the vertical resolution of the retrieval, and a complete random and systematic uncertainty budget.