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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union
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Volume 11, issue 11 | Copyright
Atmos. Meas. Tech., 11, 6043-6058, 2018
https://doi.org/10.5194/amt-11-6043-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 08 Nov 2018

Research article | 08 Nov 2018

Improvements to a long-term Rayleigh-scatter lidar temperature climatology by using an optimal estimation method

Ali Jalali1, Robert J. Sica1,2, and Alexander Haefele2,1 Ali Jalali et al.
  • 1Department of Physics and Astronomy, the University of Western Ontario, London, Canada
  • 2Federal Office of Meteorology and Climatology, MeteoSwiss, Payerne, Switzerland

Abstract. Hauchecorne and Chanin (1980) developed a robust method to calculate middle-atmosphere temperature profiles using measurements from Rayleigh-scatter lidars. This traditional method has been successfully used to greatly improve our understanding of middle-atmospheric dynamics, but the method has some shortcomings regarding the calculation of systematic uncertainties and the vertical resolution of the retrieval. Sica and Haefele (2015) have shown that the optimal estimation method (OEM) addresses these shortcomings and allows temperatures to be retrieved with confidence over a greater range of heights than the traditional method. We have calculated a temperature climatology from 519 nights of Purple Crow Lidar Rayleigh-scatter measurements using an OEM. Our OEM retrieval is a first-principle retrieval in which the forward model is the lidar equation and the measurements are the level-0 count returns. It includes a quantitative determination of the top altitude of the retrieved temperature profiles, the evaluation of nine systematic plus random uncertainties, and the vertical resolution of the retrieval on a profile-by-profile basis. Our OEM retrieval allows for the vertical resolution to vary with height, extending the retrieval in altitude 5 to 10km higher than the traditional method. It also allows the comparison of the traditional method's sensitivity to two in-principle equivalent methods of specifying the seed pressure: using a model pressure seed versus using a model temperature combined with the lidar's density measurement to calculate the seed pressure. We found that the seed pressure method is superior to using a model temperature combined with the lidar-derived density. The increased altitude capability of our OEM retrievals allows for a comparison of the Rayleigh-scatter lidar temperatures throughout the entire altitude range of the sodium lidar temperature measurements. Our OEM-derived Rayleigh temperatures are shown to have improved agreement relative to our previous comparisons using the traditional method, and the agreement of the OEM-derived temperatures is the same as the agreement between existing sodium lidar temperature climatologies. This detailed study of the calculation of the new Purple Crow Lidar temperature climatology using the OEM establishes that it is both highly advantageous and practical to reprocess existing Rayleigh-scatter lidar measurements that cover long time periods, during which time the lidar may have undergone several significant equipment upgrades, while gaining an upper limit to useful temperature retrievals equivalent to an order of magnitude increase in power-aperture product due to the use of an OEM.

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We use 16 years of lidar (laser radar) temperature measurements of the middle atmosphere to form a climatology for use in studying atmospheric temperature change using an optimal estimation method (OEM). Using OEM allows us to calculate a complete systematic and random uncertainty budget and allows for an additional 10–15 km in altitude for the measurement to be used, improving our ability to detect atmospheric temperature change up to 100 km of altitude.
We use 16 years of lidar (laser radar) temperature measurements of the middle atmosphere to form...
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