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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union
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Discussion papers
https://doi.org/10.5194/amt-2019-107
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-2019-107
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 13 May 2019

Research article | 13 May 2019

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Atmospheric Measurement Techniques (AMT).

Retrieval of Temperature From a Multiple Channel Pure Rotational Raman-Scatter Lidar Using an Optimal Estimation Method

Shayamila Mahagammulla Gamage1, Robert J. Sica1,2, Giovanni Martucci2, and Alexander Haefele2,1 Shayamila Mahagammulla Gamage et al.
  • 1Department of Physics and Astronomy, The University of Western Ontario, London, N6A 3K7, Canada
  • 2Federal Office of Meteorology and Climatology, MeteoSwiss, CH-1530 Payerne, Switzerland

Abstract. We present a new method for retrieving temperature from Pure Rotational Raman (PRR) lidar measurements. Our Optimal Estimation Method (OEM) used in this study uses the full physics of PRR scattering and does not require any assumption of the form for a calibration function nor does it require fitting of calibration factors over a large range of temperatures. The only calibration required is the estimation of the ratio of the lidar constants of the two PRR channels (coupling constant) that can be evaluated at a single or multiple height bins using a simple analytic expression. The uncertainty budget of our OEM retrieval includes both statistical and systematic uncertainties, including the uncertainty in the determination of the coupling constant on the temperature. We show that the error due to calibration can be reduced significantly using our method, in particular in the upper troposphere when calibration is only possible over a limited temperature range. Some other advantages of our OEM over the traditional Raman lidar temperature retrieval algorithm include not requiring correction or gluing to the raw lidar measurements, providing a cutoff height for the temperature retrievals that specifies the height to which the retrieved profile is independent of the a priori temperature profile, and the retrieval's vertical resolution as a function of height. The new method is tested on PRR temperature measurements from the MeteoSwiss Raman Lidar for Meteorological Observations system in different sky conditions, compared to temperature calculated using the traditional PRR calibration formulas, and validated with coincident radiosonde temperature measurements in clear and cloudy conditions during both day and night time.

Shayamila Mahagammulla Gamage et al.
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Shayamila Mahagammulla Gamage et al.
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Latest update: 18 Jul 2019
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Short summary
We present a new method for retrieving temperature from Pure Rotational Raman lidar measurements using an optimal estimation method. We show that the error due to calibration can be reduced significantly using our method. The new method is tested on PRR temperature measurements from the MeteoSwiss Raman Lidar for Meteorological Observations system in different sky conditions. The next step in this research is to assimilate the temperature profiles into models to help improve weather forecasts.
We present a new method for retrieving temperature from Pure Rotational Raman lidar measurements...
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