Retrieval of temperature from a multiple channel pure rotational Raman backscatter lidar using an optimal estimation method

Abstract

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 clear and cloudy 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 daytime and nighttime.

Solar Background Radiation Temperature Calibration of a Pure Rotational Raman Lidar

“…The agreement between the external and background methods is within a mean difference of less than 5%. Temperatures were retrieved from the lidar measurements using the OEM-based algorithm presented by Mahagammulla Gamage et al (2019). Only digital channel measurements were used for 130 the retrievals as the analog measurements introduced biases that we were not able to correct or explain.…”

“…June 2013, and the calibration constant C * (t 0 ) was computed by averaging over the 5 to 8 km altitude range. A filtering method, reliant on the cost associated with the OEM retrieval process was implemented to eliminate bad retrievals from both datasets (Mahagammulla Gamage et al, 2019). Profiles with a retrieval cost lower than 0.5 or higher than 10 were discarded.…”

“…Enhancing and refining these calibration methods are important steps toward achieving greater accuracy and reducing uncertainties in our investigations. Mahagammulla Gamage et al (2019) proposed a method for temperature retrieval that considers the full Raman lidar equation, without requiring the assumption of an empirical calibration function. This approach mitigates uncertainties when contrasted with the utilization of empirical calibration functions, which could potentially introduce substantial errors exceeding 1 K, particularly in cases involving larger temperature ranges (Behrendt, 2005).…”

On the temperature stability requirements of free-running Nd:YAG lasers for atmospheric temperature profiling through the rotational Raman technique

“…The power ratio of the filter outputs corresponding to the different regions of the spectrum needs to be calibrated to retrieve the atmospheric temperature. This is usually done by comparison with a radiosonde profile (Hammann et al, 2015), although in-situ calibrations using local light sources (Vaughan et al, 1993), or by constructing a model of the power ratio between the outputs of the filters for high-and low-quantum numbers (Mahagammulla Gamage et al, 2019) are also described in the literature. For the calibration to be valid over long periods, the stability of the system to ensure that the filters' response keeps constant in time is of paramount importance.…”

“…Of more concern regarding system stability is the laser wavelength. Although some systems use free-running lasers (Di Girolamo et al, 2004;Mahagammulla Gamage et al, 2019), laser frequency stability is achieved in many systems through the use of injection-seeded lasers, where the stability and spectral purity of the seeder is transferred to the host laser (Behrendt and Reichardt, 2000;Behrendt et al, 2002;Behrendt et al, 2004;Lange et al, 2019), which is forced to operate in a single longitudinal mode.…”