New technique for retrieval of atmospheric temperature profiles from Rayleigh-scatter lidar measurements using nonlinear inversion

Abstract

The conventional method of calculating atmospheric temperature profiles using Rayleigh-scattering lidar measurements has limitations that necessitate abandoning temperatures retrieved at the greatest heights, due to the assumption of a pressure value required to initialize the integration at the highest altitude. An inversion approach is used to develop an alternative way of retrieving nightly atmospheric temperature profiles from the lidar measurements. Measurements obtained by the Purple Crow lidar facility located near The University of Western Ontario are used to develop and test this new technique. Our results show temperatures can be reliably retrieved at all heights where measurements with adequate signal-to-noise ratio exist. A Monte Carlo technique was developed to provide accurate estimates of both the systematic and random uncertainties for the retrieved nightly average temperature profile. An advantage of this new method is the ability to seed the temperature integration from the lowest rather than the greatest height, where the variability of the pressure is smaller than in the mesosphere or lower thermosphere and may in practice be routinely measured by a radiosonde, rather than requiring a rocket or satellite-borne measurement. Thus, this new technique extends the altitude range of existing Rayleigh-scatter lidars 10-15 km, producing the equivalent of four times the power-aperture product.

Lidar temperature series in the middle atmosphere as a reference data set – Part 1: Improved retrievals and a 20-year cross-validation of two co-located French lidars

“…All channels are sampled using a Licel digital transient recorder with a record time of 0.1 µs, which corresponds to a vertical resolution of 15 m. The high-and low-gain Raleigh channels are electronically gated at 22 and 12 km, respectively, to avoid damaging the photomultipliers with large signal returns. Further details can be found in Keckhut et al (1993) and Khaykin et al (2017).…”

A middle latitude Rayleigh-scatter lidar temperature climatology determined using an optimal estimation method

“…Due to the high uncertainties caused by the pressure estimation from a model, the top 10 to 15 km are required to be eliminated from the top of each temperature profile to have accurate results (e.g. Khanna et al (2012)). The HC method gives a statistical uncertainty of the calculated temperature which assumes the 15 measurements follow Poisson statistics.…”

Extending and Merging the Purple Crow Lidar Temperature Climatologies Using the Inversion Method

“…There are two methods for retrieving temperature from lidar measurements, these methods are called the conventional method which was first proposed by Hauchecorne and Chanin in 1980 and the inversion method presented by Khanna et al, 2012. Each approach has its own deficiencies and benefits.…”

“…Since the inversion method does not provide statistical model or model parameter uncertainties, the uncertainties of its results can be estimated using Monte Carlo techniques, whereas in the conventional method the uncertainties are calculated analytically. Details of the inversion method are explained in Khanna et al, (2012). In order to extend our results to include an extra 10 km on top, the inversion method is used to perform temperature climatology for the PCL High Level Rayleigh channel.…”

“…Temperature retrievals from Rayleigh-scattering lidar measurements have been performed using the methods by Hauchecorne and Chanin (1980; henceforth HC) and Khanna et al (2012). Argall and Sica (2007) Khanna et al (2012) used the inversion technique to retrieve atmospheric temperature profiles and found that it had advantages over the HC method. This paper presents an extension of the PCL climatologies created by Argall and Sica (2007) and Iserhienrhien et al (2013).…”