A generalised background correction algorithm for a Halo Doppler lidar and its application to data from Finland

Abstract

Abstract. Current commercially available Doppler lidars provide an economical and robust solution for measuring vertical and horizontal wind velocities, together with the ability to provide co- and cross-polarised backscatter profiles. The high temporal resolution of these instruments allows turbulent properties to be obtained from studying the variation in radial velocities. However, the instrument specifications mean that certain characteristics, especially the background noise behaviour, become a limiting factor for the instrument sensitivity in regions where the aerosol load is low. Turbulent calculations require an accurate estimate of the contribution from velocity uncertainty estimates, which are directly related to the signal-to-noise ratio. Any bias in the signal-to-noise ratio will propagate through as a bias in turbulent properties. In this paper we present a method to correct for artefacts in the background noise behaviour of commercially available Doppler lidars and reduce the signal-to-noise ratio threshold used to discriminate between noise, and cloud or aerosol signals. We show that, for Doppler lidars operating continuously at a number of locations in Finland, the data availability can be increased by as much as 50 % after performing this background correction and subsequent reduction in the threshold. The reduction in bias also greatly improves subsequent calculations of turbulent properties in weak signal regimes.

Atmospheric Boundary Layer Classification With Doppler Lidar

“…The ABL classification method requires the following lidar quantities as inputs: attenuated backscatter coefficient, vertical velocity skewness, dissipation rate of turbulent kinetic energy (TKE), vertical profiles of horizontal wind, and vector wind shear. These lidar quantities are derived from the data corrected following Manninen et al () and generated at the original vertical resolution and selected temporal resolution, unless otherwise mentioned. The choice of temporal resolution depends on the signal strength and data availability, that is, the aerosol loading in the region where the Halo lidar is located; more averaging is required in clean air situations.…”

“…The instrument parameters during standard operation for the two instruments considered here are given in Table . To obtain reliable uncertainty estimates, Manninen et al () showed that the Halo lidar signal output often requires further processing to account for artifacts in the instrument background signal. This extra processing also has a major impact on the data availability, especially in regions with a low aerosol loading.…”

response

“…The absolute calibration coefficient c absolute (t) may be constant in time c absolute (t) = c absolute (Hopkin et al, 2016). A laser at the CL31 operating wavelength (≈ 905 nm) is sensitive to absorption of water vapour in the atmosphere, which can have implications for the absolute calibration (Markowicz et al, 2008;Wiegner and Gasteiger, 2015). As evaluation of absolute calibration techniques is beyond the scope of this study, for simplicity the impact of this external calibration is neglected (i.e.…”

“…Xie and Zhou (2005) propose a method for SNR calculations for lidar observations whereby the signal profile is approximated by a linear fit to the readily averaged profile along set range bins and assigning the deviations from that fit to the noise. Markowicz et al (2008) apply this method to observations of a Vaisala CT25K averaged over 200 s. These SNR values indicate that the observations are only reliable within the ABL (absence of clouds) and it is stated that an SNR = 10 marks "a limiting value of detection" (Markowicz et al, 2008). Assuming there are no temporal variations in the atmosphere probed by several consecutive observations (e.g.…”

Sesquiterpenes identified as key species for atmospheric chemistry in boreal forest by terpenoid and OVOC measurements

“…The VAD scan and 12-beam vertical stare were scheduled every 30 min at Hyytiälä; other scan types operated during the 30-min measurement cycle were not utilized in this study. The lidar data was corrected for a background noise artefact according to Manninen et al (2016). After 25 this correction a signal-to-noise-ratio threshold of 0.001 was applied to the data.…”