Tentative detection of clear-air turbulence using a ground-based Rayleigh lidar

Abstract

Atmospheric gravity waves and turbulence generate small-scale fluctuations of wind, pressure, density, and temperature in the atmosphere. These fluctuations represent a real hazard for commercial aircraft and are known by the generic name of clear-air turbulence (CAT). Numerical weather prediction models do not resolve CAT and therefore provide only a probability of occurrence. A ground-based Rayleigh lidar was designed and implemented to remotely detect and characterize the atmospheric variability induced by turbulence in vertical scales between 40 m and a few hundred meters. Field measurements were performed at Observatoire de Haute-Provence (OHP, France) on 8 December 2008 and 23 June 2009. The estimate of the mean squared amplitude of bidimensional fluctuations of lidar signal showed excess compared to the estimated contribution of the instrumental noise. This excess can be attributed to atmospheric turbulence with a 95% confidence level. During the first night, data from collocated stratosphere-troposphere (ST) radar were available. Altitudes of the turbulent layers detected by the lidar were roughly consistent with those of layers with enhanced radar echo. The derived values of turbulence parameters Cn2 or CT2 were in the range of those published in the literature using ST radar data. However, the detection was at the limit of the instrumental noise and additional measurement campaigns are highly desirable to confirm these initial results. This is to our knowledge the first successful attempt to detect CAT in the free troposphere using an incoherent Rayleigh lidar system. The built lidar device may serve as a test bed for the definition of embarked CAT detection lidar systems aboard airliners.

Impact of pitch angle fluctuations on airborne lidar forward sensing along the flight direction

“…15). The thorough analysis of CAT detection was performed in Vrancken et al (2016), Veerman et al (2014), and Hauchecorne et al (2016). Here we discuss the examples of strong backscattered signal variations caused by pitch angle fluctuations which were sometimes observed during the experiments.…”

“…For a ground-based lidar with an upwards-directed beam, L equals the altitude of the scattering volume; the intensity fluctuations of lidar response I are proportional to the turbulence strength. This permits solving for turbulence strength distribution along the line of sight (Hauchecorne et al, 2016;Keckhut et al, 2015). As the wind drift occurs, the altitudinal cross section of long-living aerosol clusters can be inferred from I (L, t) relief images in the (L, t) plane as bars, with width depending on both the wind speed and the 3-D cluster structure (Haarig et al, 2016;Hoareau et al, 2012).…”

“…The turbulence area detection was based on the lidar measurements of the fluctuation in the density of air associated with the turbulent wind (Feneyrou, 2009;Vrancken et al, 2016;Hauchecorne et al, 2016). This idea was tested at first with the use of the ground-based lidar (Hauchecorne et al, 2016). A detailed discussion of the C 2 n evaluation method and experimental examples of turbulence lidar signal responses with estimated values of C 2 n can be found, for example, in Sect.…”

“…A detailed discussion of the C 2 n evaluation method and experimental examples of turbulence lidar signal responses with estimated values of C 2 n can be found, for example, in Sect. 4b of Hauchecorne et al (2016) or in Vrancken et al (2016).…”

Aviation Turbulence

“…The above approach has been tested within the French MMEDTAC project (Hauchecorne et al 2010;Hauchecorne et al 2016), relying on aerosol-devoid observation times. Within the European project DELICAT, the DLR built such a UV lidar for operation on the Dutch Cessna Citation 2 (Vrancken et al 2010).…”