Vertical distribution of gravity wave potential energy from long‐term Rayleigh lidar data at a northern middle‐latitude site

Abstract

In this paper, we use the Rayleigh lidar in order to give an overview of the gravity wave activity at a northern middle-latitude station at Haute-Provence Observatory (43.93°N, 5.71°E). In order to have access to perturbations with short time and vertical scales, at least in a statistical sense, we analyze raw lidar signals with a variance method. Sixteen years of lidar data sets are analyzed in this study. The results of the variability, climatology, and seasonal changes are reported. We observe night-to-night variability in gravity wave potential energy, which follows a lognormal distribution with a standard deviation ranging between 0.50 and 0.58 (base 10 logarithm). A monthly distribution of gravity waves is also obtained in the upper stratosphere and mesosphere. In the 30-50 km altitude range (the upper stratosphere), an annual cycle is clearly found with a maximum in winter and a minimum in summer. An annual cycle in the lower mesosphere is also observed with maximum in winter. In the upper mesosphere, a semiannual cycle is found at~75 km. At this altitude, the maximum gravity wave activity occurs in winter and in summer. A more pronounced summer maximum is observed (+25%). The summer maximum at Haute-Provence Observatory in the upper mesosphere is probably due to oblique propagation. Looking at the seasonally averaged profiles, it is possible to observe the preferential altitudes of energy dissipation. Gravity waves are dissipating abovẽ 70 km during all seasons, but there is relatively little dissipation at lower altitudes.

Convective gravity wave propagation and breaking in the stratosphere: comparison between WRF model simulations and lidar data

“…It is independent of data processing errors. More details about the variance method are presented in a recent study by Mzé et al (2014).…”

“…In order to have access to perturbations with short time and vertical scales, at least in a statistical sense, we analyse raw lidar signals with a variance method (Hauchecorne et al, 1994;Mzé et al, 2014). This method is based on the computation of the signal perturbations over short time and vertical intervals ( t, z) and on the summation of the square of these perturbations over a large number of elementary intervals ( T = tN t , Z = zN z ), which give an estimation of their variance.…”

Evaluation of methods for gravity wave extraction from middle-atmospheric lidar temperature measurements

“…Hence, we discuss the extraction of gravity waves from temperature data rather than atmospheric density, although most of the results can be applied to density measurements as well. For different methods of extracting gravity waves from density measurements see, e.g., Sica and Russell (1999), Thurairajah et al (2010) and Mzé et al (2014).…”

“…Perturbation profiles obtained through a fit of polynomial functions to the measured profiles are examined by, e.g., Whiteway and Carswell (1995), Duck et al (2001) and Alexander et al (2011). Mzé et al (2014) apply a variance method in order to determine perturbation profiles, while Chane-Ming et al (2000) use spectral filtering.…”

Temperature Climatology with Rayleigh Lidar Above Observatory of Haute-Provence: Dynamical Feedback

“…This is attributed to planetary wave activity, which strongly perturbs the zonal winds in the middle atmosphere, resulting in wave generation by adjustment of the unbalanced flow. The gravity wave potential energy has been derived using a variance method on the raw signal [7]. We observed night-to-night variations in the lidar measurements, and inter-annual variability in gravity wave activity based on 16 years of Rayleigh lidar data (30-85 km).…”