Atmospheric Boundary Layer Classification With Doppler Lidar

Abstract

We present a method using Doppler lidar data for identifying the main sources of turbulent mixing within the atmospheric boundary layer. The method identifies the presence of turbulence and then assigns a turbulent source by combining several lidar quantities: attenuated backscatter coefficient, vertical velocity skewness, dissipation rate of turbulent kinetic energy, and vector wind shear. Both buoyancy-driven and shear-driven situations are identified, and the method operates in both clear-sky and cloud-topped conditions, with some reservations in precipitation. To capture the full seasonal cycle, the classification method was applied to more than 1 year of data from two sites, Hyytiälä, Finland, and Jülich, Germany. Analysis showed seasonal variation in the diurnal cycle at both sites; a clear diurnal cycle was observed in spring, summer, and autumn seasons, but due to their respective latitudes, a weaker cycle in winter at Jülich, and almost non-existent at Hyytiälä. Additionally, there are significant contributions from sources other than convective mixing, with cloud-driven mixing being observed even within the first 500 m above ground. Also evident is the considerable amount of nocturnal mixing within the lowest 500 m at both sites, especially during the winter. The presence of a low-level jet was often detected when sources of nocturnal mixing were diagnosed as wind shear. The classification scheme and the climatology extracted from the classification provide insight into the processes responsible for mixing within the atmospheric boundary layer, how variable in space and time these can be, and how they vary with location.

Erosion of the nocturnal boundary layer in the central Amazon during the dry season

“…Doppler LIDAR measurements were conducted to estimate the height of the PBL. The Lidar is a stand-alone remote sensing instrument that provides measurements of radial velocity and backscatter attenuated in time (Manninen et al 2018). The Lidar has superior hemispheric scanning capability, allowing the three-dimensional mapping of turbulent fluxes within the PBL.…”

The Structure of the Convective Boundary Layer as Deduced from Topological Invariants

“…While the investigation put forth above is mainly of illustrative character, we see merit in this methodological approach for a number of applications. First, our results suggest that a classification of boundary-layer turbulence by its source as introduced, for instance, by Harvey et al (2013) and Manninen et al (2018) can also be based on the present approach, which would dramatically simplify the number of thresholds and the amount of data involved in such classification. Second, the algorithmic approach put forth here can be used in the emerging field of Doppler scans from lidars where resolved fields of atmospheric flow, in particular of the vertical velocity, are available (Lothon et al 2009;Barlow et al 2011).…”

A Review of Progress and Applications of Pulsed Doppler Wind LiDARs

“…Analysis of data measured by a vertical staring LiDAR and a sonic anemometer at the Chilbolton Observatory in southern England from 1 June 2008 to 31 May 2011 indicated that the stable boundary layer with clear skies was the most common type, occurring 40% of the time [151]. Following Harvey et al [151], Manninen et al [152] proposed a method to classify turbulent mixing within the boundary layer and identified a turbulent source with the aid of the attenuated backscatter coefficient, the vertical velocity skewness, the dissipation rate of turbulent kinetic energy, the vertical profiles of horizontal wind, and the vectorial wind shear estimated from LiDAR measurements.…”

“…Analysis of data measured at Hyytiälä, Finland and Jülich, Germany in 2015 and 2016 showed that surface-driven convection was a dominant source of turbulent mixing during spring, summer and autumn. In addition, low level jets were also an important source of nocturnal mixing [152].…”