Evaluation of Mixing-Height Retrievals from Automatic Profiling Lidars and Ceilometers in View of Future Integrated Networks in Europe

Abstract

The determination of the depth of daytime and nighttime mixing layers must be known very accurately to relate boundary-layer concentrations of gases or particles to upstream fluxes. The mixing-height is parametrized in numerical weather prediction models, so improving the determination of the mixing height will improve the quality of the estimated gas and particle budgets. Datasets of mixing-height diurnal cycles with high temporal and spatial resolutions are sought by various end users. Lidars and ceilometers provide vertical profiles of backscatter from aerosol particles. As aerosols are predominantly concentrated in the mixing layer, lidar backscatter profiles can be used to trace the depth of the mixing layer. Large numbers of automatic profiling lidars and ceilometers are deployed by meteorological services and other agencies in several European countries providing systems to monito

Lidar-based remote sensing of atmospheric boundary layer height over land and ocean

“…Lidar provides direct measurements of aerosol profiles within the ABL. Several methods, such as the threshold method, gradient method, and variance method, have been developed to determine BLH by using lidar backscatter measurements (Hooper and Eloranta, 1986;Flamant et al, 1997;Menut et al, 1999;Sicard et al, 2006;Lammert and Bösenberg, 2006;Martucci et al, 2007;Emeis et al, 2008;Jordan et al, 2010;Haeffelin et al, 2012). However, the detected aerosol layers are not always consistent with ABL thermodynamical structures because aerosol vertical structures are affected by other factors.…”

Improved mixing height monitoring through a combination of lidar and radon measurements

“…Of these steps, attribution poses the larger challenge (Haeffelin et al, 2012). Indeed the information available from an elastic-scattering lidar may be insufficient for successful attribution, so some schemes incorporate supplementary information, either from model output (Di Giuseppe et al, 2012) or additional sensors (Emeis et al, 2004).…”

“…Mixing heights were derived following a procedure based on the "STRAT-2D" method (Haeffelin et al, 2012). For each five minute block, S was averaged, and then the results arranged in a 2-D array as a function of time and range.…”

“…Under these conditions, collocating the lidar and radon detector might reduce, or remove, the observed lag between the two measurements. Furthermore, the seemingly incorrect attribution on 7 May could perhaps be rectified by using a more sophisticated merging algorithm, as might be achieved by applying the additional constraints described by Haeffelin et al (2012). Nevertheless, there will be days where the merging procedure fails or produces uncertain results.…”

“…ceilometers) can also be used for determining mixing height (Münkel, 2007;Emeis et al, 2009Emeis et al, , 2012. Ceilometers have lower signal-to-noise ratios than lidars, which can make mixing height detection more difficult, but are less expensive to purchase and maintain and are becoming deployed more widely in growing networks (Haeffelin et al, 2012). The ongoing deployment of lidars, and ceilometers in particular, means there is potential to see meaningful outcomes from improvements to mixing height detection algorithms.…”