Since a few years, the number of active remote sensing systems has been rapidly increasing as national weather services started to build up networks of ceilometers. As ceilometers can be considered as "simple" backscatter lidars, it is obvious to investigate to which extent they can provide quantitative aerosol information. In this context, the calibration of the ceilometer is the most crucial point: whereas previous studies primarily have relied on the comparisons with co-incident sun photometer measurements and the Rayleigh calibration, we provide an absolute calibration of the ceilometer. The advantage of this approach is that backscatter profiles can be derived during daytime and nighttime, and even in cases when the signal-to-noise ratio of signals from the free troposphere is very low. Moreover, the retrieval can easily be automated. In this paper, we consider the Jenoptik CHM15kx-ceilometer. We discuss the methodology and the achievable accuracy and present a set of examples to highlight the wide range of applications, and the limitations. The achievable temporal resolution is of the order of a few minutes; the relative error of the particle backscatter coefficient is less than 10%. It is emphasized that the accuracy of extinction coefficients and – as a consequence – of the aerosol optical depth is limited due to the unknown lidar ratio. This is, however, an inherent problem of any backscatter lidar and not a special feature of the ceilometer.

The mixing layer height (MLH) is a measure for the vertical turbulent exchange within the boundary layer, which is one of the controlling factors for the dilution of pollutants emitted near the ground. Based on continuous MLH measurements with a Vaisala CL51 ceilometer and measurements from an air quality network, the relationship between MLH and near-surface pollutant concentrations has been investigated. In this context the uncertainty of the MLH retrievals and the representativeness of ground-based in situ measurements are crucial. We have investigated this topic by using data from the BAERLIN2014 campaign in Berlin, Germany, conducted from June to August 2014. To derive the MLH, three versions of the proprietary software BL-VIEW and a novel approach COBOLT were compared. It was found that the overall agreement is reasonable if mean diurnal cycles are considered. The main advantage of COBOLT is the continuous detection of the MLH with a temporal resolution of 10 min and a lower number of cases when the residual layer is misinterpreted as mixing layer. We have calculated correlations between MLH as derived from the different retrievals and concentrations of pollutants (PM₁₀, O₃ and NO_x) for different locations in the metropolitan area of Berlin. It was found that the correlations with PM₁₀ are quite different for different sites without showing a clear pattern, whereas the correlation with NO_x seems to depend on the vicinity of emission sources in main roads. In the case of ozone as a secondary pollutant, a clear correlation was found. We conclude that the effects of the heterogeneity of the emission sources, chemical processing and mixing during transport exceed the differences due to different MLH retrievals. Moreover, it seems to be unrealistic to find correlations between MLH and near-surface pollutant concentrations representative for a city like Berlin (flat terrain), in particular when traffic emissions are dominant. Nevertheless it is worthwhile to use advanced MLH retrievals for ceilometer data, for example as input to dispersion models and for the validation of chemical transport models.

A detailed understanding of atmospheric boundary layer (ABL) processes is key to improve forecasting of pollution dispersion and cloud dynamics in the context of future climate scenarios. International networks of automatic lidars and ceilometers (ALC) are gathering valuable data that allow for the height of the ABL and its sublayers to be derived in near real time. A new generation of advanced methods to automatically detect the ABL heights now exist. However, diversity in ALC models means these algorithms need to be tailored to instrument-specific capabilities. Here, the advanced algorithm STRATfinder is presented for application to high signal-to-noise ratio (SNR) ALC observations, and results are compared to an automatic algorithm designed for low-SNR measurements (CABAM). The two algorithms are evaluated for application in an operational network setting. Results indicate that the ABL heights derived from low-SNR ALC have increased uncertainty during daytime deep convection, while high-SNR observations can have slightly reduced capabilities in detecting shallow nocturnal layers. Agreement between the ALC-based methods is similar when either is compared to the ABL heights derived from temperature profile data. The two independent methods describe very similar average diurnal and seasonal variations. Hence, high-quality products of ABL heights may soon become possible at national and continental scales.

In the framework of the Saharan Mineral Dust Experiment (SAMUM) for the first time the spectral dependence of particle linear depolarization ratios was measured by combining four lidar systems. In this paper these measurements are compared with results from scattering theory based on the T-matrix method. For this purpose, in situ measurements—size distribution, shape distribution and refractive index—were used as input parameters; particle shape was approximated by spheroids. A sensitivity study showed that lidar-related parameters—lidar ratio Sp and linear depolarization ratio δp—are very sensitive to changes of all parameters. The simulated values of the δp are in the range of 20% and 31% and thus in the range of the measurements. The spectral dependence is weak, so that it could not be resolved by the measurements. Calculated lidar ratios based on the measured microphysics and considering equivalent radii up to 7.5μm show a range of possible values between 29 and 50 sr at λ = 532 nm. Larger Sp might be...