An empirical method to correct for temperature-dependent variations in the overlap function of CHM15k ceilometers
- 1MeteoSwiss, Payerne, Switzerland
- anow at: Institute for Atmospheric and Climate Science, ETH, Zurich, Switzerland
Abstract. Imperfections in a lidar's overlap function lead to artefacts in the background, range and overlap-corrected lidar signals. These artefacts can erroneously be interpreted as an aerosol gradient or, in extreme cases, as a cloud base leading to false cloud detection. A correct specification of the overlap function is hence crucial in the use of automatic elastic lidars (ceilometers) for the detection of the planetary boundary layer or of low cloud.
In this study, an algorithm is presented to correct such artefacts. It is based on the assumption of a homogeneous boundary layer and a correct specification of the overlap function down to a minimum range, which must be situated within the boundary layer. The strength of the algorithm lies in a sophisticated quality-check scheme which allows the reliable identification of favourable atmospheric conditions. The algorithm was applied to 2 years of data from a CHM15k ceilometer from the company Lufft. Backscatter signals corrected for background, range and overlap were compared using the overlap function provided by the manufacturer and the one corrected with the presented algorithm. Differences between corrected and uncorrected signals reached up to 45 % in the first 300 m above ground.
The amplitude of the correction turned out to be temperature dependent and was larger for higher temperatures. A linear model of the correction as a function of the instrument's internal temperature was derived from the experimental data. Case studies and a statistical analysis of the strongest gradient derived from corrected signals reveal that the temperature model is capable of a high-quality correction of overlap artefacts, in particular those due to diurnal variations. The presented correction method has the potential to significantly improve the detection of the boundary layer with gradient-based methods because it removes false candidates and hence simplifies the attribution of the detected gradients to the planetary boundary layer. A particularly significant benefit can be expected for the detection of shallow stable layers typical of night-time situations.
The algorithm is completely automatic and does not require any on-site intervention but requires the definition of an adequate instrument-specific configuration. It is therefore suited for use in large ceilometer networks.