The technological development of ground-based active remote sensing instruments has reached a point where these techniques become relevant for the operational long-term use within a meteorological measurement network. The drastically increased temporal and spatial data density compared to conventional instruments, such as radiosondes, will allow for a better process understanding and is expected to enhance the forecasting skills of numerical weather prediction systems and reduce its uncertainties. In this context, it is our goal to quantification of the measurement uncertainty and the temporal and spatial representatives of lidar measurements. In addition, automated data quality control tests adapted to the specific needs of lidar measurements will be developed. To this end, we plan to participate with three Doppler lidars in the FESSTVaL-2020 field campaign of the Hans Ertel Centre for Weather Research (HErZ) at the boundary-layer test site Falkenberg of DWD-MOL, which will allow us to verify the lidar-based wind measurement using the instrumented tall tower there, and to evaluate different scanning strategies. In addition, we plan to conduct large-eddy simulations (LES) for this field campaign, in order to further investigate the advantages and disadvantages of different scanning strategies using a lidar simulator tool, which will be specifically adapted to the characteristics of the instruments used. For further verification of lidar data, particularly also for air temperature and absolute humidity, we will exploit another dataset, which is collected during the CHEESEHEAD field campaign of summer 2019 by an in-house Raman/DIAL lidar in Wisconsin, USA, where a collocated instrumented 430 m tall tower is available. These rich data sets will form the basis for the development and adaptation of specific algorithms for uncertainty quantification and quality control, targeted at the long-term deployment of such lidars.
QALiBo: Quality Assessment of ground-based Lidar measurements in the Boundary layer
Quality Assessment of ground-based Lidar measurements in the Boundary layer (QALiBo)
Evaluation and verification of scanning strategies, quality tests and uncertainty quantification