The retrieval of turbulence parameters with profiling Doppler wind lidars (DWLs) is of high interest for boundary layer meteorology and its applications. DWLs provide wind measurements above the level of meteorological masts while being easier and less expensive to deploy. Velocity-azimuth display (VAD) scans can be used to retrieve the turbulence kinetic energy (TKE) dissipation rate through a fit of measured azimuth structure functions to a theoretical model. At the elevation angle of 35.3
From the validation against the sonic anemometers we confirm that lidar measurements can be significantly improved by the introduction of the volume-averaging effect into the retrieval. We introduce a correction for advection in the retrieval that only shows minor reductions in the TKE error for 35.3
The observation of turbulence in the atmosphere, in particular the atmospheric boundary layer (ABL), is of great importance for basic research in boundary layer meteorology and in applied fields such as aviation, wind energy
A wide range of instruments are used to measure turbulence: sonic anemometers are currently the most popular in situ instrument that can be installed on meteorological masts and provide continuous data on three-dimensional flow and its turbulent fluctuations
A variety of methods already exist to retrieve turbulence from DWL measurements. They can be categorized according to the respective scanning strategy applied: the simplest scanning pattern is a constant vertical stare to zenith, which allows researchers to obtain variances of vertical velocity and estimates of the turbulence kinetic energy (TKE) dissipation rate
In this study, data from two different experiments are analyzed. Both of the experiments and the instrumentation are introduced in this section.
The Meteorological Observatory Lindenberg–Richard-Aßmann Observatory (MOL-RAO) is part of Deutscher Wetterdienst (DWD), the national meteorological service of Germany. The observatory is situated in the east of Germany, approximately 65 km to the southeast of the center of Berlin. MOL-RAO runs a comprehensive operational measurement program to characterize the physical structure and processes in the atmospheric column above Lindenberg. Measurements of ABL processes form an essential part of it; they are carried out at the boundary layer field site (in German: Grenzschichtmessfeld, GM) in Falkenberg, about 5 km to the south of the main observatory site. The GM Falkenberg is situated in a rural landscape dominated by forest, grassland, and agricultural fields (see Fig.
Sketch of the measurement site at MOL-RAO, GM Falkenberg. Map data © OpenStreetMap contributors 2019. Distributed under a Creative Commons BY-SA License.
Since 2014, MOL-RAO has been using a DWL “Stream Line” (Halo Photonics Ltd.) for boundary layer measurements. From that time the device has been extensively tested with respect to its operational use for wind and turbulence measurements. This included, for instance, tests of the technical robustness and data availability under all weather conditions, but also tests of different scanning strategies and retrieval methods for the 3D wind vector and for the TKE.
The position of the DWL during a measurement period from 2 through 30 April 2019 was at the western edge of the field site at about 500 m of distance from the 99 m tower. It should be noted that there is a small patch of forest about 300 m to the W-NW of the lidar site. During this period the system continuously performed VAD scans with an elevation angle of 35.3
Continuous turbulence measurements (20 Hz sampling frequency) using a sonic anemometer of type USA-1 (METEK GmbH) are performed at the 50 and 90 m levels on the tower and have been used for validation purposes. The instruments are mounted at the tip of the booms pointing towards south.
Within the scope of the
Main technical specifications of the Doppler wind lidars.
The DWL measurements are particularly helpful to support the CoMet measurements by providing wind information that is essential to derive emission flux estimates from passive remote sensing
The lidars were operating in VAD modes with two different elevation angles. Since the focus for the CoMet campaign was on continuous wind profiling and a good height coverage was desired, the lidars were programmed to perform VADs with an elevation angle of 75
As shown in Fig.
Sketch of the measurement site in Upper Silesia. Red circles show the extent of the VAD scan at 35.3
From the sonic anemometers on the meteorological mast, TKE and the TKE dissipation rate are calculated. TKE is calculated from the sum of variances
Methods to retrieve turbulence parameters from VAD scans are well-known and a variety of different methods exist. The method we refine in this study is based on the theory that was originally described by
From a partial Fourier decomposition (see Appendix
In order to retrieve estimations of the TKE dissipation rate
Scanning with Doppler lidar in a classical VAD with continuous motion of the azimuth motor involves a volume averaging of radial velocities in the longitudinal (along the laser beam) and transverse (orthogonal to the beam) direction. The E89 and S17A methods do not consider this effect and will thus yield a systematic underestimation of TKE and
The measured azimuth structure function
Combining Eq. (
It shows that since the instrumental error
In
Using Eqs. (
Example of the structure functions of sonic anemometer (blue) and lidar (grey) at 90 m of height on 4 April 2019, 12:00–12:30 UTC. The dashed black line shows the measured lidar structure function
The retrieval method for
The VAD at
In Eq. (
In
The variances
Improvements of turbulence estimates in low signal conditions can be achieved by filtering bad estimates as described in
Replacing
As suggested in
The azimuth structure function and the volume-average filter are distorted by advection through a modification of
Sketch of the measurement points of a VAD scan in an earth-fixed versus a flow-fixed coordinate system.
Here,
The effects of advection on the turbulence estimation are largest in the lowest levels of the VAD scans because
In order to fulfill the assumptions that are made with regards to the turbulence model and the turbulence retrieval method, the data are filtered according to the criteria given in
Equations (
The filter criteria in Eq. (
Except for the retrieval method W20, which uses the filtering of bad estimates, we set fixed CNR filter thresholds adapted to the lidar type. Since the turbulence retrievals are very sensitive to bad estimates, we set the CNR thresholds to conservative values that are given in Table
An overview of all retrieval methods and their characteristics and filters that are applied is given in Table
Overview of turbulence retrieval methods and the applied filters and methods.
The estimation of turbulence parameters from the wind measurement system on the DLR Cessna Grand Caravan 208B
To evaluate the heterogeneity of turbulence due to changing land use along the flight legs of more than 50 km length, we divided the legs into sub-legs of 6.5 km (i.e., 100 s averaging time) and calculated turbulence for each leg individually. The location of the legs and the sub-legs is shown in Fig.
The best possible validation of the methods introduced in Sect.
In Sect.
Time series of TKE from lidar retrievals compared to a sonic anemometer at 90 m above ground level
The MOL-RAO dataset allows us to compare the retrievals without consideration of lidar volume averaging (E89 and S17A) to the S17 retrieval and its modified version W20 introduced in this study. For this purpose, the individual retrieval results are compared to the sonic anemometer estimates of TKE and its dissipation rate
Scatterplot of lidar TKE retrieval against sonic anemometer TKE at the 50 m level
Scatterplot of lidar dissipation rate retrieval against the sonic anemometer dissipation rate. The light red dots in panels
To evaluate the error that is caused by advection in the S17 retrieval, all data that were collected at MOL-RAO were binned into wind speeds with a bin width of 1 m s
Difference of the lidar retrieval of TKE
VAD scans with 35.3
Figure
Scatterplot of lidar dissipation rate retrieval from VAD scans with a 75
As for the comparison with the sonic anemometer, we evaluate the error as a function of wind speed by binning the data in wind speeds between 0 and 10 m s
Difference of lidar
During CoMet, no meteorological tower with sonic anemometers at levels that could be compared to the Doppler lidars was available. Instead, the aircraft D-FDLR was operating with a turbulence probe and provided in situ turbulence data. On 5 June 2018, the aircraft was flying a so-called “wall” pattern, with long, straight, and level legs at five altitudes (800, 1000, 1100, 1300, and 1600 m). At least the lowest three levels of this flight allow for a comparison to the measurement levels of the top levels of lidar measurements on this day. Figure
D-FDLR TKE measurements at five flight levels. Map data © OpenStreetMap contributors 2019. Distributed under a Creative Commons BY-SA License.
Vertical profile of TKE
Figure
Figure
Diurnal cycle of the TKE dissipation rate on 5 June 2018 at the three lidar locations calculated with the W20 method.
In this study, we used four different methods to retrieve turbulence parameters from the same data obtained through lidar VAD scans. The MOL-RAO experiment allowed us to investigate and validate the methods with a database of 30 d containing a broad variety of atmospheric conditions, with wind speeds of 0.12 m s
The aircraft measurements that were carried out during the CoMet campaign were used to show the agreement of the lidar retrievals with in situ measurements at higher altitudes. It is the first time that these lidar measurements have been compared to in situ aircraft data. Unfortunately, only measurements for a single day allowed for a comparison, and the spatial separation of the measurements introduces additional uncertainty. It was found that TKE estimates from lidar and aircraft compare rather well, but the small values of dissipation rates at these heights are underestimated by the lidar to a similar order of magnitude as for low-turbulence conditions in the sonic anemometer comparison. Dedicated experiments will be necessary in the future to provide more comprehensive validation datasets for turbulence retrievals with lidar VAD scans. Given the larger separation distances
The CoMet dataset was also used to show that VAD scans with a larger elevation angle (here: 75
A partial decomposition of Eq. (
Theoretical models for the spectral broadening of lidar measurements (
For statistically independent subsamples
The FSWF retrieval
Scatterplot of horizontal wind speed
The data are available from the author upon request.
NW, EP, AR, and CM helped design and carry out the field measurements. CM provided processed data from the D-FDLR aircraft turbulence probe. NW analyzed the data from the sonic anemometers, the profiling lidars, and the D-FDLR. NW wrote the paper, with significant contributions from EP. All the coauthors contributed to refining the paper text.
The authors declare that they have no conflict of interest.
This article is part of the special issue “CoMet: a mission to improve our understanding and to better quantify the carbon dioxide and methane cycles”. It is not associated with a conference.
We want to thank Jarosław Nęcki and all of the students at the University of Science and Technology, Cracow, for their tireless work in support of the CoMet campaign. We thank the Aeroklub Rybnickiego Okręgu Węglowego, Hotel Restauracja Pustelnik, and Agroturystyka “Na Polanie” for providing space and infrastructure for the lidar deployment in Upper Silesia. We thank Frank Beyrich and Andreas Fix for internal reviews and their input on the paper.
This research has been supported by the Bundesministerium für Bildung und Forschung (grant no. 01LK1701A) and the Bundesministerium für Wirtschaft und Energie (grant no. 0325936A).The article processing charges for this open-access publication were covered by a Research Centre of the Helmholtz Association.
This paper was edited by Dominik Brunner and reviewed by Rob K. Newsom and one anonymous referee.