Doppler lidar (DL) applications with a focus on turbulence measurements sometimes require measurement settings with a relatively small number of accumulated pulses per ray in order to achieve high sampling rates. Low pulse accumulation comes at the cost of the quality of DL radial velocity estimates and increases the probability of outliers, also referred to as "bad" estimates or noise. Careful filtering is therefore the first important step in a data processing chain that begins with radial velocity measurements as DL output variables and ends with turbulence variables as the target variable after applying an appropriate retrieval method. It is shown that commonly applied filtering techniques have weaknesses in distinguishing between "good" and "bad" estimates with the sensitivity needed for a turbulence retrieval. For that reason, new ways of noise filtering have been explored, taking into account that the DL background noise can differ from generally assumed white noise. It is shown that the introduction of a new coordinate frame for a graphical representation of DL radial velocities from conical scans offers a different perspective on the data when compared to the well-known velocity-azimuth display (VAD) and thus opens up new possibilities for data analysis and filtering. This new way of displaying DL radial velocities builds on the use of a phase-space perspective. Following the mathematical formalism used to explain a harmonic oscillator, the VAD's sinusoidal representation of the DL radial velocities is transformed into a circular arrangement. Using this kind of representation of DL measurements, bad estimates can be identified in two different ways: either in a direct way by singular point detection in subsets of radial velocity data grouped in circular rings or indirectly by localizing circular rings with mostly good radial velocity estimates by means of the autocorrelation function. The improved performance of the new filter techniques compared to conventional approaches is demonstrated through both a direct comparison of unfiltered with filtered datasets and a comparison of retrieved turbulence variables with independent measurements.

The height of the atmospheric boundary layer (hABL) is an important integral variable to characterise the state of the lower atmosphere with respect to different applications such as the assessment of trace gas and aerosol transport and mixing, the prediction of low-level clouds, the description of sound propagation, and the scaling of ABL profiles for use in engineering models and parametrizations. Different methods have been suggested and qualified to derive hABL based on profile measurements of atmospheric state and process variables with ground-based in-situ and remote sensing techniques. During the Field Experiment on Sub-Mesoscale Spatio-Temporal Variability in Lindenberg (FESSTVaL) which took place around the Lindenberg Meteorological Observatory – Richard-Aßmann-Observatory (MOL-RAO) of the German Meteorological Service (DWD) in summer 2021, a suite of ground-based remote sensing systems (including Doppler wind lidars, DWL, ceilometers, and microwave radiometer profilers, MWRP) was operated to characterize the status of the ABL over a heterogeneous land surface. Data from these instruments were used to derive estimates of hABL from the ceilometer backscatter intensity profiles, from the profiles of the vertical velocity variance measured with an upward looking DWL and from the wind and temperature profiles obtained from DWL and MWRP using the bulk Richardson number method. As an independent in-situ reference, different hABL estimates derived from 6-hourly operational radiosonde ascents were considered. In the presentation we discuss both case studies and results of a statistical comparison of the different hABL retrievals. Each of the methods employed has its strengths and weaknesses suggesting a synergistic approach to construct a reliable hABL composite data set.

At the Lindenberg Meteorological Observatory - Richard Aßmann Observatory (MOL-RAO), StreamLine Doppler Lidar (DL) systems from the manufacturer HALO Photonics (nowadays HALO Photonics by Lumibird) are tested for a routine application to derive profiles of turbulence variables within the atmospheric boundary layer (ABL). Information from these profile measurements is useful to get a better understanding of ABL processes and to provide enhanced insights into the ABL vertical structure under different weather conditions and over the course of a diurnal cycle (e.g. stable ABL, convective-mixed ABL, transitions between different ABL states). Further possible applications of turbulence profiles from DL measurements can be found in the area of ​​validation and/or development of turbulence closure schemes used in weather or climate models and in the wind energy sector.As an example, results for the turbulence kinetic energy (TKE) derived by means of a DL scanning and turbulence retrieval method introduced by Smalikho and Banakh (2017) are presented. For the retrieval of TKE profiles this method provides two correction terms. One corrects for an underestimation of TKE due to the averaging of radial velocity over the pulse volume and the other is used to prevent an overestimation of TKE if turbulence is very weak. The long-term measurements at MOL-RAO are used to evaluate the performance of these correction terms. It is shown that the corrections can have a significant positive effect on the precision and accuracy of the retrieved TKE, provided that noise-free DL radial velocity measurements are used as input data for the turbulence retrieval and the inherent assumptions of the retrieval method are fulfilled. To verify the latter, an additional data quality control (QC) scheme was developed at MOL-RAO and applied after the retrieval procedure. Insights into the main test criteria of this QC scheme will be presented and the results of their application will be discussed. Finally, comparisons of DL based TKE retrievals are shown between seven different DL systems which were operated side-by-side with an identical scan configuration under same atmospheric conditions. The DL systems exhibited differences in their pulse lengths and thus the size of their pulse volumes. The associated differences in the correction terms and their effect on the final TKE retrieval results will be discussed. ReferencesSmalikho, I. N. and Banakh, V. A.: Measurements of wind turbulence parameters by a conically scanning coherent Doppler lidar in the atmospheric boundary layer, Atmos. Meas. Tech., 10, 4191–4208, https://doi.org/10.5194/amt-10-4191-2017, 2017.

Doppler lidar systems are nowadays widely used for measuring the 3D wind vector within the atmospheric boundary layer (ABL). Different systems tailored towards different fields of application are commercially available. The WindRanger® is a compact, cost-effective and easy-to-use FMCW lidar for vertical wind profiling across the lowest 200 m metres above ground. It performs continuous velocity-azimuth-display scans of the laser beam at a zenith angle of 10 degrees. To assess the performance of this instrument, a WindRanger® was operated at the boundary layer field site (in German: Grenzschichtmessfeld, GM) Falkenberg of the Deutscher Wetterdienst (DWD) over a period of 13 months. We have compared the wind measurements with this instrument at a height of 90 m above ground versus sonic data collected at the 99m-tower and (for a sub-period) versus lidar wind data obtained with a pulsed Doppler lidar Streamline (Halo Photonics). Limitations of the WindRanger® measurements occurred in connection with precipitation and with low cloud base heights such that the data had to be filtered accordingly. The comparison provided RMSD values around 0.4 ms−1 for the wind speed and < 5° for the wind direction (after removing a bias due to improper alignment towards North). The WindRanger® allows for a time resolution of 0.5 s for one complete scan cycle. This lead us to investigate the possibility to derive wind gusts from the high-resolution time series. We found, however, that the wind speed from single-scan data exhibits a high variation throughout the day and derived gusts exceed the values determined from both the sonic and the Streamline Doppler lidar wind data in the convective boundary layer. This result is attributed to the small zenith angle (10 deg); this implies that the retrieved radial velocity values basically represent the vertical wind vector component which is typically characterized by strong fluctuations under convective conditions.

Doppler lidar systems scanning with a Velocity Azimuth Display (VAD) configuration are commonly used to determine profiles of wind speed and direction in the Atmospheric Boundary Layer (ABL, e.g. Päschke et al., 2015). In addition to the mean profile, short-term fluctuations of the wind, such as those that occur in connection with wind gusts, are of great interest and practical relevance. For Doppler lidar systems of the type “Streamline” (Halo Photonics) we defined and tested a scan configuration which appears suitable for the derivation of wind gusts. In particular, a conical scan mode is used and performed as a so-called fast continuous scan mode (fast CSM) that allows with 3.4s a comparably fast duration for one single conical scan with 10-11 beam directions. Such a fast scan is required to measure wind gusts according to the widely accepted definition of a wind gust (3s moving average; WMO (2018)). This special configuration introduces challenges to the data processing. Based on the fixed laser pulse repetition rate (10 kHz) of the lidar system comparatively few laser pulses are forming one measurement beam which in turn affect the quality of the radial velocity estimates. For that reason, classical approaches for data filtering (signal-to-noise thresholding, consensus filtering) are not always suitable. We therefore developed an alternative method for processing the raw lidar data. Measurements from a one-year test operation of a Streamline Doppler lidar in the fast CSM at the boundary layer field site (GM) Falkenberg of the German Meteorological Service (DWD) were used to derive both the mean wind vector and the maximum wind gust for 10-minute averaging intervals. The results were compared with sonic measurements at 90m height. We obtained a very good correlation and RMSD values of ~0.3m/s for the mean wind speed and ~0.64m/s for the wind gusts. Similar results were obtained during a 4-weeks campaign at the “Hamburg Weather Mast” at larger heights (175m and 250m). Besides these statistical results we will show examples of the gust detection for different weather situations (thunderstorm with cold pool, frontal passage, storm depression, convective gustiness) with particular emphasis on the vertical gust propagation. World Meteorological Organization (WMO) (2018): Measurement of surface wind. In Guide to Meteorological Instruments and Methods of Observation, Volume I -Measurement of Meteorological Variables, No.8: 196–213, URL:https://library.wmo.int/index.php?lvl=notice_display&id=12407#.ZD7G0c7P1aS (accessed April 2023) Päschke, E., Leinweber, R., and Lehmann, V. (2015): An assessment of the performance of a 1.5 μm Doppler lidar for operational vertical wind profiling based on a 1-year trial, Atmos. Meas. Tech., 8, 2251–2266, https://doi.org/10.5194/amt-8-2251-2015

Numerical weather prediction models operate on grid spacings of a few kilometers, where deep convection begins to become resolvable. Around this scale, the emergence of coherent structures in the planetary boundary layer, often hypothesized to be caused by cold pools, forces the transition from shallow to deep convection. Yet, the kilometer-scale range is typically not resolved by standard surface operational measurement networks. The measurement campaign Field Experiment on Submesoscale Spatio-Temporal Variability in Lindenberg (FESSTVaL) aimed at addressing this gap by observing atmospheric variability at the hectometer-to-kilometer scale, with a particular emphasis on cold pools, wind gusts, and coherent patterns in the planetary boundary layer during summer. A unique feature was the distribution of 150 self-developed and low-cost instruments. More specifically, FESSTVaL included dense networks of 80 autonomous cold pool loggers, 19 weather stations, and 83 soil sensor systems, all installed in a rural region of 15-km radius in eastern Germany, as well as self-developed weather stations handed out to citizens. Boundary layer and upper-air observations were provided by eight Doppler lidars and four microwave radiometers distributed at three supersites; water vapor and temperature were also measured by advanced lidar systems and an infrared spectrometer; and rain was observed by a X-band radar. An uncrewed aircraft, multicopters, and a small radiometer network carried out additional measurements during a 4-week period. In this paper, we present FESSTVaL’s measurement strategy and show first observational results including unprecedented highly resolved spatiotemporal cold-pool structures, both in the horizontal as well as in the vertical dimension, associated with overpassing convective systems.

Doppler wind lidars (DWLs) have increasingly been used over the last decade to derive the mean wind in the atmospheric boundary layer. DWLs allow the determination of wind vector profiles with high vertical resolution and provide an alternative to classic meteorological tower observations. They also receive signals from altitudes higher than a tower and can be set up flexibly in any power-supplied location. In this work, we address the question of whether and how wind gusts can be derived from DWL observations. The characterization of wind gusts is one central goal of the Field Experiment on Sub-Mesoscale Spatio-Temporal Variability in Lindenberg (FESSTVaL). Obtaining wind gusts from a DWL is not trivial because a monostatic DWL provides only a radial velocity per line of sight, i.e., only one component of a three-dimensional vector, and measurements in at least three linearly independent directions are required to derive the wind vector. Performing them sequentially limits the achievable time resolution, while wind gusts are short-lived phenomena. This study compares different DWL configurations in terms of their potential to derive wind gusts. For this purpose, we develop a new wind retrieval method that is applicable to different scanning configurations and various time resolutions. We test eight configurations with StreamLine DWL systems from HALO Photonics and evaluate gust peaks and mean wind over 10 min at 90 m a.g.l. against a sonic anemometer at the meteorological tower in Falkenberg, Germany. The best-performing configuration for retrieving wind gusts proves to be a fast continuous scanning mode (CSM) that completes a full observation cycle within 3.4 s. During this time interval, about 11 radial Doppler velocities are measured, which are then used to retrieve single gusts. The fast CSM configuration was successfully operated over a 3-month period in summer 2020. The CSM paired with our new retrieval technique provides gust peaks that compare well to classic sonic anemometer measurements from the meteorological tower.

Turbulence kinetic energy (TKE) is an important process variable to characterize the atmospheric boundary layer. State-of-the-art numerical weather prediction (NWP) models solve a prognostic TKE equation, this generates the interest in measurement data of this variable for verification of the NWP model output. Operational TKE measurements are typically performed using 3D ultrasonic anemometers; this limits their availability to near-surface levels (up to about 200 m above ground at a few tower sites). Alternatively, TKE may be derived from measurements with ground-based remote sensing instruments, such as Doppler lidars.At the Meteorological Observatory Lindenberg – Richard-Aßmann-Observatory (MOL-RAO) of the German Meteorological Service (DWD) we have implemented an algorithm suggested by Smalikho und Banakh (2017, Atmos. Meas. Tech. 10, 4191–4208) to derive TKE profiles from Doppler lidar measurements. In addition, this algorithm allows to derive profiles of momentum flux, eddy dissipation rate and the integral length scale of turbulence. Thus, a consistent data set to characterize turbulent processes in the atmospheric boundary layer can be obtained. The method includes a correction for an underestimation of TKE due to pulse volume averaging effects. It is based on a special Doppler lidar scan regime - a continuous scan mode (CSM) with very high azimuthal resolution (< 2 deg). This implies using a small number of lidar pulses per ray such that classical data filtering approaches cannot be applied.We briefly introduce the scan configuration and the methodology for TKE derivation and discuss an alternative data filtering approach which has been realized and tested at MOL-RAO. The methodology has been applied to a data set covering one year of quasi-operational measurements with a Halo Photonics Streamline Doppler lidar at MOL-RAOs boundary-layer field site (GM) Falkenberg. Here, the intercomparison of the derived TKE values versus sonic measurements at a height of 90m at the GM Falkenberg tower shows good agreement. Case studies illustrate the potential to characterize enhanced turbulence associated with cold pools affiliated to thunderstorms or in the shear zone below the axis of a nocturnal low-level jet. Finally, the Doppler lidar TKE values have been compared to the output of DWD’s NWP models.

Fibre-optic based Doppler wind lidars (DL) are able to retrieve vertical profiles of kinematic quantities across the lower atmosphere with high spatio-temporal resolution. Especially short-term forecasting would benefit from assimilating their data which renders these compact systems promising candidates for operational use in future observing networks of meteorological and environmental services. Therefore, DWD includes the assessment of DLs in the effort to evaluate ground-based remote sensing systems for their operational readiness, called “Pilotstation”. Besides tests focusing on aspects such as technical reliability, uncertainty characterization, scanning strategies, and the verification of the retrieved mean wind speed and direction with the help of independent reference data from a 482 MHz radar wind profiler (RWP) and 6-hourly radiosonde (RS) ascents, DWD developed a standardized retrieval assuring a high-quality Level-2 product. However, a prerequisite for operational applications is the robust detection of atmospheric return signals in the presence of instrumental noise. While the most common approach filters data via a fixed signal-to-noise ratio (SNR) threshold, we find the non-linear consensus method (CNS), already operational in the data processing chain of radar wind profilers, to be more efficient in the weak signal regime where it increases data availability without reducing data quality. Here, we present results from a long-term assessment at the Lindenberg Meteorological Observatory using the RWP and RS as references and from a side-by-side comparison of eight Halo Photonics “Streamline” DLs during the FESSTVaL 2021 field experiment. We focus on the characterization of the instrumental noise and show its impact on the derived winds and the data availability.

&lt;p&gt;Doppler lidar systems allow for a reliable determination of the profiles of wind speed and wind direction in the Atmospheric Boundary Layer (ABL) based on classical measurement strategies such as a VAD scan (Velocity Azimuth Display, e.g. P&amp;#228;schke et al., 2015, Atmos. Meas. Tech. 8, 2251&amp;#8211;2266). For many practical applications, however, short-term fluctuations of the wind, such as those that occur in connection with wind gusts, are of great interest in addition to the mean wind profile.&lt;/p&gt;&lt;p&gt;A study by Suomi et al. (2017, Q.J.R. Meteorol. Soc. 143, 2061-2072) has shown that it is, in principle, possible to derive wind gusts from Doppler lidar measurements. However, the high temporal resolution in the determination of the wind vector required for this is not achieved with usual measurement strategies. The authors therefore introduced a correction of the gust values derived from the lidar data based on a scaling approach using in-situ wind measurements.&lt;/p&gt;&lt;p&gt;In our study, an alternative measurement strategy for Doppler lidar systems of the type &quot;Streamline&quot; (Halo Photonics) was developed and tested over several months in 2020/21 at the boundary layer measurement field site (GM) Falkenberg of the German Meteorological Service (DWD). The gust derivation is based on a so-called continuous scan mode (CSM) where the radial velocity measurements taken continuously during a complete rotation of the lidar scan head are assigned to 10-11 beam directions and the wind vector for each rotation is determined using the VAD method. The duration of a scan cycle is about 3.4s, thus a time resolution can be achieved that corresponds to the widely-accepted definition of a wind gust (3s moving average; WMO (2018)).&lt;/p&gt;&lt;p&gt;This new configuration brings challenges to the data processing. In the fast CSM, comparatively few lidar pulses per measurement beam have to be used, so that classical approaches for data filtering (signal-to-noise thresholding, consensus filtering) cannot be used. An alternative method for processing the raw lidar data is proposed. The results of deriving both the mean wind vector and the respective maximum wind gust for a 10-minute averaging interval are compared with sonic measurements at 90m height for a two-month period during the FESSTVaL experiment (Field Experiment on Sub-Mesoscale Spatio-Temporal Variability in Lindenberg, www.fesstval.de). Further measurements were realised in Hamburg in spring 2022 in order to make comparisons with sonic measurements on a tower at higher levels (up to 250m). First results from this 4-week experiment will also be presented.&lt;/p&gt;&lt;p&gt;World Meteorological Organization (WMO) (2018): Measurement of surface wind. In Guide to Meteorological Instruments and Methods of Observation, Volume I -Measurement of Meteorological Variables, No.8: 196&amp;#8211;213, URL: https://library.wmo.int/doc_num.php?explnum_id=10616 (accessed April 2022)&lt;/p&gt;

Doppler wind lidar systems are an indispensable tool for the observation of the atmospheric boundary layer. With varying atmospheric conditions in the boundary layer the performance and availability of these systems varies. In order to ensure their quality measurements are needed to validate the lidar measurements. During the FESSTVaL field measurement campaign in summer 2021 airborne meteorological measurements in the atmospheric boundary layer above the measuring field Falkenberg of the German Weather Service measurements were recorded for this purpose. The focus was on the validation of Doppler lidar measurements of the wind speed, wind direction and turbulence kinetic energy in the altitude range from 90 m to 600 m above ground. The obtained data will be used to show in how far the lidar data quality is depending on the altitude the measurements have been taken from. The validation data were collected with an unmanned aerial system (UAS) of type MASC-3 (Multipurpose Airborne SensorCarrier 3) operated by the University of tuebingen. The UAS MASC-3 is used for in-situ meteorological measurements of turbulent variables (three-dimensional wind vector, temperature, humidity and turbulence) as well as aerosol particles in the lower atmosphere. [1] With the help of our UAS measurements, the quality, spatial resolution, and significance of lidar data is investigated and will be assessed in different measurement configurations and under different atmospheric conditions, such as thermal stratification, water vapor content, concentration of aerosol particles and aerosol particle size distribution. Suitable scanning strategies for the lidar systems can thus be determined, characterized, and the measurement error as well as the representativeness and availability of the lidar wind and turbulence data will be quantified. The result of the assessment will help to determine the initially mentioned performance and availability of lidar more accurately, as well as to better integrate remote sensing instrumentation into an operational measurement network. [1] A. Rautenberg et al., MDPI Sensors doi:10.3390/s19102292 (2019)

The evolution of wind gusts is difficult to observe as gusts are short-lived and small-scale phenomena. They occur with certain weather configurations (e.g. fronts, cold pools) and may already differ very locally. The question arises if individual gust observations can be taken as representative of their surroundings or if significant differences can already be apparent on the meso-gamma scale (2-20 km). Within the Field Experiment on Sub-Mesoscale Spatio-Temporal Variability in Lindenberg (FESSTVaL) different phenomena in the atmospheric boundary layer are studied with a variety of measurement instruments. This involved installing three StreamLine DWL systems from Halo Photonics at a distance of 6 km apart from each other. DWLs allow the retrieval of wind vector profiles and offer an alternative to classic meteorological tower observations, since they can be flexibly deployed at any electrified site. However, short-lived gusts are more difficult to capture than a persistent mean wind. A wind vector has to be obtained from different radial velocity measurements that are made sequentially, which limits the achievable temporal resolution. Therefore, we have developed a new retrieval method for deriving wind measurements that is suitable for different scan configurations and different time resolutions respectively different numbers of radial velocities. A fast continuous scanning mode (CSM), that completes a full observation cycle within 3.4 seconds and measures about eleven radial Doppler velocities is a suitable DWL configuration for deriving wind gusts, as shown by comparisons with measurements of a sonic anemometer at 90.3 m a.g.l. on the meteorological tower in Falkenberg. The fast CSM configuration was operated on the DWLs during the summer months 2021 at the three different sites. Their surrounding area is predominantly flat farmland, minimizing topographic impacts. This set-up allows us to observe the spatial-temporal evolution of gusts at the meso-gamma scale. Examples will be presented that illustrate the variability of wind gusts as observed during FESSTVaL.

Technology has reached a point where ground-based remote sensing instruments have the ability to greatly increase the spatial and temporal data density compared to conventional instruments. This offers the great opportunity to improve the understanding of individual processes and to increase the predictive capabilities of numerical weather models and reduce their inaccuracies. The goal of this study is to assess these measurement inaccuracies and the usefulness of Doppler lidar systems for these purposes. The data were collected during the FESST@MOL 2020 measurement campaign, organised by the German Weather Service (DWD) and initiated by the Hans-Ertel-Center for Weather Research (HErZ), at the boundary layer field site (GM) of the DWD in Falkenberg (Tauche), Germany. During the measurement campaign, a total of eight Doppler lidars of the brands Halo Photonics and Leosphere were active in different operating modes. We compare the results of triple and single Halo Photonics lidar setups and triple Leosphere lidar setups with the measurements of an ultrasonic anemometer mounted at a height of 90 m at the 99 m high instrumented tower in Falkenberg. The focus of the operating modes was on various virtual tower (VT) measurements and velocity azimuth display (VAD) measurements with the different averaging times of ten and thirty minutes for the mean horizontal wind. The discrepancy in readings between VT and VAD measurements increases with increasing height above the ground while the Halo Photonic lidars performed better in the comparison with the sonic anemometer.

<p>Die Leistung und Verf&#252;gbarkeit von Lidar Systemen bei verschiedenen atmosph&#228;rischen Bedingungen ist unabdingbares Mittel zur Beobachtung der Atmosph&#228;rischen Grenzschicht. Um diese sicherzustellen werden Messungen ben&#246;tigt die es erm&#246;glichen die Lidar Messungen &#160;zu validieren.</p> <p>Zu diesem Zwecke wurden im Rahmen der FESSTVaL Feldmess-Kampagne &#160;im Sommer 2021 fluggest&#252;tzte meteorologische Messdaten in der atmosph&#228;rischen Grenzschicht &#252;ber dem Messfeld Falkenberg des Deutschen Wetterdienstes erfasst.</p> <p>Der Schwerpunkt lag dabei auf der Validierung von Doppler-Lidar Messungen der Windgeschwindigkeit, Windrichtung und der turbulenten kinetischen Energie im H&#246;henbereich von 90 m bis 600 m &#252;ber Grund. Die Validierungsdaten wurden mit dem unbemannten Luftfahrtsystem (UAS) vom Typ MASC-3 (Multipurpose Airborne SensorCarrier, Typ 3) aufgenommen. Das UAS MASC-3 wird f&#252;r meteorologische in-situ Messungen turbulenter Gr&#246;&#223;en (Wind, Temperatur, Feuchte) sowie von Aerosol-Partikeln in der unteren Atmosph&#228;re genutzt.[1]</p> <p>Mithilfe der UAS-Messungen wird die Qualit&#228;t, die r&#228;umliche Aufl&#246;sung und die Signifikanz der Lidar-Daten in verschiedenen Messkonfigurationen und unter unterschiedlichen atmosph&#228;rischen Bedingungen, wie z.B. thermische Schichtung, Wasserdampfgehalt, Konzentration und Gr&#246;&#223;enverteilung der Aerosol-Partikel, bewertet.</p> <p>Geeignete Scanning-Strategien f&#252;r die Lidar-Systeme k&#246;nnen so bestimmt, charakterisiert und der Messfehler sowie die Repr&#228;sentativit&#228;t und Verf&#252;gbarkeit der Lidar Wind- und Turbulenzdaten quantifiziert werden. Das Ergebnis der Bewertung wird dazu beitragen die anf&#228;nglich erw&#228;hnte Leistung und Verf&#252;gbarkeit von Lidar genauer zu beurteilen und um Fernerkundungsinstrumente besser in ein operationales Messnetzwerk integrieren zu k&#246;nnen.</p> <p>[1] A. Rautenberg et al., MDPI Sensors doi:10.3390/s19102292 (2019)</p>

The technological development of ground-based active remote sensing instruments has reached a point where they have the possibility to drastically increase the temporal and spatial data density compared to conventional instruments, which would allow for a better process understanding and is expected to enhance the forecasting skills of numerical weather prediction systems and reduce its uncertainties. To test the measurement uncertainty and feasibility of Doppler Lidar systems we participated in the FESST@MOL 2020 field campaign, organized by the German Meteorological Service (DWD) in Lindenberg, Germany. During this campaign, eight Doppler Lidars were operated at the boundary layer field site (GM) Falkenberg. We evaluated different scanning strategies for the determination of the wind profile in the Atmospheric Boundary Layer (ABL) using multiple different triple Lidar virtual tower (VT) scan patterns including range height indicator (RHI) and step/stare scan modes. We compared these Lidar-based wind measurements with the data from a sonic anemometer on a 99 m tall instrumented tower also located in Falkenberg over a period of four months. The lidar and the sonic anemometer data were processed to 10- and 30- minute averages and compared to each other. The VT measurements underestimated the mean horizontal wind compared to the sonic anemometer by around 0.2 m s‑1. Besides that, we compared the VT data with those from a single fourth nearby Doppler Lidar which was running in a velocity-azimuth display (VAD) mode. The calculated mean horizontal wind values between the two different modes showed a good comparability but differed stronger with increasing height.

Eine der wesentlichen Prozessvariablen zur Charakterisierung der atmosphärischen Grenzschicht (AGS) ist die turbulente kinetische Energie (TKE). In modernen Wettervorhersage-Modellen erfolgt die Simulation der TKE mit einer eigenen prognostischen Gleichung, hieraus ergibt sich zunehmend der Bedarf nach Messdaten zur Verifikation der Modellergebnisse auch für diese Variable. Operationelle Messungen der TKE werden in der Praxis nur an wenigen Standorten mittels 3D-Ultraschall-Anemometern durchgeführt und sind damit oft auf Höhen in Bodennähe, in Einzelfällen auf Mastmessungen bis etwa 200 m Höhe beschränkt. Am Meteorologischen Observatorium Lindenberg – Richard-Aßmann-Observatorium des DWD wurde in den letzten Jahren ein in der Literatur beschriebenes Verfahren (Smalikho und Banakh, 2017) zur Ableitung verschiedener Turbulenzvariablen aus Doppler-Lidar-Messungen implementiert, getestet und anhand mehrmonatiger Datensätze bewertet.Das Verfahren von Smalikho und Banakh (2017) zeichnet sich zum einen dadurch aus, dass es auf der Grundlage von nur einer Scankonfiguration sowohl die Bestimmung des mittleren Windvektors als auch eine kombinierte Abschätzung mehrerer Turbulenzvariablen (TKE, Impulsfluss, Dissipationsrate, integrale Längenskala) erlaubt und damit ein in sich konsistenter Datensatz zur Charakterisierung turbulenter Prozesse gewonnen werden kann. Zum anderen berücksichtigt das Verfahren verschiedene Korrekturmöglichkeiten, um z.B. dem Mittelungseffekt über das Doppler Lidar Pulsvolumen und der damit verbundenen begrenzten Auflösbarkeit kleinräumiger turbulenter Fluktuationen Rechnung zu tragen. Das Verfahren basiert auf Messungen im sogenannten Continuous Scan Mode (CSM), dessen Anwendung eine vergleichsweise niedrige Anzahl von Lidar-Pulsen pro Messstrahl erfordert. Damit können klassische Ansätze der Datenfilterung (Signal-to-Noise Schwellwert, Consensus Filterung) für die Analyse dieser Messungen nicht verwendet werden.Der Beitrag beschreibt zunächst sowohl das Scan-Verfahren als auch die Methodik zur Ableitung der TKE, dabei wird auf alternative Ansätze zur Datenfilterung eingegangen. Ebenfalls implementiert wurde ein mehrstufiges Verfahren zur Charakterisierung der Qualität der abgeleiteten Turbulenzvariablen. Eine Bewertung der ermittelten TKE erfolgt auf der Basis mehrmonatiger Messungen auf dem Grenzschichtmessfeld Falkenberg des DWD.Erste Vergleiche mit unabhängigen Referenzmessungen (insb. Sonic Messungen in 90m Höhe) zeigen eine gute Übereinstimmung. Bei gesamtheitlicher Betrachtung des Turbulenzdatensatzes können des Weiteren hinreichend bekannte Effekte, wie z.B. die scherinduzierte Turbulenz unterhalb eines Low Level Jets nachgewiesen und gleichzeitig Größenabschätzungen für die damit in Verbindung stehenden turbulenten Wirbel geliefert werden. Diese Einblicke zeigen mögliche Potentiale auf, Grenzschichtprozesse auf Grundlage eines umfangreichen Messdatensatzes bestehend aus Profilinformationen verschiedener Turbulenzvariablen genauer zu analysieren und damit besser verstehen zu lernen. Des Weiteren hat die Testphase deutlich gezeigt, dass die Ableitung eines belastbaren Daten-Produktes sehr stark von der Güte der Lidar-Rohdaten abhängt. Hierbei spielen nicht nur atmosphärische Bedingungen (z.B. der Aerosolgehalt der AGS), sondern auch die Leistungsmerkmale des Messsystems, eine Rolle. Die in diesem Zusammenhang gewonnenen Erfahrungen und Erkenntnisse zur Qualität der abgeleiteten Produkte werden abschließend diskutiert.

In the Field Experiment on Sub-Mesoscale Spatio-Temporal Variability in Lindenberg (FESSTVaL, www.fesstval.de) various phenomena in the atmospheric boundary layer are investigated. One goal is to detect wind gusts from measurements of a Doppler wind lidar (DWL). DWL’s allow the determination of wind vector profiles with a high vertical resolution (∼ 30 m) and therefore are an attractive alternative to metorological towers. However, obtaining wind gusts from DWL measurements is not trivial because a monostatic lidar provides only a radial velocity, i.e., only one component of a three-dimensional vector per individual beam. Measurements in at least three linearly independent directions are therefore necessary to derive the wind vector. These must be performed sequentially, which prolongs the time interval for determining the wind vector and therefore limits the time resolution of the derived wind vector. In order to retrieve wind gusts, wind maxima of a few seconds, one needs to operate the instrument in a quick scanning mode. In this presentation, we show results from different scanning modes and discuss the method for retrieving wind gusts. We tested various configurations with respect to their ability to detect gusts and mean winds at the Boundary Layer Field Site in Falkenberg in autumn 2019. The DWL configurations that measure different lines-of-sight with rapid temporal repetitions have a lower signal-to-noise ratio (SNR) but the highest chance of detecting gusts. We have developed a new retrieval method that skips prior SNR filtering and instead iteratively removes a fixed number of measurements that do not match a least-squares-fit. The least-squares-fit is then recalculated on the reduced set of measurements, and if necessary, this step is repeated. With appropriate retrieval steps and iteration criteria, our results suggest that prior filtering can be omitted. We present the results of our new retrieval for eight different DWL configurations consisting of double-beam swinging, step-stare modes, and continuous-scanning modes. The evaluation is done by a comparison of the minimum, maximum and mean wind speed at 90 m a.g.l. against the reference measurements of a sonic anemometer that is located nearby. Ongoing work is addressing further comparison of our retrieved wind variables with unmanned aerial vehicles from the FESSTVaL campaign in summer 2020.

Fibre-optic based Doppler wind lidars (DL) are widely used for both meteorological research and in the wind energy sector. These compact systems are able to retrieve vertical profiles of kinematic quantities, such as mean wind, from the atmospheric boundary layer as well as from optically thin cloud layers in the free troposphere with high spatio-temporal resolution. It is therefore likely that especially short-term forecasting would benefit from assimilating these data. However, their potential is currently not yet employed operationally.As part of DWD's effort to evaluate ground-based remote sensing systems for their operational readiness, called "Pilotstation", we developed a software client (DL-client) that standardizes the processing of mean wind based on the Velocity Azimuth Display method. Results of a long-term assessment of DLs at the Meteorological Observatory Lindenberg, starting in 2012, show that the DL-client assures a high quality Level-2 product, which is compatible with the EUMETNET's E-PROFILE observation program. We verified the retrieved mean wind speed and direction with the help of independent reference data from a 482 MHz radar wind profiler and 6-hourly radiosonde ascents. Hence, the DL-client not only facilitates processing and archiving of the DL data, but also forms a basis for operational network deployment and data assimilation. Furthermore, through speeding up and standardizing the data processing, the individual users can concentrate on more advanced scientific data analyses.Finally, the software is freely accessible and will be continuously improved to account for different scanning strategies. Its modular build-up of processing steps offers the possibility to extend the list of products with additional retrievals, e.g. for turbulent kinetic energy and wind gusts, which are currently under development at Lindenberg.

Die Leistung und Verfügbarkeit von Lidar Systemen bei verschiedenen atmosphärischen Bedingungen ist unabdingbares Mittel zur Beobachtung der Atmosphärischen Grenzschicht. Um diese sicherzustellen werden Messungen benötigt die es ermöglichen die Lidar Messungen zu validieren. Zu diesem Zwecke wurden im Rahmen der FESSTVaL Feldmess-Kampagne im Sommer 2021 fluggestützte meteorologische Messdaten in der atmosphärischen Grenzschicht über dem Messfeld Falkenberg des Deutschen Wetterdienstes erfasst. Der Schwerpunkt lag dabei auf der Validierung von Doppler-Lidar Messungen der Windgeschwindigkeit, Windrichtung und der turbulenten kinetischen Energie im Höhenbereich von 90 m bis 600 m über Grund. Die Validierungsdaten wurden mit dem unbemannten Luftfahrtsystem (UAS) vom Typ MASC-3 (Multipurpose Airborne SensorCarrier, Typ 3) aufgenommen. Das UAS MASC-3 wird für meteorologische in-situ Messungen turbulenter Größen (Wind, Temperatur, Feuchte) sowie von Aerosol-Partikeln in der unteren Atmosphäre genutzt.[1] Mithilfe der UAS-Messungen wird die Qualität, die räumliche Auflösung und die Signifikanz der Lidar-Daten in verschiedenen Messkonfigurationen und unter unterschiedlichen atmosphärischen Bedingungen, wie z.B. thermische Schichtung, Wasserdampfgehalt, Konzentration und Größenverteilung der Aerosol-Partikel, bewertet. Geeignete Scanning-Strategien für die Lidar-Systeme können so bestimmt, charakterisiert und der Messfehler sowie die Repräsentativität und Verfügbarkeit der Lidar Wind- und Turbulenzdaten quantifiziert werden. Das Ergebnis der Bewertung wird dazu beitragen die anfänglich erwähnte Leistung und Verfügbarkeit von Lidar genauer zu beurteilen und um Fernerkundungsinstrumente besser in ein operationales Messnetzwerk integrieren zu können. [1] A. Rautenberg et al., MDPI Sensors doi:10.3390/s19102292 (2019)

A central aspect of the Field Experiment on Sub-Mesoscale Spatio-Temporal Variability in Lindenberg (FESSTVaL, www.fesstval.de) is the investigation of wind gusts with Doppler lidar measurements. Compared to meteorological tower observations, they have the advantage of being able to probe higher altitudes of the atmosphere, they thus offer the possibility to record a vertical profile of wind gusts with a resolution of about 30 m in the atmospheric boundary layer. Nevertheless, it is difficult to capture wind gusts with these instruments as it is challenging to measure fluctuations of short duration with an instrument which needs a certain time for one complete measurement.Based on the research of Suomi et al. (2017), different configurations were tested in a pre-campaign in autumn 2019 to identify a suitable measurement mode for Halo Photonics Stream Line Scanning Doppler LiDAR systems. Different lidars were operated in parallel to compare configurations against each other. A promising mode was tested during the FESST@MOL campaign in summer 2020 for a three month period. This is a continous scan mode (CSM) configuration that takes about 3.4 seconds per circulation and performs measurements in 10-11 directions.The derived wind gusts and mean wind speeds are compared with high resolution sonic anemometer measurements at 90.3 m to verify the quality of the lidar measurements. In a first comparison good agreement is shown despite the different measuring principles. In addition, various parameters are tested to identify optimal thresholds that allow a reliable derivation of wind gusts.In summer 2021 this fast CSM mode will be operated and further tested in the FESSTVaL campaign in parallel with UAS measurements. Moreover lidars will be installed at different locations to analyse the spatial characteristics of wind gusts with this scanning configuration.ReferenceSuomi, I., Gryning, S.‐E., O'Connor, E.J. and Vihma, T. (2017), Methodology for obtaining wind gusts using Doppler lidar. Q.J.R. Meteorol. Soc., 143: 2061-2072. https://doi.org/10.1002/qj.3059