Doppler Wind Lidar Research Articles

Wind profiles measurements and predictions for atmospheric acoustic propagation modeling

This work presents a comprehensive experimental system to measure meteorological conditions with both anemometers and a three-dimensional scanning Doppler LIDAR wind profiler. The LIDAR system captures real-time wind speed gradients at many locations along a particular heading. This work describes a method for extracting a cartesian grid of wind speeds gradients from a range height indicator (RHI) scan pattern. The LIDAR derived wind profiles are compared to logarithmic wind profiles based on single point traditional anemometer measurements. Differences in wind speed profiles observed using the two methods are presented and the implications on long range acoustic propagation modeling are discussed.

Atmospheric acoustic propagation modeling using heterogeneous wind profiles along the acoustic path

This work presents atmospheric sound propagation predictions using a parabolic equation solver that accounts for heterogeneous wind profile distribution along the acoustic path. Transmission loss predictions using both homogeneous and heterogeneous wind speeds information are compared with data. A three-dimensional scanning Doppler LIDAR wind profiler captures real-time wind speed gradients at many locations along the acoustic propagation path providing the heterogeneous wind speed profiles. The wind measurements are concurrent with a pitch catch transmission loss measurements. A long-range acoustic device on an anchored pontoon sends known chirp sequences to a seven-channel receiver array at the water’s edge at ranges up to approximately one kilometer. Additional synchronized meteorological observations include temperature, humidity, and wind measured with anemometers. Key differences in model results are highlighted and an assessment of the value of the computational cost is presented.

Validation of Aeolus wind profiles using ground-based lidar and radiosonde observations at Réunion island and the Observatoire de Haute-Provence

Abstract. The European Space Agency's (ESA) Aeolus satellite mission is the first Doppler wind lidar in space, operating in orbit for more than 4 years since August 2018 and providing global wind profiling throughout the entire troposphere and the lower stratosphere. The Observatoire de Haute-Provence (OHP) in southern France and the Observatoire de Physique de l'Atmosphère de La Réunion (OPAR) are equipped with ground-based Doppler Rayleigh–Mie lidars, which operate on similar principles to the Aeolus lidar and are among essential instruments within the ESA Aeolus calibration and validation (cal/val) program. This study presents the validation results of the L2B Rayleigh clear horizontal line-of-sight (HLOS) winds from September 2018 to January 2022. The point-by-point validation exercise relies on a series of validation campaigns at both observatories: AboVE (Aeolus Validation Experiment), held in September 2019 and June 2021 at OPAR and in January 2019 and December 2021 at OHP. The campaigns involved time-coordinated lidar acquisitions and radiosonde ascents collocated with the nearest Aeolus overpasses. During AboVE-2, Aeolus was operated in a campaign mode with an extended range bin setting allowing inter-comparisons up to 28.7 km. We show that this setting suffers from larger random error in the uppermost bins, exceeding the estimated error, due to lack of backscatter at high altitudes. To evaluate the long-term evolution in Aeolus wind product quality, twice-daily routine Météo-France radiosondes and regular lidar observations were used at both sites. This study evaluates the long-term evolution of the satellite performance along with punctual collocation analyses. On average, we find a systematic error (bias) of −0.92 and −0.79 m s−1 and a random error (scaled MAD) of 6.49 and 5.37 m s−1 for lidar and radiosondes, respectively.

Sub-meter wind detection with pulsed coherent Doppler lidar

High-resolution wind detection plays a crucial role in aviation safety and aerodynamics. In this work, the fine wind field within 700 meters is continuously detected at a resolution of 0.9 meters/0.5 seconds by a coherent Doppler wind LiDAR. A meter-scale perturbation by an electric fan is remotely sensed, and atmospheric turbulence with length scale down to 3 meters can be observed.

Research on the Performance of an Active Rotating Tropospheric and Stratospheric Doppler Wind Lidar Transmitter and Receiver

This paper investigates the transmitter and receiver performance of an active rotating tropospheric stratospheric Doppler wind Lidar. A 532 nm laser was determined as the detection wavelength based on transmission and scattering aspects. A ten-fold Galileo beam expander consisting of spherical and aspherical mirrors was designed and produced to compress the outgoing laser’s divergence angle using ZEMAX simulation optimization and optical-mechanical mounting means. The structure and support of the 800 mm Cassegrain telescope was redesigned. Additionally, the structure of the receiver was optimized, and the size was reduced. Meanwhile, the detectors and fiber mountings were changed to improve the stability of the received optical path. A single-channel atmospheric echo signal test was used to select the best-performing photomultiplier tube (PMT). Finally, the atmospheric wind field detection results of the original and upgraded systems were compared. The results show that after optimizing the transmitter and receiver, the detection altitude of the system is increased to about 47 km, and the wind speed and wind direction profiles match better with radiosonde measurements.

Wind retrieval for genetic algorithm-based coherent Doppler wind lidar employing airborne platform

Wind retrieval for genetic algorithm-based coherent Doppler wind lidar employing airborne platform

Assimilation of New York State Mesonet Surface and Profiler Data for the 21 June 2021 Convective Event

Abstract The New York State Mesonet (NYSM) has provided continuous in situ and remote sensing observations near the surface and within the lower troposphere since 2017. The dense observing network can capture the evolution of mesoscale motions with high temporal and spatial resolution. The objective of this study was to investigate whether the assimilation of NYSM observations into numerical weather prediction models could be beneficial for improving model analysis and short-term weather prediction. The study was conducted using a convective event that occurred in New York on 21 June 2021. A line of severe thunderstorms developed, decayed, and then reintensified as it propagated eastward across the state. Several data assimilation (DA) experiments were conducted to investigate the impact of NYSM data using the operational DA system Gridpoint Statistical Interpolation with rapid update cycles. The assimilated datasets included National Centers for Environmental Prediction Automated Data Processing global upper-air and surface observations, NYSM surface observations, Doppler lidar wind retrievals, and microwave radiometer (MWR) thermodynamic retrievals at NYSM profiler sites. In comparison with the control experiment that assimilated only conventional data, the timing and location of the convection reintensification was significantly improved by assimilating NYSM data, especially the Doppler lidar wind data. Our analysis indicated that the improvement could be attributed to improved simulation of the Mohawk–Hudson Convergence. We also found that the MWR DA resulted in degraded forecasts, likely due to large errors in the MWR temperature retrievals. Overall, this case study suggested the positive impact of assimilating NYSM surface and profiler data on forecasting summertime severe weather.

Evaluation and impact factors of Doppler wind lidar during Super Typhoon Lekima (2019)

Doppler wind lidar (DWL) has been widely employed in the wind energy industry. However, the evaluation of DWL winds under typhoon conditions is still rare. This study evaluated the accuracy of wind data measured by two types of DWLs (WindPrint S4000 and WindCube V2), and investigated the impact of three environmental factors (precipitation intensity, relative humidity and drift distance of sounding balloons) on the DWL-measured wind speed and direction. Data were collected from the joint observation at Baoshan, Zhoushan and Taizhou during the passage of Super Typhoon Lekima in 2019. The DWL observations were compared with measured data from balloon-borne radiosonde released at the same location. The results show that the optimal agreement was found with the 1-min average DWL-measured winds. The DWL data missing rate decreases with the increase of signal-to-noise ratio and height from the surface. The applicability of DWL is poor when the precipitation intensity is larger than 50 mm h−1. The DWL wind speed and wind direction biases significantly increase when the relative humidity exceeds 85% and 90%, respectively. Moreover, the measured wind data of the balloon-borne radiosonde are not reliable when the horizontal drift distance is larger than 2 km.

Investigation of wind characteristics of typhoon boundary layer through field experiments and CFD simulations

High-resolution observations of typhoon boundary layer above 100 m are rare as traditional wind towers are generally below 100 m, which limits the study of typhoon boundary layer and engineering applications such as wind-resistant design of tall buildings and wind turbines in typhoon-prone regions. In this study, boundary layer winds of super typhoon Lekima (2019) are observed, simulated and analyzed. Together with traditional wind tower, Doppler wind lidar is utilized for observations of typhoon boundary layer in order to obtain measured data above 100 m. Besides, Computational Fluid Dynamics (CFD) simulation based on Large Eddy Simulation (LES) method is conducted to further investigate the impact of complex terrain on the near-surface wind characteristics. The results show that the power law fits the mean wind speed profile well below 100 m. However, before and after the typhoon lands, a local reverse or low-level jet occurs in the mean wind speed profile at the height of 100–300 m, which cannot be depicted by the power law. Meanwhile, the turbulence intensity increases with height and experiences larger fluctuations. In addition, there is a significant negative correlation between the ground elevation and power exponents of the fitted mean wind speed profiles. This study provides useful information to better understand wind characteristics of the typhoon boundary layer.

Nocturnal Boundary Layer Height Uncertainty in Particulate Matter Simulations during the KORUS-AQ Campaign

Vertical mixing in the planetary boundary layer (PBL) is an important factor in the prediction of particulate matter (PM) concentrations; however, PBL height (PBLH) in the stable atmosphere remains poorly understood. In particular, the assessment of uncertainties related to nocturnal PBLH (nPBLH) is challenging due to the absence of stable atmosphere observations. In this study, we explored nPBLH–PM2.5 interactions by comparing model results and observations during the Korea–United States Air Quality Study (KORUS-AQ) campaign (1–31 May 2016). Remote sensing measurements (e.g., aerosol and wind Doppler lidar) and on-line WRF-Chem modeling results were used by applying three different PBL parameterizations: Yonsei University (YSU), Mellor–Yamada–Janjic (MYJ), and Asymmetrical Convective Model v2 (ACM2). Our results indicated that the uncertainties of PBLH–PM interactions were not large in daytime, whereas the uncertainties of nPBLH–PM2.5 interactions were significant. All WRF-Chem experiments showed a clear tendency to underestimate nighttime nPBLH by a factor of ~3 compared with observations, and shallow nPBLH clearly led to extremely high PM2.5 peaks during the night. These uncertainties associated with nPBLH and nPBLH–PM2.5 simulations suggest that PM2.5 peaks predicted from nighttime or next-morning nPBLH simulations should be interpreted with caution. Additionally, we discuss uncertainties among PBL parameterization schemes in relation to PM2.5 simulations.

Detection Range/Spatial Resolution Enhancement of Coherent Doppler Wind Lidar Based on Improved Simplex Coding

Detection Range/Spatial Resolution Enhancement of Coherent Doppler Wind Lidar Based on Improved Simplex Coding

Validation of the Aeolus L2B wind product with airborne wind lidar measurements in the polar North Atlantic region and in the tropics

Abstract. During the first 3 years of the European Space Agency's Aeolus mission, the German Aerospace Center (Deutsches Zentrum für Luft- und Raumfahrt, DLR) performed four airborne campaigns deploying two different Doppler wind lidars (DWL) on board the DLR Falcon aircraft, aiming to validate the quality of the recent Aeolus Level 2B (L2B) wind data product (processor baseline 11 and 12). The first two campaigns, WindVal III (November–December 2018) and AVATAR-E (Aeolus Validation Through Airborne Lidars in Europe, May and June 2019), were conducted in Europe and provided first insights into the data quality at the beginning of the mission phase. The two later campaigns, AVATAR-I (Aeolus Validation Through Airborne Lidars in Iceland) and AVATAR-T (Aeolus Validation Through Airborne Lidars in the Tropics), were performed in regions of particular interest for the Aeolus validation: AVATAR-I was conducted from Keflavik, Iceland, between 9 September and 1 October 2019 to sample the high wind speeds in the vicinity of the polar jet stream; AVATAR-T was carried out from Sal, Cape Verde, between 6 and 28 September 2021 to measure winds in the Saharan dust-laden African easterly jet. Altogether, 10 Aeolus underflights were performed during AVATAR-I and 11 underflights during AVATAR-T, covering about 8000 and 11 000 km along the Aeolus measurement track, respectively. Based on these collocated measurements, statistical comparisons of Aeolus data with the reference lidar (2 µm DWL) as well as with in situ measurements by the Falcon were performed to determine the systematic and random errors of Rayleigh-clear and Mie-cloudy winds that are contained in the Aeolus L2B product. It is demonstrated that the systematic error almost fulfills the mission requirement of being below 0.7 m s−1 for both Rayleigh-clear and Mie-cloudy winds. The random error is shown to vary between 5.5 and 7.1 m s−1 for Rayleigh-clear winds and is thus larger than specified (2.5 m s−1), whereas it is close to the specifications for Mie-cloudy winds (2.7 to 2.9 m s−1). In addition, the dependency of the systematic and random errors on the actual wind speed, the geolocation, the scattering ratio, and the time difference between 2 µm DWL observation and satellite overflight is investigated and discussed. Thus, this work contributes to the characterization of the Aeolus data quality in different meteorological situations and allows one to investigate wind retrieval algorithm improvements for reprocessed Aeolus data sets.

Estimating the benefit of Doppler wind lidars for short‐term low‐level wind ensemble forecasts

AbstractThis work focuses on the potential of a network of Doppler lidars for the improvement of short‐term forecasts of low‐level wind. For the impact assessment, we developed a new methodology that is based on ensemble sensitivity analysis (ESA). In contrast to preceding network design studies using ESA, we calculate the explicit sensitivity including the inverse of the background covariance matrix to account directly for the localization scale of the assimilation system. The new method is applied to a pre‐existing convective‐scale 1,000‐member ensemble simulation to mitigate effects of spurious correlations. We evaluate relative changes in the variance of a forecast metric, that is, the low‐level wind components averaged over the Rhein–Ruhr metropolitan area in Germany. This setup allows us to compare the relative variance change associated with the assimilation of hypothetical observations from a Doppler wind lidar with respect to the assimilation of surface‐wind observations only. Furthermore, we assess sensitivities of derived variance changes to a number of settings, namely observation errors, localization length scale, regularization factor, number of instruments in the network, and their location, as well as data availability of the lidar measurements. Our results demonstrate that a network of 20–30 Doppler lidars leads to a considerable variance reduction of the forecast metric chosen. On average, an additional network of 25 Doppler lidars can reduce the 1–3 hr forecast error by a factor of 1.6–3.3 with respect to 10‐m wind observations only. The results provide the basis for designing an operational network of Doppler lidars for the improvement of short‐term low‐level wind forecasts that could be especially valuable for the renewable energy sector.

High Resolution Coherent Doppler Wind Lidar Incorporating Phase-Shift Keying

A coherent Doppler wind lidar (CDWL) with spatial/temporal resolution of meter and sub-second scale is reported. Phase-shift keying (PSK) is introduced into the pulse pair to enhance the measurement efficiency, and the pulse shaping and perfect binary PSK modulation are both realized by a single Mach-Zehnder modulator (MZM). The identical intensity envelope of the paired pulses reduces the influence of amplifier's gain profile and provides a monitoring parameter for bias control, which improves the system stability in practice. Theoretical analysis and numerical simulation are conducted to illustrate the principle of the proposed method. In experiments, the bias drift of the MZM is monitored in real time. Continuous radial wind profile measurement over 800 m is demonstrated with spatial and temporal resolution of 3 m and 0.1 s, respectively.

Quality control and error assessment of the Aeolus L2B wind results from the Joint Aeolus Tropical Atlantic Campaign

Abstract. Since the start of the European Space Agency's Aeolus mission in 2018, various studies were dedicated to the evaluation of its wind data quality and particularly to the determination of the systematic and random errors in the Rayleigh-clear and Mie-cloudy wind results provided in the Aeolus Level-2B (L2B) product. The quality control (QC) schemes applied in the analyses mostly rely on the estimated error (EE), reported in the L2B data, using different and often subjectively chosen thresholds for rejecting data outliers, thus hampering the comparability of different validation studies. This work gives insight into the calculation of the EE for the two receiver channels and reveals its limitations as a measure of the actual wind error due to its spatial and temporal variability. It is demonstrated that a precise error assessment of the Aeolus winds necessitates a careful statistical analysis, including a rigorous screening for gross errors to be compliant with the error definitions formulated in the Aeolus mission requirements. To this end, the modified Z score and normal quantile plots are shown to be useful statistical tools for effectively eliminating gross errors and for evaluating the normality of the wind error distribution in dependence on the applied QC scheme, respectively. The influence of different QC approaches and thresholds on key statistical parameters is discussed in the context of the Joint Aeolus Tropical Atlantic Campaign (JATAC), which was conducted in Cabo Verde in September 2021. Aeolus winds are compared against model background data from the European Centre for Medium-Range Weather Forecasts (ECMWF) before the assimilation of Aeolus winds and against wind data measured with the 2 µm heterodyne detection Doppler wind lidar (DWL) aboard the Falcon aircraft. The two studies make evident that the error distribution of the Mie-cloudy winds is strongly skewed with a preponderance of positively biased wind results distorting the statistics if not filtered out properly. Effective outlier removal is accomplished by applying a two-step QC based on the EE and the modified Z score, thereby ensuring an error distribution with a high degree of normality while retaining a large portion of wind results from the original dataset. After the utilization of the described QC approach, the systematic errors in the L2B Rayleigh-clear and Mie-cloudy winds are determined to be below 0.3 m s−1 with respect to both the ECMWF model background and the 2 µm DWL. Differences in the random errors relative to the two reference datasets (Mie vs. model is 5.3 m s−1, Mie vs. DWL is 4.1 m s−1, Rayleigh vs. model is 7.8 m s−1, and Rayleigh vs. DWL is 8.2 m s−1) are elaborated in the text.

Estimation and characterization of the refractive index structure constant within the marine atmospheric boundary layer.

We verified the feasibility of an alternative solution to generate temperature and pressure profiles with the U.S. standard atmosphere model (USSA-76). We simultaneously integrated this model with conventional meteorological parameters measured by a weather station in the course of estimating the refractive index structure constant (C n2). Moreover, a continuous-time-series estimation method of the refractive index structure constant was established within the marine atmospheric boundary layer (ABL) based on wind data obtained from a coherent Doppler wind lidar (CDWL). We also analyzed the optical turbulence characteristics induced by wind shear during the conducted experiment. Laminated and patchy stratified turbulences, which affect the performance of imaging and light transmission systems, were found within the marine ABL. Additionally, the relationship between the ABL and all atmospheric optical turbulence factors shows that the ratio of marine ABL in the entire layer differs from that reported in previous studies. Moreover, the influence of thermal turbulence factors within the marine ABL was less than that of the entire layer in our case. We report a real-time C n2 estimation method based on a CDWL. The characteristics of the marine ABL C n2 constitute a reference for optoelectronic applications.

A Hybrid Genetic/Powell Algorithm for Wind Measurement in Doppler Lidar

Doppler peaks extraction from massive raw data is a tricky part of coherent Doppler wind Lidar (CDWL) optimization. In this paper, a hybrid genetic/Powell algorithm (HGAP) is proposed to process the power spectrum of the measured signal from CDWL. The HGAP has excellent global exploration capability, which likes traditional genetic algorithms and fast convergence, which like the Powell method. Hence, the HGAP has advantages to find the center frequency of the Doppler peaks from massive raw data, especially to search multiple peaks in complex wind field measurement. Compared with other notable algorithms, the HGAP shows excellent performance in numerical optimization when we use it to solve 27 typical benchmark functions. Then, our algorithm is used to process the raw data in a field experiment of radial wind measurement. The results show that the HGAP can obtain wind speed components quickly and accurately and has value for application in complex wind field analysis.

Local-Scale Horizontal CO2 Flux Estimation Incorporating Differential Absorption Lidar and Coherent Doppler Wind Lidar

A micro-pulse lidar system incorporating differential absorption lidar (DIAL) and coherent Doppler wind lidar (CDWL) is proposed and demonstrated. Due to the high signal-to-noise ratio (SNR) of the superconducting nanowire single-photon detector (SNSPD), the DIAL channel achieves high sensitivity in CO2 measurement. Meanwhile, the CDWL channel is used to obtain the horizontal wind field. In the process of the optimization and calibration of the DIAL receiver, specifically, mode scrambling and temperature control of the connecting fiber between the telescope and the SNSPD enhance the stability and robustness of the system. Horizontal scanning of the CO2 concentration and the wind field is carried out in a 6 km range over a scanning span of 60° with a radial resolution of 150 m and 15 s. The results show that the hybrid lidar system captures the spatial distribution of CO2 concentration and the wind field simultaneously. The horizontal net CO2 flux in a radius of 6 km is estimated by integrating the CO2 concentration and the wind transport vector, indicating different characteristics of horizontal net CO2 fluxes in an industrial area, a university campus, and a park. During most of the experiment, CO2 flux remained positive in the industrial area, but balances fell to nearly zero on the campus and in the park. The horizontal net fluxes averaged over 24 h in the three areas are 3.5 × 105 ppm·m2·s−1, 0.7 × 105 ppm·m2·s−1, and 0.1 × 105 ppm·m2·s−1.

1.8 m/0.5 s Resolution Coherent Doppler Wind Lidar Using Continuous Phase Modulation

A high-spatial-resolution coherent Doppler wind lidar (CDWL) with high modulation efficiency is reported. The pseudo-random phase coding (PRPC) links the spatial resolution to the modulation rate but suffers from the non-rectangular transition caused by the limited bandwidth. With the help of continuous phase modulation (CPM), the abrupt phase switching between successive bit intervals is avoided, thus significantly reducing the bandwidth requirement. By mapping the binary sequence into different transition states rather than phase levels, a 10-fold modulation efficiency improvement is realized. In experiments, the performance of the proposed lidar is compared with lidars in the PRPC method and conventional non-coding method. Continuous radial wind profile measurement of 800 m is demonstrated with spatial and temporal resolution of 1.8 m and 0.5 s, which is the highest spatial resolution realized by a pulsed CDWL to our best knowledge.

Scanning Doppler LIDAR wind profiles to inform near shore atmospheric acoustic propagation modeling

This work presents a comprehensive experimental system to measure concurrent atmospheric acoustic transmission loss and meteorological conditions. A three-dimensional scanning Doppler lidar wind profiler captures real-time wind speed gradients at many locations along the acoustic propagation path of a simple pitch catch style study. A long-range acoustic device on an anchored pontoon sends known chirp sequences to a seven-channel receiver array at the water’s edge at ranges up to approximately one kilometer. Additional synchronized meteorological observations include temperature, humidity, and wind measured with anemometers. The meteorological data stream is used to inform the sound speed gradient implemented in a parabolic equation based numerical model of atmospheric acoustic propagation. The model can account for sea surface roughness and accommodate a sound speed profile that changes along the propagation range. Model predictions are compared to measured transmission losses. An assessment of the value of the computational cost of incorporating the varying sound speed profiles in the model is presented.