Radial Wind Research Articles

The urban effects on the planetary boundary layer wind structures of typhoon Lekima (2019)

The urban effects on the planetary boundary layer (PBL) wind structures of landfalling tropical cyclones (TCs) have rarely been explored. In this study, numerical simulations for typhoon Lekima (2019), with and without multilayer building effect parameterization (BEP) and urban surfaces, were executed to investigate the urban effects on TC PBL wind structures. Validations against observations demonstrate that the simulation incorporating BEP and urban surface more accurately replicates the track, intensity and 10-m wind field of Lekima (2019). Based on the comparison between the simulations with and without urban surface, urban effects were analyzed, and the possible mechanisms were examined from the perspective of turbulent transport. Results show that urban surfaces have a deceleration effect on TC wind fields overall. This deceleration effect is most pronounced near the surface and decreases with height under 1 km above ground level. Urban surfaces reduce tangential winds and radial inflow in the near-surface layer, leading to a slight decrease in TC intensity. This is primarily attributed to the enhanced downward transfer of tangential momentum and upward transfer of radial momentum within the PBL, which results in larger magnitudes of negative tangential wind tendencies and positive radial wind tendencies induced by the divergence of subgrid-scale (SGS) momentum fluxes. Additionally, stronger tangential winds and radial outflow above the elevated PBL height correspond well to the increased tangential and radial wind tendencies in nearby areas. The analysis illustrates that turbulent transport provides insights into how urban surfaces affect the PBL wind structures of TCs.

Characterizing surface pressure and wind fields of typhoons approaching Hong Kong

In this paper, 17 severe typhoons that have affected Hong Kong are simulated using an advanced numerical atmospheric simulation system - Weather Research and Forecasting model (WRF). The simulated surface pressure and wind fields of these typhoons are validated against a wide range of field observations. Then azimuth-dependent models for the radius of maximum winds and the Holland parameter are established statistically at the surface level. It is observed that the shape parameter of the Holland pressure model is smaller at the surface than that at the gradient level. And the Holland wind field model cannot well reproduce the simulated radial wind profiles due to the complexities of nonuniform surface conditions and typhoon dynamics. It is found that the modified Rankine model provides satisfactory estimates of typhoon wind speeds in Hong Kong. Additionally, wind field asymmetries of typhoons approaching Hong Kong are highly correlated with the typhoon track velocity, vertical wind shear and the angle between them. The proposed statistical models and identified characteristics of wind field asymmetries of typhoons will provide useful information for rapidly assessing typhoon wind hazards.

Improvement of Wind Power Prediction by Assimilating Principal Components of Cabin Radar Observations

Abstract Data assimilation is an important approach to improve the prediction performance of near-surface wind and wind power. Based on the four-dimensional variational technique, this study proposes an approach to improve near-surface wind and wind power prediction by extracting and assimilating the principal components of cabin radar radial wind observations installed at wind turbines within a wind farm. The verification for a series of cases under strong and weak vertical wind shear conditions indicates that compared to the simulations without assimilation, the predicted ultra-short-term (0–4 h) mean absolute error of near-surface wind and single turbine wind power could be reduced by 0.09–1.17 m s−1 and 53–209 kW after the assimilation of radial wind directly and by 0.33–1.38 m s−1 and 62–239 kW after the assimilation of principal components. These illustrate that assimilating the principal components of radial wind is superior to assimilating radial wind directly and could obviously reduce prediction error. Further investigation suggests that extracting the principal components of radial wind has marginal influences on the density and distribution of observations, but could obviously reduce the fluctuation of the observations and the correlation among the observations. The prediction improvement by assimilating the principal components of radial wind is essentially due to the assimilation of low-frequency and low-correlation information involved in the observations.

Contraction of the radius of maximum symmetric rotational kinetic energy during the intensification of Tropical Cyclone Khanun (2017)

Tropical cyclone (TC) Khanun in 2017 was simulated in this study by the Weather Research and Forecasting (WRF) model. The observation-validated simulation data were used to examine how asymmetric rotational and environmental flows played the roles in determining the contraction of the radius of maximum kinetic energy of symmetric rotational flow (Kψs). The radius of maximum Kψs was contracted rapidly before rapid intensification (RI) and moved inward slowly, then barely moved, and moved inward slowly again during RI.The conversion from kinetic energy of asymmetric rotational flow (Kψa) to Kψs was induced by advection of asymmetric rotational tangential wind by asymmetric divergent radial wind. The conversion and convergence of inward flux of Kψs led to the rapid contraction before RI. During RI, in additional to horizontal and vertical flux convergence of Kψs, the conversion from environmental kinetic energy (Ke) to Kψs through the interaction between Kψs and symmetric radial environmental flow was important for the second slow contraction.

Research on integrated LiDAR and multi-parameter detection of atmospheric transmittance, turbulence, and wind

An integrated LiDAR system has been reported, which can be used for simultaneous detection of atmospheric transmittance, turbulence, and wind along the same path. Through the integrated design of optics and mechanics, the size and weight of the system were effectively reduced. The comprehensive detection distance of atmospheric transmittance, atmospheric coherence length, and radial wind had also been achieved at least 4 kilometers. Comparative experiments have demonstrated that the detection results of the integrated LiDAR system and the near-surface meteorological observation system have standard deviations of less than 0.03 km−1 for extinction coefficient, 0.2 m/s for wind velocity, and 7.15 × 10−14 m−2/3 for C 2 n (atmospheric refractive index structure parameter), thus verifying the accuracy of the system detection. The reliability of the integrated LiDAR system was validated through six consecutive nights of continuous detection experiments, measuring three parameters simultaneously. Through analysis, the influence laws among atmospheric transmittance, coherence length, and wind were preliminarily explored. Significant variations in wind velocity can induce substantial fluctuations in atmospheric coherence length, and it is positively correlated with atmospheric transmittance. The integrated LiDAR system can provide a variety of reliable real-time detection data for further research on the laser transmission process in the atmosphere.

A 3D-Var assimilation scheme for vertical velocity with CMA-MESO v5.0

Abstract. Certain vertical motions associated with meso-microscale systems are favorable for convection development and maintenance. Correct initialization of updraft motions is thus significant in convective precipitation forecasts. A three-dimensional variational-based vertical velocity (w) assimilation scheme has been developed within the high-resolution (3 km) CMA-MESO (the Mesoscale Weather Numerical Forecast System of the China Meteorological Administration) model. This scheme utilizes the adiabatic Richardson equation as the observation operator for w, enabling the update of horizontal winds and mass fields of the model's background. The tangent linear and adjoint operators are subsequently developed and undergo an accuracy check. A single-point w observation assimilation experiment reveals that the observational information is effectively spread both horizontally and vertically. Specifically, the assimilation of w contributes to the generation of horizontal wind convergence at lower model levels and divergence at higher model levels, thereby adjusting the locations of convection occurrence. The impact of assimilating w on the forecast is then examined through a series of continuous 10 d runs. Further assimilation of w, in addition to the assimilation of conventional and radial wind data, significantly improves the forecast accuracy of precipitation, resulting in higher FSS (fractions skill score) values and higher ETS (equitable threat score) skills at higher thresholds (5 and 20 mm h−1). However, it should be noted that further assimilation of w can potentially lead to some false precipitation, resulting in slightly lower ETS values at lower thresholds (1 mm h−1) and a neutral impact on BIAS (bias score) skills. An individual case study conducted within the batch experiments reveals that assimilating w has a beneficial impact on the enhancement of vertical motion across different layers of the model, facilitating the transport of moisture from lower to middle–high model levels, thereby leading to an improvement in forecast skills.

Dynamic Response Analysis of Moving Trains Passing Through the Stationary Thunderstorm Downburst Wind

The safety of the high-speed train traveling through the stationary thunderstorm downburst wind was studied. First, a thunderstorm wind test device was used to simulate the stationary thunderstorm downburst wind. Based on the rigid model pressure measurement tests, the aerodynamic forces of the train traveling along different paths through the stationary thunderstorm downburst wind were measured. The influence of the radial distance of the crossing path on the aerodynamic force coefficients of the train was investigated. On this basis, an unsteady aerodynamic model of the high-speed train crossing through the stationary thunderstorm downburst wind was established, and dynamic response analysis was carried out using the SIMPACK multibody dynamics simulation software to explore further the safety of the high-speed train crossing through the stationary thunderstorm downburst wind. The research showed that the stationary thunderstorm downburst wind field has significant spatial variation characteristics compared with the atmospheric boundary layer wind field. When the train passes through the thunderstorm downburst wind, the radial wind speed and wind yaw angle experienced by the train constantly change, and the change curve shows a symmetrical distribution. The aerodynamic force of the train will undergo sudden loading and unloading processes, and the lateral force coefficient of the train on different paths shows a “pulse-type” variation. Moreover, the lateral force coefficient increases with the increase of wind yaw angle. Under the influence of the thunderstorm downburst wind, the variation trend of the aerodynamic force coefficients of the train is consistent with that under crosswind. However, there are significant differences in the numerical values. Therefore, it is impossible to simply use the formula for calculating the aerodynamic force coefficients of the train under crosswinds to predict the aerodynamic force coefficients of the train under the thunderstorm downburst wind. While passing through the thunderstorm downburst wind, the overturning coefficient index plays a decisive role in the safety of train operations. Train rollover is the main form of train safety accidents, while derailment accidents are not easy. The numerical results obtained in this study are significant for evaluating the operational safety while moving trains traversing the stationary thunderstorm downburst wind.

Assessing the Fidelity of Landfalling Tropical Cyclone Convective‐Scale Environments in the Warn‐On‐Forecast System Using Radiosondes

AbstractForecasts of tropical cyclone (TC) tornadoes are less skillful than their non‐TC counterparts at all lead times. The development of a convection‐allowing regional ensemble, known as the Warn‐on‐Forecast System (WoFS), may help improve short‐fused TC tornado forecasts. As a first step, this study investigates the fidelity of convective‐scale kinematic and thermodynamic environments to a preliminary set of soundings from WoFS forecasts for comparison with radiosondes for selected 2020 landfalling TCs. Our study shows reasonable agreement between TC convective‐scale kinematic environments in WoFS versus observed soundings at all forecast lead times. Nonetheless, WoFS is biased toward weaker than observed TC‐relative radial winds, and stronger than observed near‐surface tangential winds with weaker winds aloft, during the forecast. Analysis of storm‐relative helicity (SRH) shows that WoFS underestimates extreme observed values. Convective‐scale thermodynamic environments are well simulated for both temperature and dewpoint at all lead times. However, WoFS is biased moister with steeper lapse rates compared to observations during the forecast. Both CAPE and, to a lesser extent, 0–3‐km CAPE distributions are narrower in WoFS than in radiosondes, with an underestimation of higher CAPE values. Together, these results suggest that WoFS may have utility for forecasting convective‐scale environments in landfalling TCs with lead times of several hours.

The role of heating in the formation and the dynamics of YSO jets

Context. Theoretical arguments as well as observations of young stellar objects (YSOs) support the presence of a diversified circumstellar environment. A stellar jet is thought to account for most of the stellar spin down and disk wind outflow for the observed high mass-loss rate, thus playing a major role in the launching of powerful jets. RY Tau, for instance, is an extensively studied intermediate mass pre-main sequence star. Observational data reveal a small-scale jet called micro-jet. Nevertheless, it is not clear how the micro-jet shapes the jet observed at a large scale. Aims. The goal is to investigate the spatial stability and structure of the central jet at a large scale by mixing the stellar and disk components. Methods. Two existing analytical self-similar models for the disk and the stellar winds to build the initial setups. Instead of using a polytropic equation of state, we mapped the heating and cooling sources from the analytical solutions. The heating exchange rate was controlled by two parameters, its spatial extent and its intensity. Results. The central jet and the surrounding disk are strongly affected by these two parameters. We separate the results into three categories, which show different emissivity, temperature, and velocity maps. We reached this categorization by looking at the opening angle of the stellar solution. For cylindrically, well-collimated jets, we have opening angles as low as 10° between 8 − 10 au, and for the wider jets, we can reach 30° with a morphology closer to radial solar winds. Conclusions. Our parametric study shows that the less heated the outflow is, the more collimated it appears. We also show that recollimation shocks appear consistently with UV observations in terms of temperature but not density.

Near-wake measurements and simulations of a floating wind turbine using a four-beam nacelle-based lidar

Recent advances in lidar technology have expanded the possibilities for measuring full-scale wind turbine wakes within the atmospheric boundary layer. This study utilizes a four-beam pulsed lidar installed on the nacelle of a floating turbine to measure the near-wake. The wake measurement campaign was conducted on the Floatgen, with lidar measurements reaching up to 2.5 times the rotor diameter distance. These measurements are presented as 10-minute average radial wind speeds. The focus of this study is on the below rated wind speed of 7 m/s. Free flow conditions were assumed at the farthest measurement points, which are located ±0.9 times the rotor diameter from to the rotor center. The sensitivity of lidar measurements to turbulence intensity, vertical wind shear, and significant wave height was investigated. The environmental conditions were categorized into five cases, considering turbulence, vertical shear, and yaw misalignment as well as waves. Two simulation models with different fidelity levels are used to simulate these cases, and the beam-wise radial wind speed predictions are compared with the measurements. A maximum mean absolute error of 11.3% between the measurements and simulations is observed.

Dual-Frequency, Dual-Mode Reconfigurable Digital Atmospheric Radar Receiver Design

A new dual-frequency, dual-mode reconfigurable digital receiver based on Field-Programmable Gate Array (FPGA) dynamic reconfiguration is proposed, which is based on a common hardware platform of high-bandwidth RF front-end, high-speed data acquisition, and real-time signal processing. The receiver adopts the design of dynamically reconfigurable down-conversion, filter extraction, and matched filtering in the digital domain. In this study, we completed the design and development of the digital receiver, experimental platform construction, and field detection test with hardware and software cooperation. The experimental results show that the receiver achieves full digital reception and signal processing for 53.8 MHz stratosphere–troposphere (ST) detection and 35.0 MHz meteor detection and successfully acquired the number of meteors versus time, the meteor trail, and low-altitude atmospheric radial winds. This dual-frequency, dual-mode reconfigurable digital receiver can be applied to new-generation multifunction integrated radar systems such as dual-frequency ST/meteor radars.

Near-Surface Wind Profiling in a Utility-Scale Onshore Wind Farm Using Scanning Doppler Lidar: Quality Control and Validation

Wind profiling within operating wind farms is important for both wind resource assessment and wind power prediction. With increasing wind turbine size, it is getting difficult to obtain wind profiles covering the turbine-affecting area due to the limited height of wind towers. In this study, a stepwise quality control and optimizing process for deriving high-quality near-surface wind profiles within wind farms is proposed. The method is based on the radial wind speed obtained by the Doppler Wind Lidar velocity-azimuth display (VAD) technique. The method is used to obtain the whole wind profile from ground level to the height affected by wind turbines within a utility-scale onshore wind farm, in northern China. Compared with the traditional carrier-to-noise ratio (CNR) filter-based quality control method, the proposed data processing method can significantly improve the accuracy of the derived wind. For a 10 m wind speed, an increase in coefficient of determination (R2) from 0.826 to 0.932, and a decrease in mean absolute error (MAE) from 1.231% to 0.927% are obtained; while for 70 m wind speed, R2 increased from 0.926 to 0.958, and MAE decreased from 1.023% to 0.771%. For wind direction, R2 increased from 0.978 to 0.992 at 10 m, and increased from 0.983 to 0.995 at 70 m. The optimized method also presents advantages in improving the accuracy of derived wind under complex wind environments, e.g., inside a wind farm, and increasing the data availability during clear nights. The proposed method could be used to derive wind profiles from below the minimum range of a vertically operating scanning Doppler Lidar to a height affected by wind turbines. Combined with Doppler beam-swinging (DBS) scanning data, the method could be used to obtain the complete wind profile in the boundary layer. These wind profiles could be further used to predict wind power and evaluate the climate and environmental effects of wind farms.

An Online Feedback-Based Local Method for Topology Identification and Var/Volt Control in Radial Wind Farms

An Online Feedback-Based Local Method for Topology Identification and Var/Volt Control in Radial Wind Farms

The role of the cold pool in a mountain-to-plain and plain-to-mountain squall line case in the south of the Yangtze River in China

A squall line event that occurred in the south of the Yangtze River in China on 4 May 2020 was simulated using the WRF model and 3DVAR data assimilation. The radar radial wind, reflectivity, and conventional observation data were assimilated in a cycling interval of 15 min. The main findings from the examination of the development mechanisms of the squall line are as follows. The simulation effectively reproduced the development and evolution of the squall line. The squall line strengthened from the Wuling Mountains to the Dongting Lake Plain, moved eastwards and developed to its strongest stage over the plains, before weakening from thereon to the Mulianjiu Mountains. When the squall line moved from the mountains to the plains, the convergence of the airflow in front of the squall line increased because of the strengthening of the near-surface easterly airflow over the plains. Concurrently, the intensity of the cold pool behind the squall line decreased, while the low-level vertical wind shear over the plains increased. This reduced the gap between the cold pool and vertical wind shear. The low-level upward airflow in front of the cold pool tended to be vertical, which was conducive to the development and maintenance of the squall line. When the squall line moved eastwards from the plains to the mountains, the convergence of the airflow in front of the squall line weakened because of the weakening of the surface easterly airflow over the mountains. Concurrently, the intensity of the cold pool behind the squall line increased, while the low-level vertical wind shear in front of the squall line significantly declined. The intensity of the cold pool significantly exceeded the low-level vertical wind shear, inducing a tendency for the low-level upward airflow in front of the cold pool to tilt towards the cold pool, which was not conducive to the development and maintenance of the squall line. This was a reason why the squall line moved eastwards faster after going up the mountains. Based on these observational and simulation results, physical conceptual models for the enhancement of squall lines from the mountains to the plains and their weakening from the plains to the mountains have been preliminarily developed.

Denoising coherent Doppler lidar data based on a U-Net convolutional neural network.

The coherent Doppler wind lidar (CDWL) has long been thought to be the most suitable technique for wind remote sensing in the atmospheric boundary layer (ABL) due to its compact size, robust performance, and low-cost properties. However, as the coherent lidar exploits the Mie scattering from aerosol particles, the signal intensity received by the lidar is highly affected by the concentration of aerosols. Unlike air molecules, the concentration of aerosol varies greatly with time and weather, and decreases dramatically with altitude. As a result, the performance of the coherent lidar fluctuates greatly with time, and the detection range is mostly confined within the planetary boundary layer. The original data collected by the lidar are first transformed into a spectrogram and then processed into radial wind velocities utilizing algorithms such as a spectral centroid. When the signal-to-noise ratio (SNR) is low, these classic algorithms fail to retrieve the wind speed stably. In this work, a radial wind velocity retrieving algorithm based on a trained convolutional neural network (CNN) U-Net is proposed for denoising and an accurate estimate of the Doppler shift in a low-SNR regime. The advantage of the CNN is first discussed qualitatively and then proved by means of a numerical simulation. Simulated spectrum data are used for U-Net training and testing, which show that the U-Net is not only more accurate than the spectral centroid but also achieves a further detection range. Finally, joint observation data from the lidar and radiosonde show excellent agreement, demonstrating that the U-Net-based retrieving algorithm has superior performance over the traditional spectral centroid method both in accuracy and detection range.

Rayleigh Doppler Lidar Technology Based on a Quadruple Dual-pass Fabry–Perot Interferometer

A novel Rayleigh Doppler lidar technology based on a quadruple dual-pass Fabry–Perot interferometer (FPI) that can accurately measure wind field, temperature and aerosol backscatter ratio from the troposphere to lower stratosphere is proposed. This study aims to analyse the detection principle of wind speed, temperature and aerosol backscatter ratio in detail and obtain their measurement error formulas. The structure of this type of lidar is studied and designed. The FPI consists of two edge channels FPI-1 and FPI-2, aerosol channel FPI-M and locking channel FPI-L. FPI-1, FPI-2 and FPI-M use a dual-pass optical path, whereas FPI-L uses a single-pass optical path. The parameters of FPI are optimised as follows: the free spectral spacing (FSR) is 12 GHz, the FWHM of FPI-1 and FPI-2 are both 2.2 GHz, the peak-to-peak interval of FPI-1 and FPI-2 is 5.8 GHz, the FWHM of FPI-M and FPI-L are both 1.2 GHz, the peak-to-peak interval of FPI-M and FPI-1 is 2.9 GHz and the peak-to-peak interval of FPI-L and FPI-1 is 2.3 GHz. Under simulated atmospheric conditions, for a daytime sky background brightness of 0.3 Wsr−1m−2nm−1 at 355 nm, using a laser with a pulse energy of 350 mJ and a repetition frequency of 50 Hz and a telescope with a 0.45-m aperture, with a vertical range resolution of 30 m at 0–10 km, 100 m at 10–20 km and 500 m at 20–35km, temporal resolution of 30 min, zenith angle of 0° for temperature and aerosol backscatter ratio detection and temporal resolution of 3 min and zenith angle of 30° for radial wind speed detection, the detection performance of the designed Rayleigh Doppler lidar is determined. The simulation results show that the measurement errors of aerosol backscatter ratio, temperature and radial wind speed of the lidar system in the daytime and night-time are less than 4.36 × 10−3 and 3.32 × 10−3 (excluding cirrus cloud area), 4.0 K and 3.0 K and 3.8 m/s and 1.9 m/s, respectively, from an altitude of 0.06 to 35km.

Reexamining the Estimation of Tropical Cyclone Radius of Maximum Wind from Outer Size with an Extensive Synthetic Aperture Radar Dataset

Abstract The radius of maximum wind Rmax, an important parameter in tropical cyclone (TC) ocean surface wind structure, is currently resolved by only a few sensors so that, in most cases, it is estimated subjectively or via crude statistical models. Recently, a semiempirical model relying on an outer wind radius, intensity, and latitude was fit to best-track data. In this study we revise this semiempirical model and discuss its physical basis. While intensity and latitude are taken from best-track data, Rmax observations from high-resolution (3 km) spaceborne synthetic aperture radar (SAR) and wind radii from an intercalibrated dataset of medium-resolution radiometers and scatterometers are considered to revise the model coefficients. The new version of the model is then applied to the period 2010–20 and yields Rmax reanalyses and trends that are more accurate than best-track data. SAR measurements corroborate that fundamental conservation principles constrain the radial wind structure on average, endorsing the physical basis of the model. Observations highlight that departures from the average conservation situation are mainly explained by wind profile shape variations, confirming the model’s physical basis, which further shows that radial inflow, boundary layer depth, and drag coefficient also play roles. Physical understanding will benefit from improved observations of the near-core region from accumulated SAR observations and future missions. In the meantime, the revised model offers an efficient tool to provide guidance on Rmax when a radiometer or scatterometer observation is available, for either operations or reanalysis purposes.

Optimal Use of Radar Radial Winds in the HARMONIE Numerical Weather Prediction System

Abstract The use of radial velocity information from the European weather radar network is a challenging task, because of a heterogeneous radar network and the different ways of providing the Doppler velocity information. Preprocessing is therefore needed to harmonize the data. Radar observations consist of a very high resolution dataset, which means that it is both demanding to process as well as that the inherent resolution is much higher than the model resolution. One way of reducing the number of data is to create “super observations” (SO) by averaging observations in a predefined area. This paper describes the preprocessing necessary to use radar radial velocities in the data assimilation where the SO construction is included. Our main focus is to optimize the use of radial velocities in the HARMONIE–AROME numerical weather model. Several experiments were run to find the best settings for first-guess check limits as well as a tuning of the observation error value. The optimal size of the SO and the corresponding thinning distance for radar radial velocities was also studied. It was found that the radial velocity information and the reflectivity from weather radars can be treated differently when it comes to the size of the SO and the thinning. A positive impact was found when adding the velocities together with the reflectivity using the same SO size and thinning distance, but the best results were found when the SO and thinning distance for the radial velocities are smaller than the corresponding values for reflectivity.

Two-dimensional MHD modelling of switchbacks from jetlets in the slow solar wind

Solar wind switchbacks are polarity reversals of the magnetic field, recently frequently measured by Parker Solar Probe inside 0.2 AU. In this Letter we show that magnetic switchbacks, similar to those observed by PSP, are reproduced by injecting a time-limited collimated high-speed stream in the Parker spiral. We performed a 2D magnetohydrodynamics simulation with the PLUTO code of a slightly inclined jet at 1000 km s−1 between 5 and 60 R⊙. The jet rapidly develops a field inversion at its wings and, at the same time, it is bent by the Parker spiral. The match with the radial outward wind field creates two asymmetric switchbacks, one that bends to the anti-clockwise and one that bends to the clockwise direction in the ecliptic plane, with the last one being the most extended. The simulation shows that such S-shaped magnetic features travel with the jet and persist for several hours and to large distances from the Sun (beyond 20 R⊙). We show the evolution of physical quantities as they would be measured by a hypothetical detector at a fixed position when crossed by the switchback, for comparison with in situ measurements.

Multi-longitudinal-mode Doppler lidar technology based on quadri-channel Mach–Zehnder interferometer

The detection principle of a multi-longitudinal-mode (MLM) Doppler lidar based on a quadri-channel Mach–Zehnder interferometer (QMZI) was analysed. The measurement error formulas for the radial wind speed and backscatter ratio of this type of Doppler lidar system were derived. The advantages of this detection technology were thoroughly analysed based on the principle. The optical path difference (OPD) ‘l’ between the two interference arms of the QMZI was optimised. For a detection height of 0–20 km, ‘l’ was selected as 50 cm to balance the detection of radial wind speed and backscatter ratio. The overall structure of the MLM Doppler lidar based on QMZI was designed, and detailed design parameters of the system were provided. Further simulation was conducted to evaluate the detection performance of the designed QMZI- based MLM Doppler lidar system. The simulation results showed that when using a pulse laser with a power of 17.5 W@355 nm and a telescope with an aperture of 25 cm, a detection zenith angle of 30°, a vertical resolution of 26 m@0–10 km and 52 m@10–20 km and a pulse accumulation time of 1 min, the radial wind speed measurement errors of the system during the day and night were less than 2.1 m/s and 2.5 m/s; the backscatter ratio relative measurement errors were less than 0.81% and 0.97%.