Search Results (51)

This study used reanalysis and lidar observations to investigate nocturnal downslope wind events in the Taklimakan desert, revealing their vertical structure, influencing factors, climatology, and impacts on boundary layer dynamics and dust emissions. 125 events were detected along the northern slope of the Kunlun Mountains, impacting Minfeng. Due to its weakness after onset, downslope flow is deflected horizontally when it encounters the opposing synoptic winds. The continued radiative cooling, dense air drainage, and adiabatic warming intensify downslope flow as the night progresses, causing it to gradually sink and overcome the opposing synoptic winds. Downslope wind events typically occur between an hour before and two hours after sunset, with the strongest occurring at or before sunset due to the longer period of radiative cooling and the coincidence with early evening instability conditions. Strong events occur under weak stability conditions as a stable atmosphere with a strong inversion layer can inhibit sinking motion. Most events, even the strongest ones, occur under dry conditions due to enhanced radiative cooling. Mechanical turbulence occurs when downslope flow hits the surface, whereas thermal turbulence occurs when warmer, downslope air weakens the lower atmosphere’s temperature inversion. Downslope wind events significantly raise dust emissions in the Taklimakan desert. Full article

The Marine Atmospheric Boundary Layer (MABL), as a critical component of Earth’s climate system, governs the exchange of matter and energy between the ocean surface and the lower atmosphere. This study presents shipborne Doppler lidar observations conducted during 12 January to 3 February 2024, along the southeastern Chinese coast. Employing a Coherent Doppler Wind Lidar (CDWL) system onboard the R/V “Yuezhanyu” research vessel, we investigated the spatiotemporal variability of MABL characteristics through integration with ERA5 reanalysis data. The key findings reveal a significant positive correlation between MABL height and surface sensible heat flux in winter, underscoring the dominant role of sensible heat flux in boundary layer development. Through the Empirical Orthogonal Function (EOF) analysis of the ERA5 regional boundary layer height, sensible heat flux, and sea level pressure, we demonstrate MABL height over the coastal seas typically exceeds the corresponding terrestrial atmospheric boundary layer height and exhibits weak diurnal variation. The CDWL observations highlight complex wind field dynamics influenced by synoptic conditions and maritime zones. Compared to onshore regions, the MABL over offshore areas further away from land has lower wind shear changes and a more uniform wind field. Notably, the terrain of Taiwan, China, induces significant low-level jet formations within the MABL. Low-level jets and low boundary layer height promote the pollution episode observed by CDWL. This research provides new insights into MABL dynamics over East Asian marginal seas, with implications for improving boundary layer parameterization in regional climate models and advancing our understanding of coastal meteorological processes. Full article

Marine atmospheric boundary-layer height (MABLH) is crucial for ocean heat, momentum, and substance transfer, affecting ocean circulation, climate, and ecosystems. Due to the unique geographical location of the South China Sea (SCS), coupled with its complex atmospheric environment and sparse ground-based observation stations, accurately determining the MABLH remains challenging. Coherent Doppler wind lidar (CDWL), as a laser-based active remote sensing technology, provides high-resolution wind profiling by transmitting pulsed laser beams and analyzing backscattered signals from atmospheric aerosols. In this study, we developed a stacking optimal ensemble model (SOEM) to estimate MABLH in the vicinity of the site by integrating CDWL measurements from a representative SCS site with ERA5 (fifth-generation reanalysis dataset from the European Centre for Medium-Range Weather Forecasts) data from December 2019 to May 2021. Based on the categorization of the total cloud cover data into weather conditions such as clear/slightly cloudy, cloudy/transitional, and overcast/rainy, the SOEM demonstrates enhanced performance with an average mean absolute percentage error of 3.7%, significantly lower than the planetary boundary-layer-height products of ERA5. The SOEM outperformed random forest, extreme gradient boosting, and histogram-based gradient boosting models, achieving a robustness coefficient ($R^2$) of 0.95 and the lowest mean absolute error of 32 m under the clear/slightly cloudy condition. The validation conducted in the coastal city of Qingdao further confirmed the superiority of the SOEM in resolving meteorological heterogeneity. The predictions of the SOEM aligned well with CDWL observations during Typhoon Sinlaku (2020), capturing dynamic disturbances in MABLH. Overall, the SOEM provides a precise approach for estimating convective boundary-layer height, supporting marine meteorology, onshore wind power, and coastal protection applications. Full article

Understanding optical turbulence within the atmospheric boundary layer (ABL) is essential for refining atmospheric motion analyses, enhancing numerical weather prediction models, and improving light propagation assessments. This study develops an optical turbulence model for the boundary layer over the South China Sea (SCS) by integrating multiple observational and reanalysis datasets, including ERA5 data from the European Center for Medium-Range Weather Forecasts (ECMWF), radiosonde observations, coherent Doppler wind lidar (CDWL), and ultrasonic anemometer (CSAT3) measurements. Utilizing Monin–Obukhov Similarity Theory (MOST) as the theoretical foundation, the model’s performance is evaluated by comparing its outputs with the observed diurnal cycle of near-surface optical turbulence. Error analysis indicates a root mean square error (RMSE) of less than 1 and a correlation coefficient exceeding 0.6, validating the model’s predictive capability. Moreover, this study demonstrates the feasibility of employing ERA5-derived temperature and pressure profiles as alternative inputs for optical turbulence modeling while leveraging CDWL’s high-resolution observational capacity for all-weather turbulence characterization. A comprehensive statistical analysis of the atmospheric refractive index structure constant ($C_n^2$) from November 2019 to September 2020 highlights its critical implications for optoelectronic system optimization and astronomical observatory site selection in the SCS region. Full article

In this paper, a wind retrieval method based on genetic algorithm-particle swarm optimization (GA-PSO) for the coherent Doppler wind lidar (CDWL) is proposed. The algorithm incorporates an advanced optimization framework that considers wind field spatial continuity, simultaneously enhancing retrieval accuracy and computational efficiency. Comprehensive validations of the GA-PSO algorithm are conducted using a 1.5 μm all-fiber CDWL through ground-based and airborne experiments. In ground-based experiments, the GA-PSO algorithm extends the detection range by 20%~30% compared with traditional methods. The validation against meteorological tower data demonstrates excellent agreement, with mean deviations better than 0.27 m/s for horizontal wind speed and 3.07° for horizontal wind direction and corresponding RMSE values better than 0.36 m/s and 6.04°, respectively. During high-altitude airborne experiments at 5.5 km, the GA-PSO algorithm recovers up to 31% more horizontal wind speed and direction information compared with traditional algorithms, demonstrating exceptional performance in low signal-to-noise ratio (SNR) conditions. Both simulation analysis and field experiments demonstrate that the GA-PSO algorithm achieves processing speeds comparable to traditional real-time methods, establishing its suitability for real-time, three-dimensional wind retrieval applications. Full article

Pulsed Coherent Doppler Wind Lidar (CDWL) usually utilizes a fixed-length range gate to divide the time domain of the echo signal, which can lead to the incomplete sampling of echo signals, resulting in a spectral leakage phenomenon and affecting the wind speed inversion accuracy. In this paper, we propose to utilize the Hanning Self-Convolutional Window (HSCW) to preprocess the wind speed echo signal, suppress the spectral leakage phenomenon, and improve the wind speed inversion accuracy of the algorithm. Simulation experiments show that the signal-to-noise ratio (SNR) is 3.28 dB higher than that of the Rectangular Window (RW), and the average root mean square error (RMSE) values of the first- to third-order HSCW are 164.2 kHz, 116.7 kHz, and 101.9 kHz, respectively. The comparison of wind speed with a commercial CDWL shows that the RMSE of the second-order HSCW inversion result is 0.184 m/s, while the RW and first-order HSCW are 0.449 m/s and 0.266 m/s, respectively. Full article

The wind field, a critical atmospheric parameter, significantly influences climate, weather forecasting, aviation safety, and wind energy applications. The precise observation of wind fields is essential for improving weather predictions, studying climate change, ensuring aviation safety, and optimizing wind energy systems. Among the various wind field detection methods, coherent wind lidar technology stands out due to its superior detection range, accuracy, and robustness. However, the high-range resolution required for applications such as aircraft takeoff and landing or wind turbine region monitoring presents unique challenges in wind detection. To address the aforementioned challenges, this study established a modular coherent Doppler wind lidar simulation system. Unlike traditional single-module simulation approaches, this system achieves multi-parameter coupling analysis of laser emission under pulse modulation, atmospheric transmission, and wind speed inversion through integrated hardware-transmission-processing collaborative modeling. Subsequently, by adjusting key parameters of the system model, an in-depth analysis of wind speed inversion within a 1.2 km detection range was conducted, investigating the dual impacts of reducing pulse duration on both range resolution and wind speed measurement accuracy. Furthermore, a Mach–Zehnder modulator module was implemented in the radar hardware section to generate odd–even pulse pairs, while a differential correlation algorithm was introduced in the data processing module to enhance range resolution. Ultimately, wind speed measurements with a 4.5 m range resolution along the laser emission direction were achieved in simulations. Comparative analysis shows that pulse modulation techniques effectively reduce wind speed measurement errors caused by short-pulse methods, offering a reliable framework for practical wind field measurements. Full article

Coherent Doppler Wind Lidar (CDWL) is an effective tool for measuring the atmospheric wind field. However, CDWL is affected by various noises, which can reduce the usable value of the received echo signal. This paper proposes a novel joint denoising algorithm based on SVD-ICEEMDAN-SCC-MF to remove noises in CDWL detection. The SVD-ICEEMDAN-SCC-MF consists of singular value decomposition (SVD), improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN), Spearman correlation coefficient (SCC), and median filtering (MF). Specifically, the SVD first separates the signal from the noise by retaining the main feature (large singular value) and removing the remained components (small singular value) to achieve the initial signal reconstruction. Then, ICEEMDAN is used for decomposition to distinguish the intrinsic mode function (IMF) of the signal and the noise. The SCC of the retained components is calculated to determine the correlation of the reconstructed signal. Furthermore, low correlation components of the reconstructed signal are denoised again by median filtering (MF). Finally, the complete denoised signal is obtained by combining the components after MF and the high correlation components in the previous stage. The validity of the SVD-ICEEMDAN-SCC-MF is verified in simulated and real data, and the denoising effect is significantly better than other algorithms. In simulation cases, the $SN{R}_{out}$ of the proposed method is improved by 20.5117 dB at most, from −5 dB to 15.5117 dB, and the $RMSE$ is only 0.5174. After denoising the power spectrum of the real CDWL signal, the detection range is extended from 3 km to more than 3.6 km. Full article

In this paper, we present the logic designs of two FPGA hardware programming algorithms implemented for a Coherent Doppler Lidar system used in wind sensing. The first algorithm divides the received time-domain signals into segments, each corresponding to a specific spatial resolution. It then calculates the power spectrum for each segment and accumulates these spectra over 10,000 pulse returns. The second algorithm computes the autocorrelation of the received signals and accumulates the results over the same number of pulses. Both signal pre-processing algorithms are initially developed as logic designs and compiled using the Xilinx System Generator toolset to produce a hardware VLSI image. This image is subsequently programmed into an FPGA. However, the hardware implementation of these algorithms presents several challenges: (1) bit growth: multiplication operations in the binary number system significantly increase the number of bits, complicating hardware implementation. (2) Memory constraints: onboard RAM arrays of sufficient size are lacking for accumulating vectors of the calculated Fast Fourier Transforms (FFTs) or autocorrelations. (3) Signal drive issues: large fan-out in the logic design leads to significant capacitance, restricting the driving capabilities of transistor output signals. This article discusses the solutions devised to overcome these challenges. Additionally, it presents atmospheric wind measurements obtained using the two algorithms. Full article

This study investigated the influence of sea–land breezes on nocturnal spatial and temporal distribution of ozone (O₃) and its potential effects on particulate nitrate formation in Qingdao, a coastal city in northern China. Observation campaigns were conducted to measure surface air pollutants and meteorological factors during a typical sea–land breezes event from 22 to 23 July 2022. A coherent Doppler lidar (CDL) system was employed to continuously detect three-dimensional wind fields. The results revealed that nocturnal ozone levels were enhanced by a conversion of sea–land breezes. Initially, the prevailing northerly land breeze transported high concentrations of O₃ and other air pollutants from downtown to the Yellow Sea. As the sea breeze developed in the afternoon, the sea breeze front advanced northward, resulting in a flow of high O₃ concentrations back into inland areas. This penetration of the sea breeze front led to a notable spike in O₃ concentrations between 16:00 on 22 July and 02:00 on 23 July across downtown areas, with an average increase of over 70 μg/m³ within 10 min. Notably, a time lag in peak O₃ concentration was observed with southern downtown areas peaking before northern rural areas. During this period, combined pollution of O₃ and PM_2.5 was also observed. These findings indicated that the nighttime increase in O₃ concentrations, coupled with enhanced atmospheric oxidation, would likely promote the secondary conversion of gaseous precursors into PM_2.5. Full article

The long-term atmospheric mixing layer height (MLH) information plays an important role in air quality and weather forecasting. However, it is not sufficient to study the characteristics of MLH using long-term high spatial and temporal resolution data in the desert. In this paper, over the southern edge of the Taklimakan Desert, the diurnal, monthly, and seasonal variations in the daytime MLH (retrieved by coherent Doppler wind lidar) and surface meteorological elements (provided by the local meteorological station) in a two-year period (from July 2021 to July 2023) were statistically analyzed, and the relationship between the two kinds of data was summarized. It was found that the diurnal average MLH exhibits a unimodal distribution, and the decrease rate in the MLH in the afternoon is much higher than the increase rate before noon. From the seasonal and monthly perspective, the most frequent deep mixing layer (>4 km) was formed in June, and the MLH is the highest in spring and summer. Finally, in terms of their mutual relationship, it was observed that the east-pathway wind has a greater impact on the formation of the deep mixing layer than the west-pathway wind; the dust weather with visibility of 1–10 km contributes significantly to the formation of the mixing layer; the temperature and relative humidity also exhibit a clear trend of a concentrated distribution at about the height of 3 km. The statistical analysis of the MLH deepens the understanding of the characteristics of dust pollution in this area, which is of great significance for the treatment of local dust pollution. Full article

Aircraft wake vortices are serious threats to aviation safety. The Pulsed Coherent Doppler Lidar (PCDL) has been widely used in the observation of aircraft wake vortices due to its advantages of high spatial-temporal resolution and high precision. However, the post-processing algorithms require significant computing resources, which cannot achieve the real-time detection of a wake vortex (WV). This paper presents an improved Convolutional Neural Network (CNN) method for WV locating and grading based on PCDL data to avoid the influence of unstable ambient wind fields on the localization and classification results of WV. Typical WV cases are selected for analysis, and the WV locating and grading models are validated on different test sets. The consistency of the analytical algorithm and the CNN algorithm is verified. The results indicate that the improved CNN method achieves satisfactory recognition accuracy with higher efficiency and better robustness, especially in the case of strong turbulence, where the CNN method recognizes the wake vortex while the analytical method cannot. The improved CNN method is expected to be applied to optimize the current aircraft spacing criteria, which is promising in terms of aviation safety and economic benefit improvement. Full article

Coherent Doppler wind lidar (CDWL) uses transmitted laser pulses to measure wind velocity distribution. However, the echo signal of CDWL is easily affected by atmospheric turbulence, which can decrease the signal-to-noise ratio (SNR) of lidar. To improve the SNR, this paper proposes a pulse accumulation method based on the cross-correlation function to estimate the phase of the signal. Compared with incoherent pulse accumulation, the proposed method significantly enhances the correlation between signals from different periods to obtain high SNR gains that arise from pulse accumulation. Using simulation, the study evaluates the effectiveness of this phase estimation method and its robustness against noise in algorithms which analyze Doppler frequency shifts. Furthermore, a CDWL is developed for measuring the speed of an indoor motor turntable and the outdoor atmospheric wind field. The phase estimation method yielded SNR gains of 28.18 dB and 32.03 dB for accumulation numbers of 500 and 1500, respectively. The implementation of this method in motor turntable speed measurements demonstrated a significant reduction in speed error—averaging 9.18% lower than that of incoherent accumulation lidar systems. In experiments that measure atmospheric wind fields, the linear fit curve slope between the measured wind speed and the wind speed measured via a commercial wind-measuring lidar can be reduced from 1.146 to 1.093. Full article

Convective weather is often accompanied by precipitation and windshear, seriously endangering the safety of aircraft during takeoff and landing. However, under rainfall conditions, conventional wind lidars have a limited detection range due to significant signal attenuation. To solve this problem, a 200 mm temperature-controlled telescope coated with a hydrophobic film is applied in the coherent Doppler wind lidar system to improve the detection capability in rain. The maximum detection range of the lidar is extended to 30 km and demonstrated at Kunming Changshui International Airport at an altitude of 2102 m. Firstly, the detection accuracy and maximum detection range of the lidar are verified. Through the analysis of the horizontal wind field under two typical convective weather conditions, it is found that convective weather often accompanies low-level convergence and divergence structures, leading to headwind shear and crosswind shear on the airport runway. From the vertical profile, it is shown that the triggering of convective weather is accompanied by low-level southwest winds and high-altitude northeastern winds. According to the statistics of wind speed and direction on clear and rainy days over 9 months, rainy days are usually caused by the invasion of cold air from Northeast China, resulting in airport windshear. In summary, the enhanced lidar can effectively identify and analyze windshear during rainy days, which is very useful for aviation safety, especially for takeoff and landing in all weather conditions. Full article

Wind fields provide direct power for exchanging energy and matter in the atmosphere. All-fiber coherent Doppler lidar is a powerful tool for detecting boundary-layer wind fields. According to the characteristics of the lidar echo signal, an adaptive noise-reduction peak retrieval (ANRPR) algorithm is proposed in this study. Firstly, the power spectrum data are divided into several continuous range gates according to the time series. Then, the adaptive iterative reweighted penalized least-squares (airPLS) method is used to reduce the background noise. Secondly, the continuity between spectra is enhanced by 2D Gaussian low-pass filtering. Finally, an adaptive peak-retrieval algorithm is employed to extract the Doppler shift, facilitating the synthesis of a spatial atmospheric 3D wind field through the vector synthesis method. When comparing data from different heights of the meteorological gradient tower, both the horizontal wind-speed correlation and the horizontal wind-direction correlation exceed 0.90. Experimental results show that the proposed algorithm has better robustness and a longer detection distance than the traditional algorithm. Full article