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Keywords = coherent Doppler wind lidar

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21 pages, 6475 KB  
Article
Comparative Study of Low-Level Wind Fields Characteristics at Two Critical Locations in the Terminal Area of Plateau Mountain Airports During the Dry-Season Using Coherent Doppler Wind Lidars
by Junjie Wu, Zhuoqun Shi, Mingrui Lu, Xiaojing Li, Tinglong Zhang and Wanyin Luo
Remote Sens. 2026, 18(8), 1224; https://doi.org/10.3390/rs18081224 - 18 Apr 2026
Viewed by 416
Abstract
The Qinghai–Tibet Plateau is characterized by highly complex terrain, and civil aviation serves as a primary mode of transportation for regional mobility. A comprehensive understanding of wind field characteristics within the terminal areas of plateau mountain airports, as well as the formation mechanisms [...] Read more.
The Qinghai–Tibet Plateau is characterized by highly complex terrain, and civil aviation serves as a primary mode of transportation for regional mobility. A comprehensive understanding of wind field characteristics within the terminal areas of plateau mountain airports, as well as the formation mechanisms of wind shear during different flight phases, is of considerable importance for flight risk assessment, improvement of transport efficiency, and refined meteorological support services. However, studies focusing on wind field structures within the terminal areas of plateau mountain airports remain limited. In this study, dry-season observations from Coherent Doppler Wind Lidars at two critical locations in the terminal area of Lhasa Airport are analyzed. A comparative analysis is conducted on the vertical structure, diurnal variation, and the characteristics of turbulence and wind shear under different terrain conditions. The results show that above the valley height, both sites are dominated by stable westerly winds. Below the valley height, the wind field is strongly influenced by terrain complexity. At the Lhasa Airport site (LS), the valley is regular in shape and has a stable orientation. The prevailing wind direction is aligned with the valley, and easterly winds dominate the entire valley, especially in the middle and lower layers. In contrast, the Qushui site (QS) is located at the confluence of two valleys, where the terrain is more open and complex. The prevailing wind shifts clockwise with height, from northeasterly in the lower layers to easterly aloft. The wind direction is less concentrated than at LS. In terms of diurnal variation, a stable easterly layer forms within the valley at LS in the morning. A transition layer of about 200–300 m exists between this layer and the westerlies aloft. Within the transition layer, wind speed is relatively weak and wind direction stability is low. At QS, morning winds are weaker and more variable within the valley. Wind direction stability increases with height. In the afternoon, both sites are influenced by the downward transport of westerly momentum. However, the effect is more pronounced at QS, where low-level wind speed is higher and wind direction is more stable. Turbulence at both sites peaks between 14:00 and 17:00 and is mainly driven by thermally induced updrafts. Turbulence intensity at QS is stronger, with a vertical extent exceeding 1500 m, indicating a stronger response to thermal forcing. Wind shear at both sites mainly occurs between 12:00 and 18:00, with peak frequency from 13:00 to 17:00. This period is consistent with peak turbulence activity. Wind shear at LS occurs more frequently and lasts longer. At QS, momentum transport from above 1500 m enhances wind shear occurrence at 800–1000 m. The causes of wind shear differ under different prevailing wind conditions. Under prevailing westerlies, wind shear is mainly caused by rapid changes in wind direction with height. Under prevailing easterlies, it is primarily associated with an enhanced vertical gradient of wind speed. These results reveal the significant influence of complex terrain on low-level wind structures and causes of wind shear. The findings provide a scientific basis for operational decision-making at plateau mountain airports. Full article
(This article belongs to the Special Issue New Insights from Wind Remote Sensing)
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14 pages, 2575 KB  
Article
Typical Wind Shear Simulation and Detection Analysis Based on Coherent Doppler Wind Lidar
by Yuanyuan Wei, Jinlong Yuan, Chaoyong Chen, Tengfei Wu and Zikang Tong
Sensors 2026, 26(5), 1643; https://doi.org/10.3390/s26051643 - 5 Mar 2026
Viewed by 460
Abstract
To enhance the accuracy of wind shear identification by coherent Doppler wind lidar (CDWL), it is necessary to clarify the variation characteristics of CDWL detection results under typical airflow disturbance conditions. This study first numerically simulated typical wind shear fields and generated the [...] Read more.
To enhance the accuracy of wind shear identification by coherent Doppler wind lidar (CDWL), it is necessary to clarify the variation characteristics of CDWL detection results under typical airflow disturbance conditions. This study first numerically simulated typical wind shear fields and generated the Plane Position Indication (PPI) results of CDWL through coordinate projection. Then, it compared the performance of the double-slope algorithm and the least squares algorithm on wind shear identification from the PPI data. The results showed that for wind fields with significant peak characteristics, the double-slope algorithm can more sensitively identify wind shear near the peak, compared with the least square algorithm. In contrast, for wind fields with stable, continuous and linear gradient characteristics, the least squares algorithm can better suppress noise and fit the wind speed gradient changes. Finally, a self-developed long-range CDWL was used to conduct wind shear detection experiments at a plateau airport. After the CDWL beam position was calibrated, its data were compared with those from the anemometer. The “least square + double-slope” scheme was adopted to analyze the typical wind shear case, and the effectiveness and reliability of the identification scheme were verified in combination with an aircraft crew report. Full article
(This article belongs to the Special Issue Remote Sensing in Atmospheric Measurements)
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10 pages, 10494 KB  
Communication
Detection and Analysis of Airport Tailwind Events Triggered by Frontal Activity
by Yue Liu, Yixiang Chen, Jinlong Yuan, Zhekai Li, Fangzhi Wei, Tianwen Wei, Jiadong Hu and Haiyun Xia
Remote Sens. 2025, 17(18), 3127; https://doi.org/10.3390/rs17183127 - 9 Sep 2025
Viewed by 1300
Abstract
Excessive tailwind, threatening the safety of aircraft takeoff and landing, is one of the prominent research topics in the field of aviation meteorology. This paper analyzes the causes of tailwinds at Beijing Daxing International Airport (BDIA), based on coherent Doppler wind lidar (CDWL) [...] Read more.
Excessive tailwind, threatening the safety of aircraft takeoff and landing, is one of the prominent research topics in the field of aviation meteorology. This paper analyzes the causes of tailwinds at Beijing Daxing International Airport (BDIA), based on coherent Doppler wind lidar (CDWL) and ERA5 reanalysis data. CDWL with high spatiotemporal resolution is utilized to detect variations in the low-level wind field in the vicinity of airport areas. ERA5 reanalysis data are employed to investigate the distribution characteristics of meteorological elements such as wind fields, pressure, and temperature in the Beijing surrounding regions. The study of two typical tailwind events reveals that frontal activity, through the combined effects of pressure gradient adjustment and topographic constraints from the Taihang Mountains, drives the development of low-level southerly jets. It serves as the key mechanism triggering excessive tailwind. By integrating CDWL and ERA5 data for local and regional analysis, this study contributes to enhancing understanding of tailwind causal mechanisms and provides critical support for aviation meteorological disaster early warning. Full article
(This article belongs to the Special Issue Remote Sensing for High Impact Weather and Extremes (2nd Edition))
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22 pages, 23385 KB  
Article
Structure, Mechanisms, and Impacts of Nocturnal Downslope Wind Events in the Taklimakan Desert
by Mohamed Elshora, Lian Su, Tianwen Wei and Haiyun Xia
Remote Sens. 2025, 17(17), 2984; https://doi.org/10.3390/rs17172984 - 27 Aug 2025
Viewed by 1709
Abstract
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 [...] Read more.
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
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16 pages, 24903 KB  
Technical Note
A Shipborne Doppler Lidar Investigation of the Winter Marine Atmospheric Boundary Layer over Southeastern China’s Coastal Waters
by Xiaoquan Song, Wenchao Lian, Fuyou Wang, Ping Jiang and Jie Wang
Remote Sens. 2025, 17(13), 2161; https://doi.org/10.3390/rs17132161 - 24 Jun 2025
Cited by 1 | Viewed by 1192
Abstract
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 [...] Read more.
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
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23 pages, 12403 KB  
Article
A Comprehensive Ensemble Model for Marine Atmospheric Boundary-Layer Prediction in Meteorologically Sparse and Complex Regions: A Case Study in the South China Sea
by Yehui Chen, Tao Luo, Gang Sun, Wenyue Zhu, Qing Liu, Ying Liu, Xiaomei Jin and Ningquan Weng
Remote Sens. 2025, 17(12), 2046; https://doi.org/10.3390/rs17122046 - 13 Jun 2025
Cited by 4 | Viewed by 1911
Abstract
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, [...] Read more.
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 (R2) 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
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21 pages, 6949 KB  
Article
Estimation of Atmospheric Boundary Layer Turbulence Parameters over the South China Sea Based on Multi-Source Data
by Ying Liu, Tao Luo, Kaixuan Yang, Hanjiu Zhang, Liming Zhu, Shiyong Shao, Shengcheng Cui, Xuebing Li and Ningquan Weng
Remote Sens. 2025, 17(11), 1929; https://doi.org/10.3390/rs17111929 - 2 Jun 2025
Cited by 3 | Viewed by 2893
Abstract
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) [...] Read more.
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 (Cn2) 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
(This article belongs to the Section Environmental Remote Sensing)
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23 pages, 12632 KB  
Article
An Enhanced Three-Dimensional Wind Retrieval Method Based on Genetic Algorithm-Particle Swarm Optimization for Coherent Doppler Wind Lidar
by Xu Zhang, Xianqing Zang, Yuxuan Sang, Xinwei Lian and Chunqing Gao
Remote Sens. 2025, 17(9), 1616; https://doi.org/10.3390/rs17091616 - 2 May 2025
Cited by 3 | Viewed by 1535
Abstract
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. [...] Read more.
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
(This article belongs to the Section Atmospheric Remote Sensing)
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16 pages, 9675 KB  
Article
Research on Spectral Leakage Suppression Method of Coherent Wind Lidar Based on Hanning Self-Convolutional Window
by Chen Su, Shoufeng Tong, Peng Lin, Naiyuan Liang, Zejie He and Xiaonan Yu
Appl. Sci. 2025, 15(9), 4709; https://doi.org/10.3390/app15094709 - 24 Apr 2025
Viewed by 1308
Abstract
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 [...] Read more.
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
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15 pages, 29108 KB  
Article
Simulation and Analysis of Coherent Wind Lidar Based on Range Resolution
by Jiaxin Chen, Hong Li, Weiwei Zhan, Yunkai Dong, Liheng Wu and Wenbo Wang
Sensors 2025, 25(8), 2344; https://doi.org/10.3390/s25082344 - 8 Apr 2025
Cited by 2 | Viewed by 2238
Abstract
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 [...] Read more.
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
(This article belongs to the Section Radar Sensors)
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21 pages, 9832 KB  
Article
A Novel Joint Denoising Strategy for Coherent Doppler Wind Lidar Signals
by Yuefeng Zhao, Wenkai Song, Nannan Hu, Xue Zhou, Jiankang Luo, Jinrun Huang and Qianqian Tao
Remote Sens. 2025, 17(7), 1291; https://doi.org/10.3390/rs17071291 - 4 Apr 2025
Cited by 3 | Viewed by 1573
Abstract
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 [...] Read more.
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 SNRout 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
(This article belongs to the Section Environmental Remote Sensing)
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18 pages, 4883 KB  
Article
FPGA Programming Challenges When Estimating Power Spectral Density and Autocorrelation in Coherent Doppler Lidar Systems for Wind Sensing
by Sameh Abdelazim, David Santoro and Fred Moshary
Sensors 2025, 25(3), 973; https://doi.org/10.3390/s25030973 - 6 Feb 2025
Cited by 1 | Viewed by 2174
Abstract
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 [...] Read more.
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 article belongs to the Special Issue Integrated Sensor Systems for Environmental Applications)
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13 pages, 10498 KB  
Article
Nocturnal Ozone Enhancement Induced by Sea-Land Breezes During Summertime in Northern Coastal City Qingdao, China
by He Meng, Jiahong Liu, Lu Wang, Laiyuan Shi and Jianjun Li
Atmosphere 2024, 15(11), 1350; https://doi.org/10.3390/atmos15111350 - 10 Nov 2024
Cited by 3 | Viewed by 2346
Abstract
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 [...] Read more.
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 PM2.5 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 PM2.5. Full article
(This article belongs to the Special Issue New Insights in Air Quality Assessment: Forecasting and Monitoring)
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14 pages, 3542 KB  
Technical Note
Study on Daytime Atmospheric Mixing Layer Height Based on 2-Year Coherent Doppler Wind Lidar Observations at the Southern Edge of the Taklimakan Desert
by Lian Su, Haiyun Xia, Jinlong Yuan, Yue Wang, Amina Maituerdi and Qing He
Remote Sens. 2024, 16(16), 3005; https://doi.org/10.3390/rs16163005 - 16 Aug 2024
Cited by 6 | Viewed by 2078
Abstract
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, [...] Read more.
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
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19 pages, 6258 KB  
Article
Locating and Grading of Lidar-Observed Aircraft Wake Vortex Based on Convolutional Neural Networks
by Xinyu Zhang, Hongwei Zhang, Qichao Wang, Xiaoying Liu, Shouxin Liu, Rongchuan Zhang, Rongzhong Li and Songhua Wu
Remote Sens. 2024, 16(8), 1463; https://doi.org/10.3390/rs16081463 - 20 Apr 2024
Cited by 5 | Viewed by 3172
Abstract
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 [...] Read more.
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
(This article belongs to the Special Issue Computer Vision-Based Methods and Tools in Remote Sensing)
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