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Advances in Satellite and Ground-Based Polarimetric Remote Sensing and Applications in Atmosphere, Ocean and Land Surface Detections

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Atmospheric Remote Sensing".

Deadline for manuscript submissions: closed (31 October 2023) | Viewed by 17268

Special Issue Editors

Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
Interests: polarization remote sensing; vector radiative transfer model; light scattering by aerosol particles; cloud detection
State Environmental Protection Key Laboratory of Satellite Remote Sensing, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China
Interests: aerosol remote sensing; polarimetric atmospheric detection
Special Issues, Collections and Topics in MDPI journals
Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China
Interests: polarization remote sensing technology; space borne polarimetric payloads; polarization calibration

Special Issue Information

Dear Colleagues,

Polarization is a fundamental property of electromagnetic waves. The changes of skylight polarization due to the scattering interactions of unpolarized solar radiation with the constituents of atmosphere, oceans, and land surfaces (e.g., gases, aerosol particles, water droplets, ice crystals, oceanic suspensions, water, and soil and vegetation surfaces) contain valuable information of the Earth system. Since the discovery of skylight polarization by Arago in 1809, measurements of the polarization of skylight by various satellite and ground-based polarimetric instruments have been emphasized, as these can be used for studying the properties of the planet Earth in a unique way.

The aim of this Special Issue is to disseminate recent developments in satellite and ground-based polarimetric remote sensing. Papers with new ideas and results of diverse aspects of polarimetric remote sensing, including theory, instrumentation, calibration and validation, algorithms, and comprehensive applications in atmosphere, ocean, and land surface detections are all welcome. Potential topics of this Special Issue” Advances in Satellite and Ground-based Polarimetric Remote Sensing and Applications in Atmosphere, Ocean and Land Surface Detections” include, but are not limited to:

  • Development of theory of polarimetric remote sensing;
  • Vector radiative transfer model;
  • Improvement of satellite and ground-based polarimetric instrumentation;
  • Polarimetric sensor calibration and data validation;
  • Polarimetric data and image processing;
  • Advanced polarimetric retrieval algorithms;
  • Polarimetric remote sensing of atmospheric aerosols and clouds;
  • Polarimetric remote sensing of ocean and land surface;
  • Understanding of atmosphere-ocean-land system based on comprehensive observations.

Dr. Li Li
Prof. Dr. Zhengqiang Li
Prof. Jin Hong
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • light scattering theory and polarized radiative transfer
  • satellite-based polarimetric remote sensing
  • ground-based polarimetric remote sensing
  • calibration and data validation
  • polarimetric data processing
  • advanced retrieval algorithms
  • applications of polarimetric remote sensing

Published Papers (10 papers)

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Research

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21 pages, 14403 KiB  
Article
Simulation of Parallel Polarization Radiance for Retrieving Chlorophyll a Concentrations in Open Oceans Based on Spaceborne Polarization Crossfire Strategy
by Yichen Wei, Xiaobing Sun, Xiao Liu, Honglian Huang, Rufang Ti, Jin Hong, Haixiao Yu, Yuxuan Wang, Yiqi Li and Yuyao Wang
Remote Sens. 2023, 15(23), 5490; https://doi.org/10.3390/rs15235490 - 24 Nov 2023
Viewed by 635
Abstract
The polarization crossfire (PCF) suite carried onboard the Chinese GaoFen-5B satellite is composed of a Particulate Observing Scanning Polarimeter (POSP) and a Directional Polarimetric Camera (DPC), which can provide multi-angle, multi-spectral, and polarization data. In this paper, the influence of polarization and the [...] Read more.
The polarization crossfire (PCF) suite carried onboard the Chinese GaoFen-5B satellite is composed of a Particulate Observing Scanning Polarimeter (POSP) and a Directional Polarimetric Camera (DPC), which can provide multi-angle, multi-spectral, and polarization data. In this paper, the influence of polarization and the directionality of reflectance in open oceans on the inversion of chlorophyll a (Chla) concentrations are investigated, from 410 nm to 670 nm. First, we exploit a vector radiative transfer model to simulate the absolute and relative magnitudes of the water-leaving radiance signal (I) and the parallel polarization radiance (PPR) to the top-of-atmosphere (TOA) radiation field. The simulation results show that the PPR can enhance the relative contribution of the water-leaving signal, especially in sunglint observation geometry. The water-leaving signal for PPR exhibits significant directional and spectral variations relative to the observation geometries, and the maximum value of the water-leaving signal for PPR occurs in the backscattering direction. In addition, the sensitivity of the PPR to the Chla concentration is sufficient. The synthetic datasets are utilized to develop retrieval algorithms for the Chla concentrations based on the back-propagation neural network (BPNN). The inversion results show that the PCF strategy improves the accuracy of Chla retrieval, with an RMSE of 0.014 and an RRMSE of 6.57%. Thus, it is an effective method for retrieving the Chla concentration in open oceans, by utilizing both the directionality and polarization of the reflectance. Full article
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36 pages, 9387 KiB  
Article
Solid Angle Geometry-Based Modeling of Volume Scattering with Application in the Adaptive Decomposition of GF-3 Data of Sea Ice in Antarctica
by Dong Li, He Lu and Yunhua Zhang
Remote Sens. 2023, 15(12), 3208; https://doi.org/10.3390/rs15123208 - 20 Jun 2023
Viewed by 2000
Abstract
Over the last two decades, spaceborne polarimetric synthetic aperture radar (PolSAR) has been widely used to penetrate sea ice surfaces to achieve fully polarimetric high-resolution imaging at all times of day and in a range of weather conditions. Model-based polarimetric decomposition is a [...] Read more.
Over the last two decades, spaceborne polarimetric synthetic aperture radar (PolSAR) has been widely used to penetrate sea ice surfaces to achieve fully polarimetric high-resolution imaging at all times of day and in a range of weather conditions. Model-based polarimetric decomposition is a powerful tool used to extract useful physical and geometric information about sea ice from the matrix datasets acquired by PolSAR. The volume scattering of sea ice is usually modeled as the incoherent average of scatterings of a large volume of oriented ellipsoid particles that are uniformly distributed in 3D space. This uniform spatial distribution is often approximated as a uniform orientation distribution (UOD), i.e., the particles are uniformly oriented in all directions. This is achieved in the existing literature by ensuring the canting angle φ and tilt angle τ of particles uniformly distributed in their respective ranges and introducing a factor cosτ in the ensemble average. However, we find this implementation of UOD is not always effective, while a real UOD can be realized by distributing the solid angles of particles uniformly in 3D space. By deriving the total solid angle of the canting-tilt cell spanned by particles and combining the differential relationship between solid angle and Euler angles φ and τ, a complete expression of the joint probability density function pφ,τ that can always ensure the uniform orientation of particles of sea ice is realized. By ensemble integrating the coherency matrix of φ,τ-oriented particle with pφ,τ, a generalized modeling of the volume coherency matrix of 3D uniformly oriented spheroid particles is obtained, which covers factors such as radar observation geometry, particle shape, canting geometry, tilt geometry and transmission effect in a multiplicative way. The existing volume scattering models of sea ice constitute special cases. The performance of the model in the characterization of the volume behaviors was investigated via simulations on a volume of oblate and prolate particles with the differential reflectivity ZDR, polarimetric entropy H and scattering α angle as descriptors. Based on the model, several interesting orientation geometries were also studied, including the aligned orientation, complement tilt geometry and reflection symmetry, among which the complement tilt geometry is specifically highlighted. It involves three volume models that correspond to the horizontal tilt, vertical tilt and random tilt of particles within sea ice, respectively. To match the models to PolSAR data for adaptive decomposition, two selection strategies are provided. One is based on ZDR, and the other is based on the maximum power fitting. The scattering power that reduces the rank of coherency matrix by exactly one without violating the physical realizability condition is obtained to make full use of the polarimetric scattering information. Both the models and decomposition were finally validated on the Gaofen-3 PolSAR data of a young ice area in Prydz Bay, Antarctica. The adaptive decomposition result demonstrates not only the dominant vertical tilt preference of brine inclusions within sea ice, but also the subordinate random tilt preference and non-negligible horizontal tilt preference, which are consistent with the geometric selection mechanism that the c-axes of polycrystallines within sea ice would gradually align with depth. The experiment also indicates that, compared to the strategy based on ZDR, the maximum power fitting is preferable because it is entirely driven by the model and data and is independent of any empirical thresholds. Such soft thresholding enables this strategy to adaptively estimate the negative ZDR offset introduced by the transmission effect, which provides a novel inversion of the refractive index of sea ice based on polarimetric model-based decomposition. Full article
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18 pages, 8822 KiB  
Article
Data Comparison and Cross-Calibration between Level 1 Products of DPC and POSP Onboard the Chinese GaoFen-5(02) Satellite
by Xuefeng Lei, Zhenhai Liu, Fei Tao, Hao Dong, Weizhen Hou, Guangfeng Xiang, Lili Qie, Binghuan Meng, Congfei Li, Feinan Chen, Yanqing Xie, Miaomiao Zhang, Lanlan Fan, Liangxiao Cheng and Jin Hong
Remote Sens. 2023, 15(7), 1933; https://doi.org/10.3390/rs15071933 - 04 Apr 2023
Cited by 1 | Viewed by 1524
Abstract
The Polarization CrossFire (PCF) suite onboard the Chinese GaoFen-5(02) satellite has been sophisticatedly composed by the Particulate Observing Scanning Polarimeter (POSP) and the Directional Polarimetric Camera (DPC). Among them, DPC is a multi-angle sequential measurement polarization imager, while POSP is a cross-track scanning [...] Read more.
The Polarization CrossFire (PCF) suite onboard the Chinese GaoFen-5(02) satellite has been sophisticatedly composed by the Particulate Observing Scanning Polarimeter (POSP) and the Directional Polarimetric Camera (DPC). Among them, DPC is a multi-angle sequential measurement polarization imager, while POSP is a cross-track scanning simultaneous polarimeter with corresponding radiometric and polarimetric calibrators, which can theoretically be used for cross comparison and calibration with DPC. After the data preprocessing of these two sensors, we first select local homogeneous cluster scenes by calculating the local variance-to-mean ratio in DPC’s Level 1 product projection grids to reduce the influence of scale differences and geometry misalignment between DPC and POSP. Then, taking the observation results after POSP data quality assurance as the abscissa and taking the DPC observation results under the same wavelength band and geometric conditions as the same ordinate, a two-dimensional radiation/polarization feature space is established. Results show that the normalized top of the atmosphere (TOA) radiances of DPC and POSP processed data at the nadir are linearly correlated. The normalized TOA radiance root mean square errors (RMSEs) look reasonable in all common bands. The DPC and POSP normalized radiance ratios in different viewing zenith angle ranges at different times reveal the temporal drift of the DPC relative radiation response. The RMSEs, mean absolute errors (MAEs), relative errors (REs), and scatter percentage of DPC degree of linear polarization (DoLP) falling within the expected error (EE = ±0.02) of POSP measured DoLP are better than 0.012, 0.009, 0.066, and 91%, respectively. Full article
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19 pages, 4504 KiB  
Article
Application of a Fusion Model Based on Machine Learning in Visibility Prediction
by Maochan Zhen, Mingjian Yi, Tao Luo, Feifei Wang, Kaixuan Yang, Xuebin Ma, Shengcheng Cui and Xuebin Li
Remote Sens. 2023, 15(5), 1450; https://doi.org/10.3390/rs15051450 - 04 Mar 2023
Cited by 2 | Viewed by 2902
Abstract
To improve the accuracy of atmospheric visibility (V) prediction based on machine learning in different pollution scenarios, a new atmospheric visibility prediction method based on the stacking fusion model (VSFM) is established in this paper. The new method uses the stacking strategy to [...] Read more.
To improve the accuracy of atmospheric visibility (V) prediction based on machine learning in different pollution scenarios, a new atmospheric visibility prediction method based on the stacking fusion model (VSFM) is established in this paper. The new method uses the stacking strategy to fuse two base learners—eXtreme gradient boosting (XGBoost) and light gradient boosting machine (LightGBM)—to optimize prediction accuracy. Furthermore, seasonal feature importance evaluations and feature selection were utilized to optimize prediction accuracy in different seasons with different pollution sources. The new VSFM was applied to 1-year environmental and meteorological data measured in Qingdao, China. Compared to other traditional non-stacking models, the new VSFM improved precision during different seasons, especially in extremely low-visibility scenarios (V< 2 km). The TS score of the VSFM was significantly better than that of other models. For extremely low-visibility scenarios, the VSFM had a threat score (TS) of 0.5, while the best performance of other models was less than 0.27. The new method is promising for atmospheric visibility prediction under complex urban pollution conditions. The research results can also improve our understanding of the factors that influence urban visibility. Full article
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15 pages, 3952 KiB  
Article
Linearized Single-Scattering Property Database for Hexagonal Prism Ice Particles
by Chenxu Gao, Dongbin Liang, Bingqiang Sun, Jian Liu and Zhaoyuan Liu
Remote Sens. 2022, 14(23), 6138; https://doi.org/10.3390/rs14236138 - 03 Dec 2022
Cited by 1 | Viewed by 1049
Abstract
Accurate description of the single scattering properties of atmospheric particles can be an essential factor influencing the remote sensing of atmospheric microphysics. In this paper, a database for the linearized single scattering properties of ice particles was developed in the visible to infrared [...] Read more.
Accurate description of the single scattering properties of atmospheric particles can be an essential factor influencing the remote sensing of atmospheric microphysics. In this paper, a database for the linearized single scattering properties of ice particles was developed in the visible to infrared spectral region of 0.4–15 μm and for size parameters ranging from 0.5 to 500. The linearized invariant imbedding T-matrix method and linearized physical-geometric optics method were jointly applied. A full set of integral scattering properties including extinction efficiency, single scattering albedo, asymmetry factors, and differential scattering properties, including six phase matrix elements, were the basic scattering parameters in the database. Furthermore, the Jacobians of these regular scattering properties with respect to refractive index (real and imaginary parts) and effective radius were also included and used for sensitivity determinations. The spectral and size-dependent variations and changing rates of the derivative characteristics with actual application values, such as backscattering depolarization ratios, were also discussed. Full article
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13 pages, 3651 KiB  
Article
Shortwave Infrared Multi-Angle Polarization Imager (MAPI) Onboard Fengyun-3 Precipitation Satellite for Enhanced Cloud Characterization
by Haofei Wang, Peng Zhang, Dekui Yin, Zhengqiang Li, Huazhe Shang, Hanlie Xu, Jian Shang, Songyan Gu and Xiuqing Hu
Remote Sens. 2022, 14(19), 4855; https://doi.org/10.3390/rs14194855 - 29 Sep 2022
Cited by 6 | Viewed by 1688
Abstract
Accurate measurement of the radiative properties of clouds and aerosols is of great significance to global climate change and numerical weather prediction. The multi-angle polarization imager (MAPI) onboard the Fengyun-3 precipitation satellite, planned to be launched in 2023, will provide the multi-angle, multi-shortwave [...] Read more.
Accurate measurement of the radiative properties of clouds and aerosols is of great significance to global climate change and numerical weather prediction. The multi-angle polarization imager (MAPI) onboard the Fengyun-3 precipitation satellite, planned to be launched in 2023, will provide the multi-angle, multi-shortwave infrared (SWIR) channels and multi-polarization satellite observation of clouds and aerosols. MAPI operates in a non-sun-synchronized inclined orbit and provides images with a spatial resolution of 3 km (sub-satellite) and a swath of 700 km. The observation channels of the MAPI include 1030 nm, 1370 nm, and 1640 nm polarization channels and corresponding non-polarization channels, which provide observation information from 14 angles. In-flight radiometric and polarimetric calibration strategies are introduced, aiming to achieve radiometric accuracy of 5% and polarimetric accuracy of 2%. Simulation experiments show that the MAPI has some unique advantages of characterizing clouds and aerosols. For cloud observation, the polarization phase functions of the 1030 nm and 1640 nm around the scattering angle of a cloudbow show strong sensitivity to cloud droplet radius and effective variance. In addition, the polarized observation of the 1030 nm and 1640 nm has a higher content of information for aerosol than VIS-NIR. Additionally, the unique observation geometry of non-sun-synchronous orbits can provide more radiometric and polarization information with expanded scattering angles. Thus, the multi-angle polarization measurement of the new SWIR channel onboard Fengyun-3 can optimize cloud phase state identification and cloud microphysical parameter inversion, as well as the retrieval of aerosols. The results obtained from the simulations will provide support for the design of the next generation of polarized imagers of China. Full article
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14 pages, 7432 KiB  
Communication
Analysis of Optical Turbulence over the South China Sea Using Balloon-Borne Microthermal Data and ERA5 Data
by Manman Xu, Shiyong Shao, Ningquan Weng and Qing Liu
Remote Sens. 2022, 14(17), 4398; https://doi.org/10.3390/rs14174398 - 04 Sep 2022
Cited by 2 | Viewed by 1373
Abstract
It is very useful for adaptive optics (AO) systems to have appropriate knowledge of optical turbulence. However, due to the limitations of space and time, it is difficult to obtain turbulence parameters, especially in the far sea area. In this paper, the characteristics [...] Read more.
It is very useful for adaptive optics (AO) systems to have appropriate knowledge of optical turbulence. However, due to the limitations of space and time, it is difficult to obtain turbulence parameters, especially in the far sea area. In this paper, the characteristics of optical turbulence over the South China Sea are obtained by analyzing the meteorological data obtained from the field experiment of ocean optical parameters and the fifth set of reanalysis data of the European Centre for Medium-Range Weather Forecasts (ECMWF) for 10 years (2011–2020). Firstly, a new statistical model is proposed based on the measured data and the Hufnagel-Valley 5/7, which can well reconstruct the atmospheric turbulence characteristics of the South China Sea. Secondly, according to the comparison between the temperature and wind speed data in ERA5 data and microthermal measurement, the ERA5 data have good reliability, with the temperature deviation basically less than 1.5 K and the wind speed deviation basically less than 2 m∙s−1. Thirdly, the vertical distributions and seasonal behavior of the turbulence strength at the determined location are analyzed, which shows that the turbulence strength in the upper atmosphere is strongest in summer, followed by autumn and winter, and weakest in spring. Then, the distribution profile of the Richardson number provides us with the relative probability of the existence of optical turbulence. During summer and September, the instability of the atmosphere is significantly larger than other months and the extremely low intensity in April indicates the most stable condition in all months. Finally, the analysis results of turbulence parameter profiles for many years show that there is good consistency between different parameters. Full article
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28 pages, 11739 KiB  
Article
Laboratory Calibration of an Ultraviolet–Visible Imaging Spectropolarimeter
by Jingjing Shi, Mengfan Li, Yadong Hu, Xiangjing Wang, Hua Xu, Gaojun Chi and Jin Hong
Remote Sens. 2022, 14(16), 3898; https://doi.org/10.3390/rs14163898 - 11 Aug 2022
Cited by 4 | Viewed by 1456
Abstract
The ultraviolet–visible imaging spectropolarimeter (UVISP), developed by the Anhui Institute of Optics and Fine Mechanics (AIOFM), Chinese Academy of Science (CAS), is a dual-beam snapshot instrument for measuring the spectral, radiometric, and linear polarization information of absorbing aerosol in a wavelength range from [...] Read more.
The ultraviolet–visible imaging spectropolarimeter (UVISP), developed by the Anhui Institute of Optics and Fine Mechanics (AIOFM), Chinese Academy of Science (CAS), is a dual-beam snapshot instrument for measuring the spectral, radiometric, and linear polarization information of absorbing aerosol in a wavelength range from 340 to 520 nm. In this paper, we propose a complete set of calibration methods for UVISP to ensure the accuracy of the measured radiation polarization data, thus guaranteeing the reliability of inversion results. In geometric calibration, we complete the assignment of the field of view (FOV) angle to each pixel of the detector using a high precision turntable and parallel light source. In addition, the geometric calibration accuracy of the S beam and P beam is also analyzed. The results show that the residuals of all row pixels are less than 0.12°. Based on geometric calibration, a spectral calibration is conducted at each spectrum of the S beam and P beam for the given FOV, and the relation between the wavelength and pixel is obtained by a linear fitting procedure. For radiometric calibration, the uniformity of spectral responsivity is corrected, and the function between spectral radiance and output digital data is established. To improve the accuracy of the polarimetric measurement, a polarimetric calibration is proposed, and validated experimental results show that the root mean square (RMS) errors for the demodulated value are all within 0.011 for the input linear polarized light with different angles of linear polarization (AoLPs). Finally, field measurements are conducted, and the absolute deviations are all within 0.01 when the UVISP and CE-318 sun–sky polarimetric radiometer (CE318N) simultaneously measure the degree of linear polarization (DoLP) of the sky at different zenith angles. These experimental results demonstrate the efficiency and accuracy of the proposed calibration methods. Full article
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Review

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26 pages, 3959 KiB  
Review
Polarimetry for Bionic Geolocation and Navigation Applications: A Review
by Qianhui Li, Liquan Dong, Yao Hu, Qun Hao, Wenli Wang, Jie Cao and Yang Cheng
Remote Sens. 2023, 15(14), 3518; https://doi.org/10.3390/rs15143518 - 12 Jul 2023
Cited by 2 | Viewed by 1327
Abstract
Polarimetry, which seeks to measure the vectorial information of light modulated by objects, has facilitated bionic geolocation and navigation applications. It is a novel and promising field that provides humans with a remote sensing tool to exploit polarized skylight in a similar way [...] Read more.
Polarimetry, which seeks to measure the vectorial information of light modulated by objects, has facilitated bionic geolocation and navigation applications. It is a novel and promising field that provides humans with a remote sensing tool to exploit polarized skylight in a similar way to polarization-sensitive animals, and yet few in-depth reviews of the field exist. Beginning with biological inspirations, this review mainly focuses on the characterization, measurement, and analysis of vectorial information in polarimetry for bionic geolocation and navigation applications, with an emphasis on Stokes–Mueller formalism. Several recent breakthroughs and development trends are summarized in this paper, and potential prospects in conjunction with some cutting-edge techniques are also presented. The goal of this review is to offer a comprehensive overview of the exploitation of vectorial information for geolocation and navigation applications as well as to stimulate new explorations and breakthroughs in the field. Full article
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Other

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12 pages, 3958 KiB  
Technical Note
A Rotary Platform Mounted Doppler Lidar for Wind Measurements in Upper Troposphere and Stratosphere
by Ming Zhao, Chenbo Xie, Bangxin Wang, Kunming Xing, Jianfeng Chen, Zhiyuan Fang, Lu Li and Liangliang Cheng
Remote Sens. 2022, 14(21), 5556; https://doi.org/10.3390/rs14215556 - 03 Nov 2022
Cited by 3 | Viewed by 1439
Abstract
A Doppler lidar mounted on a rotary platform has been developed for measuring wind fields in the upper troposphere and stratosphere. The rotating platform was used to support a large system for the detection of wind velocities of sight (VOS) in four directions. [...] Read more.
A Doppler lidar mounted on a rotary platform has been developed for measuring wind fields in the upper troposphere and stratosphere. The rotating platform was used to support a large system for the detection of wind velocities of sight (VOS) in four directions. The principle, structure, and parameters of the lidar system are introduced. The Fabry-Perot interferometer (FPI), the core component of the wind measurement system, was designed after comprehensively considering the measurement uncertainty and the influence of Mie scattering. Its dual-edge channel bandwidth is 1.05 GHz with 3.48 GHz spacing. In operation, the FPI channels are locked to the laser frequency with a stability of 14.8 MHz. Compared with the local radiosonde, it was found that the deviation in wind speed below 28 km was generally less than 10 m/s, and the deviation in wind direction below 19 km was less than 10 degrees. The 42-day profile comparison between lidar in Hefei and radiosondes in Anqing and Fuyang was analyzed. The statistical results show that the wind speed and wind direction deviations between lidar and radiosondes below 20 km were approximately 10 m/s and 20 degrees, respectively, which are comparable to the regional differences in the wind field. However, as altitudes exceed 20 km, the deviations increased rapidly with height. The experiments indicate that the Doppler lidar could measure wind fields from 7 km to 30 km, with better detection accuracy below 20 km. Full article
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