S-band Radar Research Articles

A Radar-Based Methodology for Aerosol Plume Identification and Characterisation on the South African Highveld

Biomass burning on the South African Highveld annually injects substantial amounts of aerosols and trace gases into the atmosphere, impacting the global radiative balance, cloud microphysics, and regional air quality. These aerosols are transported as plumes over long distances, posing challenges to existing in situ and satellite-based monitoring techniques because of their limited spatial and temporal resolution, particularly in environments with low-level sources. This study aims to develop and validate a novel radar-based methodology to detect, track, and characterise aerosol plumes, addressing the limitations of existing in situ and satellite monitoring techniques. Using high-resolution volumetric reflectivity data from an S-band radar in Pretoria, South Africa, a traditional storm tracking algorithm is adapted to improve plume identification. Case studies of plume events in June and August 2013 demonstrate the radar’s effectiveness in distinguishing lower vertical profiles and reduced reflectivity of plumes compared with storm echoes. The adapted algorithm successfully tracked the spatial and temporal evolution of the plumes, revealing their short-lived nature. Results indicate that radar-derived geospatial characteristics have the potential to contribute significantly to understanding the impacts of plumes on local air quality. These findings underscore the critical need for high spatio-temporal resolution data to support effective air quality management and inform policy development in regions affected by biomass burning.

Automatic Identification of Three-Body Scatter Spike Based on Jensen–Shannon Divergence and Support Vector Machine

Abstract The three-body scatter spike (TBSS), an echo artifact in radar imagery, manifests as a weak, linear echo extending radially from a core of high reflectivity. Adequately, though not indispensably, indicating the presence of large hail in convective storms, the automatic identification of the TBSS proves advantageous in significantly improving the effectiveness of hailstorm detection. This study introduces an algorithm that synergizes Jensen–Shannon divergence (JSD) and support vector machine (SVM) for rapid TBSS detection in two decades’ worth of single-polarization radar data across China. The algorithm, tested on data from 50 S-band China Next Generation Weather Radar (CINRAD) in central and eastern China, utilized reflectivity factor images for sample extraction. An application in Chenzhou, China, demonstrates the algorithm’s efficacy in improving hailstorm detection resolution. Significance Statement In recent years, China’s hail recordkeeping, primarily based on manual observations at national surface meteorological stations, has suffered from limited spatial and temporal detail. However, the advent of the China Next Generation Weather Radar (CINRAD) network offers a new avenue for hailstorm detection. TBSS, a secondary but significant indicator for large hail in S-band radar, presents an opportunity for enhanced hail warning capabilities. By automating TBSS detection in radar archives spanning two decades, this research significantly enhances the resolution of hailstorm climatology, contributing to more effective hail disaster mitigation and management.

A Localized Quantitative Precipitation Estimation for S-band Polarimetric Radar in Taiwan

Abstract A polarimetric radar quantitative precipitation estimation to estimate rain rate (R) from specific attenuation (A) has been applied in Taiwan's operational Quantitative Precipitation Estimation and Segregation Using Multiple Sensors (QPESUMS) system since 2016. A 3-yrs' (2016-2018) drop size distribution dataset from an operational Parsivel network was used to derive a localized coefficient as well as the α(K) function in the R(A) scheme for S-band radar, where α is a key parameter in the estimation of A and K is the linear fitted slope of differential reflectivity (ZDR) versus reflectivity (Z). The local DSD data was also used to derive localized R(Z) and R(KDP) relationships, and the relationships were evaluated using radar observations in heavy rain cases. A synthetic QPE combining the localized R(A), R(Z), and R(KDP) relationships is compared to its operational counterpart and showed about 8 % reduction in normalized mean error for the Mei-Yu cases. Typhoon cases exhibited similar improvements by the localized QPE relationships, but showed higher uncertainties than in the Mei-Yu cases. The higher uncertainties in the typhoon QPE verification was likely due to the stronger winds in typhoons than in the Mei-Yu events that caused greater mismatches between the radar observations at an altitude and the gauges at the ground. Overall, the results demonstrated advantages of localized radar rainfall relationships derived from the disdrometer data to improve the accuracy of the operational rainfall estimation products.

Accuracy of Polarimetric Radar ZDR Estimates: Implications for the Quantitative Observation of Meteorological and Nonmeteorological Echoes

Abstract This paper considers theoretical and observed uncertainties in the estimates of ZDR and ρHV(0) using data from an operational S-band radar and a mobile X-band radar. Cases of widespread uniform precipitation including bright-band, clear air, and ash echoes from forest fires are all considered in order to obtain a wide range of ρHV(0) values as this along with the radar frequency and spectrum width determines the uncertainties. The theoretical uncertainties in these parameters provide a good estimate of the lower bound of the standard deviations of the observed values where these have been estimated using the adjacent data to the target pixel. The implications for the accuracy of precipitation estimation, particle identification, and estimates of drop-size distributions are discussed. Significance Statement High-quality quantitative precipitation and particle size/classification retrievals using weather radar are strongly dependent on the accuracy of ZDR and ρHV(0). This paper examines the theoretical limits to the measurement accuracy and verifies these limits with radar data at 10- and 3-cm wavelengths.

Quality Control of Doppler Spectra from a Vertically Pointing, S-Band Profiling Radar

Abstract This study describes a novel combination of methods to remove spurious spectral peaks, or “spurs,” from Doppler spectra produced by a vertically pointing, S-band radar. The University of Massachusetts S-band frequency-modulated, continuous-wave radar (UMass FMCW) was deployed to monitor the growth of the CBL over northern Alabama during the VORTEX–Southeast field campaign in 2016. The Doppler spectra contained spurs caused by high-voltage switching power supplies in the traveling wave tube amplifier. In the original data-processing scheme for this radar, a median filtering method was used to eliminate most of the spurs, but the largest ones persisted, which significantly degraded the quality of derived radar moments (e.g., reflectivity, Doppler velocity, and spectrum width) and hindered further analysis of these data (e.g., hydrometeor classification and boundary layer height tracking). Our technique for removing the spurs consists of three steps: (i) a Laplacian filter identifies and masks peaks in the spectra that are characteristic of the spurs in shape and amplitude, (ii) an in-painting method then fills in the masked area based on surrounding data, and (iii) the moments data (e.g., reflectivity, Doppler velocity, and spectrum width) are then recomputed using a coherent power technique. This combination of techniques was more effective than the median filter at removing the largest spurs from the Doppler spectra and preserved more of the underlying Doppler spectral structure of the scatterers. Performance of both the median-filter and the in-painting methods is assessed through statistical analysis of the spectral power differences. Downstream products, such as boundary layer height detection, are more easily derived from the recomputed moments. Significance Statement This manuscript describes a novel combination of image and signal processing techniques used to recover meteorological observations from corrupted Doppler radar spectra. This successful recovery of meteorologically significant information illustrates the importance of retaining Doppler spectra when practical. In seeking solutions to data quality issues, the atmospheric science community should remain cognizant of promising techniques offered by other disciplines. We present this data rescue study as an example to the meteorological community.

Modeling Wind Turbines to Assess Impact of Offshore Wind Farms on Maritime X- and S-band Radars

This article discusses several aspects related to modeling the impact of offshore wind farms on maritime radar systems operating in the X and S bands. The first part of the paper focuses on theoretical models and analyses, taking into account radio shadowing and false radar echoes. Additionally, the issue of spatial modeling of wind turbines, with diffraction phenomena considered, is reviewed with the help of suitable propagation models. By relaying on a software-based implementation of the proposed model, the authors carried out a detailed simulation of the impact of wind turbines on radar systems operating in the X and S bands. The results of these simulations are presented and discussed in the second part of the article.

Radar, Lightning, and Synoptic Observations for a Thunderstorm on 7 January 2012 during the CHUVA-Vale Campaign

Thunderstorms can generate intense electrical activity, hail, and result in substantial economic and human losses. The development of very short-term forecasting tools (nowcasting) is essential to provide information to alert systems in order to mobilize most efficiently the population. However, the development of nowcasting tools depends on a better understanding of the physics and microphysics of clouds and lightning formation and evolution. In this context, the objectives of this study are: (a) to describe the environmental conditions that led to a genesis of a thunderstorm that produce hail on 7 January 2012, in the Metropolitan Area of São Paulo (MASP) during the CHUVA-Vale campaign, and (b) to evaluate the thunderstorm microphysical properties and vertical structure of electrical charge. Data from different sources were used: field campaign data, such as S-band radar, and 2- and 3-dimensional lightning networks, satellite data from the Geostationary Operational Environmental Satellite-13 (GOES-13), the Meteosat Second Generation (MSG), and reanalysis of the European Centre for Medium-Range Weather Forecasts Reanalysis v5 (ERA5). The thunderstorm developed in a region of low-pressure due to the presence of a near-surface inverted trough and moisture convergence, which favored convection. Convective Available Potential Energy (CAPE) of 1053.6 J kg−1 at the start of the thunderstorm indicated that strong convective energy was present. Microphysical variables such as Vertically Integrated Liquid water content (VIL) and Vertically Integrated Ice (VII) showed peaks of 140 and 130 kg m−2, respectively, before the hail reached the surface, followed by a decrease, indicating content removal from within the clouds to the ground surface. The thunderstorm charge structure evolved from a dipolar structure (with a negative center between 4 and 6 km and a positive center between 8 and 10 km) to a tripolar structure (negative center between 6 and 7.5 km) in the most intense phase. The first lightning peak (100 flashes in 5 min−1) before the hail showed that there had been a lightning jump. The maximum lightning occurred around 18:17 UTC, with approximately 350 flashes 5 min−1 with values higher than 4000 sources 500 m−1 in 5 min−1. Likewise, the vertical cross-sections indicated that the lightning occurred ahead of the thunderstorm’s displacement (maximum reflectivity), which could be useful in predicting these events.

THE OBSERVATION NETWORK PERFECTION FOR FLIGHT SAFETY IN THE REPUBLIC OF KAZAKHSTAN

One of the ways of flight safety improvement and quality air traffic services is perfection the material and technical equipment of the country's observation network. This makes it possible to improve the analysis of the state of the “surface background– atmosphere” system, which is necessary, in particular, to identify hazardous and especially dangerous weather phenomena and to predict them. One of the directions for improving the means of monitoring atmospheric processes is the use of remote sensing methods of the atmosphere, which include meteorological radar. Today, meteorological radar networks have been created in all developed countries: in the United States, the NEXRAD network unites about 150 WSR-88D Doppler polarized S-band radars; in Europe, within the framework of the international OPERA project, about 180 radars from various manufacturers working in various observation programs are networked. Some of them are doppler and polarized. In China, Japan, Australia, radars are also integrated into national networks. In the process of analyzing open sources, we determined the main characteristics of meteorological radar networks in several countries of the world and calculated the required number of radars to cover the territory of the Republic of Kazakhstan.

Layered metamaterials with Sierpinski triangular fractal metasurface: Compatible stealth for S-band radar and infrared

Due to the completely opposite stealth mechanisms of radar and infrared waves, and the limitation of the Planck–Rozanov limit, compatible stealth of S-band radar and infrared is extremely difficult to realize at thin thicknesses. In order to solve the problem, a layered metamaterial consisting of infrared stealth layer (IRSL) with aluminum foil and radar stealth layer (RASL) with carbonyl iron powder is designed. The excellent infrared stealth performance (infrared emissivity < 0.3) is achieved because of the low infrared emissivity aluminum foil and reasonable area design. Meanwhile, the Sierpinski triangular fractal structure of IRSL not only serves to reduce the reflection of radar waves, but also introduces the electromagnetic double resonance mechanism of one-dimensional electric resonance and two-dimensional magnetic resonance to lose waves. Therefore, the effective absorption (RL < −10 dB) of 2.12–3.5 GHz in S-band is achieved with a thickness of only 2.24 mm. The double-layer model with fractal structure in this work realizes the perfect compatible stealth for S-band radar and infrared at extremely thin thickness, which provides a new design idea for the development of multi-band compatible stealth.

Clutter and Interference Cancellation in River Surface Velocity Measurement with a Coherent S-Band Radar

Using a Doppler radar to measure river surface velocity is a safe and effective technique. However, the measurement would be severely affected by undesired targets that enter the illuminated area of radar. The issue is worsened when measuring the surface velocities of wide rivers because undesired targets such as boats and ships are more likely to be present. The buoy boats fixed on the river surface and cargo ships sailing on the river would generate ground clutter and moving target interference, respectively. The clutter and interference can mask the signal produced by the Bragg scattering and seriously bias the extraction result of river surface velocity. This paper proposes two effective methods to remove ground clutter and moving target interference, respectively. One is an improved phase-based method that eliminates ground clutter after obtaining its boundaries through the phase in the frequency domain, and another is an improved constant false alarm rate (CFAR) detector that combines smallest-of selection logic and a multi-step deletion scheme to detect and remove interference in the time-Doppler spectrum. The experimental data measuring the surface velocity of the Yangtze River with a coherent S-band radar in July 2022 are used to verify the proposed methods. The results show that the proposed methods can effectively remove ground clutter and moving target interference, respectively. After clutter and interference cancellation, a more reasonable result of river surface velocity distribution can be extracted. Therefore, the methods proposed in this paper can be used to remove clutter and interference when extracting the surface velocity of rivers with numerous undesired targets.

Ionospheric correction of S-band tracking radar data using NavIC S-band signals in missile test range applications

AbstractIn missile test ranges, complex missions demand precise trajectory generated by radar. Both the radar and Global Navigation Satellite System (GNSS) signals are affected by atmospheric effects, degrading their accuracy and performance. The Indian Regional Navigation Satellite System/Navigation with Indian Constellation (IRNSS/NavIC) transmits signals in the S-band together with the L-band. This paper presents a novel experimental technique to improve the tracking accuracy of S-band radars using the concurrent NavIC S-band signal. The ionospheric delay using the NavIC S-band signal is calculated first, and the results are used to improve the trajectory data of simultaneously operating S-band radars. This is a unique application of the NavIC S-band signals apart from its conventional usage. During a launch mission, for low elevation angles, the ionospheric error is found to be ~130 m while at higher elevation angles the error values are found to be ~1–3 m. The concept is validated using data from a missile test mission. This report on the use of S-band GNSS signals for the correction of S-band radar range data offers a clear advantage of simplicity and accuracy.

An Advanced Data Processing Algorithm for Extraction of Polarimetric Radar Signatures of Moving Automotive Vehicles Using the H/A/α Decomposition Technique

A dedicated signal and data processing chain is proposed for a fully polarimetric Doppler surveillance S-band radar to extract the polarimetric signatures of moving targets. To extract the target’s polarimetric features, detection, clustering, and tracking steps are realized for a multi-target environment in the range-Doppler domain. A dedicated data fusion method for all four polarimetric radar channel signals is implemented to take full advantage of the additional polarimetric information and improve the detection performance. While tracking each particular target, polarization information is collected and used to describe their polarization scattering characteristics. Using the polarimetric H/A/α decomposition technique, the polarimetric features of moving automotive targets are extracted and investigated. The developed processing chain has been applied to the signals scattered from vehicles moving in a highway. By employing both time averaging and spatial averaging of the statistical coherency matrix, the polarimetric signatures of both moving vehicles and static clutter have been presented in the two-dimensional H/α plane. It has been found that the spatial averaging approach results in polarimetric signatures of moving vehicles that give the opportunity to directly and without consideration of the motion of the targets compare the polarization features of moving targets and static clutter. Therefore, this method can be used to improve the performance of target detection or target classification.

Suzuki Distributed Monostatic and Bistatic S-Band Radar Sea Clutter

Low grazing angle S-band radar sea clutter data, collected with the NetRAD multistatic radar system, are analyzed. The Suzuki distribution, a compound Gaussian model with log normal texture, is found to be a good model for both monostatic and bistatic clutter. Clutter textures from simultaneously recorded monostatic and bistatic data are interpreted using hydrodynamics, providing estimates of the water depth and wave direction.

A Uniformity Index for Precipitation Particle Axis Ratios Derived from Radar Polarimetric Parameters for the Identification and Analysis of Raindrop Areas

A uniformity index for the axis ratios (Uar) derived from dual polarization weather radar data is proposed for raindrop area identification and analysis. The derivation of this new parameter is based on radar scattering simulations and assumptions. Uar is between 0 and 1 and can be calculated from the differential reflectivity (ZDR) and the copolar correlation coefficient (ρhv), which reflects the uniformity of the axis ratio (r) of the particle group. For raindrops, Uar is close to 1 under ideal conditions, but is clearly different from that of ice particles whose value is close to 0. Studies conducted during two convective weather events observed by X-band and S-band radar are presented to show the Uar features. In convective areas, high Uar presents a U-shaped vertical structure. One branch corresponds to the ZDR column, while the other branch is located at the rear of the convective cloud zone and is lower in altitude, representing the process of ice particles melting into raindrops and then being transported upward by a strong updraft. In stratiform cloud areas, a more than 95% overall identification ratio is obtained when the threshold of Uar is set to 0.2~0.3 for discriminating rain layers.

Study on the Quantitative Precipitation Estimation of X-Band Dual-Polarization Phased Array Radar from Specific Differential Phase

In this study, the quantitative precipitation estimation (QPE) capability of three X-band dual-polarization phased array radars (PAR) in Guangzhou, South China, was demonstrated, with an S-band operational dual-polarization radar as the benchmark. Rainfall rate (R) estimators based on the specific differential phase (KDP) for summer precipitation for both X-band and S-band radars were derived from the raindrop size distributions (DSDs) observed by a 2-dimensional video disdrometer (2DVD) in South China. Rainfall estimates from the radars were evaluated with gauge observations in three events, including pre-summer rainfall, typhoon precipitation, and local severe convective precipitation. Observational results showed that radar echoes from the X-band PARs suffered much more severely from attenuation than those from the S-band radar. Compared to S-band observations, the X-band echoes can disappear when the signal-to-noise ratio drops to a certain level due to severe attenuation, resulting in different estimated rainfall areas for X- and S-band radars. The attenuation corrected by KDP had good consistency with S-band observations, but the accuracy of attenuation correction was affected by DSD uncertainty and may vary in different types of precipitation. The QPE results demonstrated that the R(KDP) estimator produced better rainfall accumulations from the X-band PAR observations compared to the S-band observations. For both the X-band and S-band radars, the estimates of hourly accumulated rainfall became more accurate in heavier rainfall, due to the decreases of both the DSD uncertainty and the impact of measurement errors. In the heavy precipitation area, the estimation accuracy of the X-band radar was high, and the overestimation of the S-band radar was obvious. Through the analysis of the ZH-ZDR distribution in the three weather events, it was found that the X-band PAR with the capability of high spatiotemporal observations can capture minute-level changes in the microphysical characteristics, which help improve the estimation accuracy of ground rainfall.

Prediction of Ship Motion Attitude From Radial Velocity of Water Particle Using Coherent S-Band Radar

Prediction of Ship Motion Attitude From Radial Velocity of Water Particle Using Coherent S-Band Radar

Wave Parameter Inversion From Motion-Affected Echoes Using Shipboard Coherent Microwave Radar

Shipboard coherent microwave radar has been a rapidly developing tool for ocean wave measurements. However, the radial velocity estimated from echoes collected with a shipboard radar is significantly affected by the forward speed and six-degrees-of-freedom (six-DOF) motion of the ship. Accordingly, the performance of ocean wave parameter inversion using such radar degrades. To address this problem, the distribution of energy modulated by the ship motion in the wavenumber-frequency spectrum is illustrated, and wave parameters inversion method based on shipboard coherent S-band radar is proposed. An adaptive filter is designed according to the distribution of the energy components modulated by the ship motion in the wavenumber-frequency spectrum. The proposed method filters out the non-wave components and preserves the wave field components. A two-dimensional inverse Fourier transform is applied to the filtered wavenumber-frequency spectrum to obtain the spatial-temporal radial velocities. Then the wave height spectrum is estimated from the radial velocities based on the direct relationship between the radial velocity spectrum and the wave height spectrum. Later, the significant wave height and mean wave period can be derived from the wave height spectrum. A dataset collected with a shipboard coherent S-band radar in the South China Sea in December 2020 is analyzed. The ship deployed with the radar sailed around a wave buoy according to a route plan for two days in that experiment. Comparisons between the radar-estimated and buoy-measured measurements in cases of ship motion are conducted. The results indicate that the proposed method can invert wave parameters well.

Inversion of Wave Parameters From Time-Doppler Spectrum Using Shore-Based Coherent S-Band Radar

For coherent microwave radar, the Bragg scattering from the broken-short waves generated after wave breaking usually introduces extra low-frequency components in the estimated wave height spectrum and, thus, leads to inaccurate retrievals of wave parameters, especially the overestimation of wave period. In order to eliminate the impacts of wave breaking, some methods based on the removal of “group line” in the spatial–temporal domain are proposed to estimate wave parameters. However, these methods are not suitable for the case that the spatial–temporal data are not available. To address this problem, a method is proposed to invert wave parameters only from the time-Doppler spectrum. Temporal velocity series are derived from the time-Doppler spectrum in which breaking components are removed. Then, the wave height spectrum from which wave parameters can be obtained is estimated from the velocity series by the direct transform relationship based on the linear wave theory. Without spatial–temporal data, the “group line” can be removed using the proposed method, and the method is validated by simulation. In addition, an approximately 11-day dataset collected with a shore-based coherent S-band radar deployed along the coast of Zhejiang province in China is reanalyzed and used to retrieve significant wave height and mean wave period. Compared with the buoy-measured data, the significant wave heights and mean wave periods retrieved by the proposed method have the root-mean-square differences (RMSDs) of 0.25 m and 0.60 s, respectively, and also have the correlation coefficients (CCs) of 0.94 and 0.81, respectively. The results indicate that the proposed method can invert wave parameters from the time-Doppler spectrum with a reasonable performance.

Dual-Frequency Retrieval of Soil Moisture from L- and S-Band Radar Data for Corn and Soybean

Radar backscattering responds differently to soil moisture due to vegetation effects depending on the microwave frequency. The retrieval of soil moisture using a single frequency has been common. In this paper, we study how soil moisture retrieval performs using dual-frequency radar backscattering (L- and S-bands) compared with using L-band only. The dual-frequency inputs increase the amount of independent information, which is expected to reduce the uncertainty in estimating soil moisture. Forward scattering models for corn and soybean fields were previously generated and validated with the L-band for the SMAPVEX12 campaign: they are inverted as an independent test for the retrieval of soil moisture using the SMEX02 campaign data in this paper. It is demonstrated that L-band modeling of forward scattering processes is scalable at the S-band, in that the physics and parameters behind modeling the vegetation effects remain the same between L- and S-bands. Either L- or S-band single-frequency retrieval has reliable performance for soil moisture retrieval. Furthermore, averaging the retrieved soil moisture from both frequencies further improves the retrieval performance. The averaging avoids the determination of the weights of the L- and S-band sigma0 during the cost function minimization. The dual frequency retrieval is evaluated with the unbiased RMSE of 0.031 and 0.057 m3/m3 for corn and soybean, respectively, which are improvements by up to 0.010 and 0.004 m3/m3, compared with single-frequency cases. The findings here can apply to the upcoming NISAR mission featuring L- and S-bands.

Contrasting features of monsoon convection over land and sea in the west coast of peninsular India as revealed by S-band radar

Contrasting features of monsoon convection over land and sea in the west coast of peninsular India as revealed by S-band radar