Special Issue "Radar Polarimetry—Applications in Remote Sensing of the Atmosphere"

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

Deadline for manuscript submissions: closed (31 October 2019).

Special Issue Editors

Dr. Haonan Chen

Guest Editor
NOAA Earth System Research Laboratory, 325 Broadway, Boulder, CO 80305, USA
Interests: radar remote sensing; radar polarimetry; radar and satellite data fusion; precipitation microphysics; precipitation classification and quantification using multiparameter weather radar
Prof. V. Chandrasekar
Website
Guest Editor
Colorado State University, 1373 Campus Delivery, Fort Collins, CO 80523, USA
Interests: radar meteorology; radar system and networking; polarimetric analysis and signal processing; wave propagation and remote sensing
Dr. Sanghun Lim
Website
Guest Editor
Korea Institute of Civil Engineering and Building Technology, Korea
Interests: radar meteorology/hydrology; precipitation microphysics; precipitation identification and quantitative precipitation estimation
Special Issues and Collections in MDPI journals
Prof. Tomoo Ushio
Website
Guest Editor
Department of Aeronautics and Astronautics, Tokyo Metropolitan University, 1 Chome-1 Minamiosawa, Hachioji, Tokyo 192-0364, Japan
Interests: radar-based remote sensing; passive and active remote sensing of atmosphere from spaceborne platforms; and atmospheric electricity

Special Issue Information

Dear Colleagues,

Radar has been widely used for remote sensing of weather, climate, hydrology, and the environment. Over the past 30 years, numerous radar techniques and algorithms have been developed for measuring, modeling, simulating and forecasting the Earth’s atmosphere state. In particular, polarization diversity has great potential to characterize precipitation microphysics and different atmospheric properties. The ground-based polarimetric radar can also be used for validation of satellite (i.e., passive or active space-borne sensors) observations and products. This Special Issue focuses on recent advances in polarimetric radar applications in geoscience and remote sensing. Contributions are welcome from all areas of active remote sensing of the atmosphere. Submissions are solicited covering, but not limited to, the following topics:

  • Concept of wave propagation and polarization
  • Radar remote sensing of environment
  • Advances in polarimetric radar hardware, signal processing, and data quality control
  • Scanning and vertically pointing cloud and precipitation radars
  • Identification of hydrometeor phase using polarimetric and Doppler spectra radar measurements
  • Remote sensing precipitation measurement, validation, and applications
  • The International Workshop on Small Weather Radars (ISWR 2018)

Dr. Haonan Chen  
Prof. V. Chandrasekar
Dr. Sanghun Lim
Prof. Tomoo Ushio
Guest Editors

Manuscript Submission Information

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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 2200 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

  • Quantitative remote sensing
  • Polarization theory/application
  • Atmospheric sensing
  • Polarimetric Radar
  • Satellite
  • Precipitation retrieval, validation and application

Published Papers (12 papers)

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Open AccessArticle
Melting Layer Detection and Characterization based on Range Height Indicator–Quasi Vertical Profiles
Remote Sens. 2019, 11(23), 2848; https://doi.org/10.3390/rs11232848 - 29 Nov 2019
Abstract
The melting layer (ML) is an important region used to describe the transition of hydrometeors from the solid to the liquid phase. It is a typical feature used to characterize the vertical structure of the stratiform precipitation. The present study implements a new [...] Read more.
The melting layer (ML) is an important region used to describe the transition of hydrometeors from the solid to the liquid phase. It is a typical feature used to characterize the vertical structure of the stratiform precipitation. The present study implements a new automatic melting-layer detection algorithm based on the range-height-indicator–quasi-vertical profile (R-QVP) in the X-band dual-polarization radars. The algorithm uses the gradients of the polarimetric radar variables reflectivity factor at horizontal polarization (Zh), differential reflectivity (Zdr), and copolar correlation coefficient (ρhv), and their combinations to describe the ML characteristics. The melting layer heights derived from the radar were compared and validated with the heights of the 0 °C wet-bulb temperature derived from the Modern-Era retrospective analysis for research and applications (MERRA) reanalysis datasets and obtained high correlation coefficient 0.96. The R-QVP combined with this algorithm led to spatial and temporal variabilities of the melting layer thickness. The thickness of the melting layer was independent of the seasonal, spatial, and temporal variabilities of the precipitations. Intriguing polarimetric signatures have been observed inside, above, and below the ML, based on the phase of the precipitation particles. The statistics of the polarimetric variables were evaluated for ML, rain, and snow. Further, the linkage between enhanced specific differential phase shift (Kdp) and Zdr in the dendritic growth layer (DGL) and surface precipitation was also described. Full article
(This article belongs to the Special Issue Radar Polarimetry—Applications in Remote Sensing of the Atmosphere)
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Open AccessArticle
Continuous Monitoring of Differential Reflectivity Bias for C-Band Polarimetric Radar Using Online Solar Echoes in Volume Scans
Remote Sens. 2019, 11(22), 2714; https://doi.org/10.3390/rs11222714 - 19 Nov 2019
Abstract
The measurement error of differential reflectivity (ZDR), especially systematic ZDR bias, is a fundamental issue for the application of polarimetric radar data. Several calibration methods have been proposed and applied to correct ZDR bias. However, recent studies have shown [...] Read more.
The measurement error of differential reflectivity (ZDR), especially systematic ZDR bias, is a fundamental issue for the application of polarimetric radar data. Several calibration methods have been proposed and applied to correct ZDR bias. However, recent studies have shown that ZDR bias is time-dependent and can be significantly different on two adjacent days. This means that the frequent monitoring of ZDR bias is necessary, which is difficult to achieve with existing methods. As radar sensitivity has gradually been enhanced, large amounts of online solar echoes have begun to be observed in volume-scan data. Online solar echoes have a high frequency, and a known theoretical value of ZDR (0 dB) could thus allow the continuous monitoring of ZDR bias. However, online solar echoes are also affected by low signal-to-noise ratio and precipitation attenuation for short-wavelength radar. In order to understand the variation of ZDR bias in a C-band polarimetric radar at the Nanjing University of Information Science and Technology (NUIST-CDP), we analyzed the characteristics of online solar echoes from this radar, including the daily frequency of occurrence, the distribution along the radial direction, precipitation attenuation, and fluctuation caused by noise. Then, an automatic method based on online solar echoes was proposed to monitor the daily ZDR bias of the NUIST-CDP. In the proposed method, a one-way differential attenuation correction for solar echoes and a maximum likelihood estimation using a Gaussian model were designed to estimate the optimal daily ZDR bias. The analysis of three months of data from the NUIST-CDP showed the following: (1) Online solar echoes occurred very frequently regardless of precipitation. Under the volume-scan mode, the average number of occurrences was 15 per day and the minimum number was seven. This high frequency could meet the requirements of continuous monitoring of the daily ZDR bias under precipitation and no-rain conditions. (2) The result from the proposed online solar method was significantly linearly correlated with that from the vertical pointing method (observation at an elevation angle of 90°), with a correlation coefficient of 0.61, suggesting that the proposed method is feasible. (3) The day-to-day variation in the ZDR bias was relatively large, and 32% of such variations exceeded 0.2 dB, meaning that a one-time calibration was not representative in time. Accordingly, continuous calibration will be necessary. (4) The ZDR bias was found to be largely influenced by the ambient temperature, with a large negative correlation between the ZDR bias and the temperature. Full article
(This article belongs to the Special Issue Radar Polarimetry—Applications in Remote Sensing of the Atmosphere)
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Open AccessArticle
The Potential for Discriminating Microphysical Processes in Numerical Weather Forecasts Using Airborne Polarimetric Radio Occultations
Remote Sens. 2019, 11(19), 2268; https://doi.org/10.3390/rs11192268 - 28 Sep 2019
Cited by 3
Abstract
Accurate representation of cloud microphysical processes in numerical weather and climate models has proven challenging, in part because of the highly specialized instrumentation required for diagnosing errors in simulated distributions of hydrometeors. Global Navigation Satellite System (GNSS) polarimetric radio occultation (PRO) is a [...] Read more.
Accurate representation of cloud microphysical processes in numerical weather and climate models has proven challenging, in part because of the highly specialized instrumentation required for diagnosing errors in simulated distributions of hydrometeors. Global Navigation Satellite System (GNSS) polarimetric radio occultation (PRO) is a promising new technique that is sensitive to hydrometeors and has the potential to help address these challenges by providing microphysical observations that are relevant to larger spatial scales, especially if this type of observing system can be implemented on aircraft that can target heavy precipitation events. Two numerical experiments were run using a mesoscale model configured with two different microphysical parameterization schemes for a very intense atmospheric river (AR) event that was sampled by aircraft deploying dropsondes just before it made landfall in California, during the CalWater 2015 field campaign. The numerical experiments were used to simulate profiles of airborne polarimetric differential phase delay observations. The differential phase delay due to liquid water hydrometeors below the freezing level differed significantly in the two experiments, as well as the height of the maximum differential phase delay due to all hydrometeors combined. These results suggest that PRO observations from aircraft have the potential to contribute to validating and improving the representation of microphysical processes in numerical weather forecasts once these observations become available. Full article
(This article belongs to the Special Issue Radar Polarimetry—Applications in Remote Sensing of the Atmosphere)
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Open AccessArticle
Microphysical Characteristics of Three Convective Events with Intense Rainfall Observed by Polarimetric Radar and Disdrometer in Eastern China
Remote Sens. 2019, 11(17), 2004; https://doi.org/10.3390/rs11172004 - 24 Aug 2019
Cited by 1
Abstract
Polarimetric radar and disdrometer observations obtained during the 2014 Observation, Prediction, and Analysis of Severe Convection of China (OPACC) field campaign are used in this study to investigate the microphysical characteristics of three primary types of organized intense rainfall events (meiyu rainband, typhoon [...] Read more.
Polarimetric radar and disdrometer observations obtained during the 2014 Observation, Prediction, and Analysis of Severe Convection of China (OPACC) field campaign are used in this study to investigate the microphysical characteristics of three primary types of organized intense rainfall events (meiyu rainband, typhoon outer rainband, and squall line) in eastern China. Drop size distributions (DSDs) of these three events on the ground are derived from measurements of a surface disdrometer, while the corresponding three-dimensional microphysical structures are obtained from the Nanjing University C-band polarimetric radar (NJU-CPOL). Although the environmental moisture and instability conditions are different, all three events possess relatively high freezing level favorable for warm-rain processes where the high medium to small raindrop concentration at low levels is consistent with the high surface rainfall rates. Convection is tallest in the squall line where abundant ice-phase processes generate large amounts of rimed particles (graupel and hail) above the freezing level and the largest surface raindrops are present among these three events. The storm tops of both the typhoon and meiyu rainbands are lower than that in the squall line, composed of less active ice processes above the freezing level. The typhoon rainrate is more intense than that of meiyu, enhanced by higher coalescence efficiency. A revised generalized intercept parameter versus mass-weighted mean diameter (Nw-Dm) space diagram is constructed to describe the DSD distributions over the three events and illustrate the relative DSD positions for heavy precipitation. DSDs of these intense rainfall convections observed in this midlatitude region of eastern Asia somewhat represent the typical DSD characteristics in low latitudes, suggesting that the parameterization of microphysical characteristics in eastern China in numerical models needs to be further investigated to improve rain fall forecasts in these heavy rainfall events. Full article
(This article belongs to the Special Issue Radar Polarimetry—Applications in Remote Sensing of the Atmosphere)
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Open AccessArticle
Comparison of Radar-Based Hail Detection Using Single- and Dual-Polarization
Remote Sens. 2019, 11(12), 1436; https://doi.org/10.3390/rs11121436 - 17 Jun 2019
Cited by 1
Abstract
The comparative analysis of radar-based hail detection methods presented here, uses C-band polarimetric radar data from Czech territory for 5 stormy days in May and June 2016. The 27 hail events were selected from hail reports of the European Severe Weather Database (ESWD) [...] Read more.
The comparative analysis of radar-based hail detection methods presented here, uses C-band polarimetric radar data from Czech territory for 5 stormy days in May and June 2016. The 27 hail events were selected from hail reports of the European Severe Weather Database (ESWD) along with 21 heavy rain events. The hail detection results compared in this study were obtained using a criterion, which is based on single-polarization radar data and a technique, which uses dual-polarization radar data. Both techniques successfully detected large hail events in a similar way and showed a strong agreement. The hail detection, as applied to heavy rain events, indicated a weak enhancement of the number of false detected hail pixels via the dual-polarization hydrometeor classification. We also examined the performance of hail size detection from radar data using both single- and dual-polarization methods. Both the methods recognized events with large hail but could not select the reported events with maximum hail size (diameter above 4 cm). Full article
(This article belongs to the Special Issue Radar Polarimetry—Applications in Remote Sensing of the Atmosphere)
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Open AccessArticle
Adaptive Blending Method of Radar-Based and Numerical Weather Prediction QPFs for Urban Flood Forecasting
Remote Sens. 2019, 11(6), 642; https://doi.org/10.3390/rs11060642 - 16 Mar 2019
Cited by 6
Abstract
Preparing proper disaster prevention measures is important for decreasing the casualties and property losses resulting from floods. One of the most efficient measures in this regard is real-time flood forecasting using quantitative precipitation forecasts (QPFs) based on either short-term radar-based extrapolation or longer-term [...] Read more.
Preparing proper disaster prevention measures is important for decreasing the casualties and property losses resulting from floods. One of the most efficient measures in this regard is real-time flood forecasting using quantitative precipitation forecasts (QPFs) based on either short-term radar-based extrapolation or longer-term numerical weather prediction. As both methods have individual advantages and limitations, in this study we developed a new real-time blending technique to improve the accuracy of rainfall forecasts for hydrological applications. We tested the hydrological applicability of six QPFs used for urban flood forecasting in Seoul, South Korea: the McGill Algorithm for Prediction Nowcasting by Lagrangian Extrapolation (MAPLE), KOrea NOwcasting System (KONOS), Spatial-scale Decomposition method (SCDM), Unified Model Local Data Assimilation and Prediction System (UM LDAPS), and Advanced Storm-scale Analysis and Prediction System (ASAPS), as well as our proposed blended approach based on the assumption that the error of the previously predicted rainfall is similar to that of current predicted rainfall. We used the harmony search algorithm to optimize real-time weights that would minimize the root mean square error between predicted and observed rainfall for a 1 h lead time at 10 min intervals. We tested these models using the Storm Water Management Model (SWMM) and Grid-based Inundation Analysis Model (GIAM) to estimate urban flood discharge and inundation using rainfall from the QPFs as input. Although the blended QPF did not always have the highest correlation coefficient, its accuracy varied less than that of the other QPFs. In addition, its simulated water depth in pipe and spatial extent were most similar to observed inundated areas, demonstrating the value of this new approach for short-term flood forecasting. Full article
(This article belongs to the Special Issue Radar Polarimetry—Applications in Remote Sensing of the Atmosphere)
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Open AccessArticle
Statistical Characteristics of Raindrop Size Distribution in the Monsoon Season Observed in Southern China
Remote Sens. 2019, 11(4), 432; https://doi.org/10.3390/rs11040432 - 19 Feb 2019
Cited by 10
Abstract
This study investigates the statistical characteristics of raindrop size distributions (DSDs) in monsoon season with observations collected by the second-generation Particle Size and Velocity (Parsivel2) disdrometer located in Zhuhai, southern China. The characteristics are quantified based on convective and stratiform precipitation [...] Read more.
This study investigates the statistical characteristics of raindrop size distributions (DSDs) in monsoon season with observations collected by the second-generation Particle Size and Velocity (Parsivel2) disdrometer located in Zhuhai, southern China. The characteristics are quantified based on convective and stratiform precipitation classified using the rainfall intensity and total number of drops. On average of the whole dataset, the DSD characteristic in southern China consists of a higher number concentration of relatively small-sized drops when compare with eastern China and northern China, respectively. In the meanwhile, the Dm and log10Nw scatter plots prove that the convective rain in monsoon season can be identified as maritime-like cluster. The DSD is in good agreement with a three-parameter gamma distribution, especially for the medium to large raindrop size. Using filtered data observed by Parsivel2 disdrometer, a new Z–R relationship, Z = 498R1.3, is derived for convective rain in monsoon season in southern China. These results offer insights of the microphysical nature of precipitation in Zhuhai during monsoon season, and provide essential information that may be useful for precipitation retrievals based on weather radar observations. Full article
(This article belongs to the Special Issue Radar Polarimetry—Applications in Remote Sensing of the Atmosphere)
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Open AccessArticle
Phased-Array Radar System Simulator (PASIM): Development and Simulation Result Assessment
Remote Sens. 2019, 11(4), 422; https://doi.org/10.3390/rs11040422 - 19 Feb 2019
Cited by 3
Abstract
In this paper, a system-specific phased-array radar system simulator was developed, based on a time-domain modeling and simulation method, mainly for system performance evaluation of the future Spectrum-Efficient National Surveillance Radar (SENSR). The goal of the simulation study was to establish a complete [...] Read more.
In this paper, a system-specific phased-array radar system simulator was developed, based on a time-domain modeling and simulation method, mainly for system performance evaluation of the future Spectrum-Efficient National Surveillance Radar (SENSR). The goal of the simulation study was to establish a complete data quality prediction method based on specific radar hardware and electronics designs. The distributed weather targets were modeled using a covariance matrix-based method. The data quality analysis was conducted using Next-Generation Radar (NEXRAD) Level-II data as a basis, in which the impact of various pulse compression waveforms and channel electronic instability on weather radar data quality was evaluated. Two typical weather scenarios were employed to assess the simulator’s performance, including a tornado case and a convective precipitation case. Also, modeling of some demonstration systems was evaluated, including a generic weather radar, a planar polarimetric phased-array radar, and a cylindrical polarimetric phased-array radar. Corresponding error statistics were provided to help multifunction phased-array radar (MPAR) designers perform trade-off studies. Full article
(This article belongs to the Special Issue Radar Polarimetry—Applications in Remote Sensing of the Atmosphere)
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Open AccessArticle
Utilization of a C-band Polarimetric Radar for Severe Rainfall Event Analysis in Complex Terrain over Eastern China
Remote Sens. 2019, 11(1), 22; https://doi.org/10.3390/rs11010022 - 23 Dec 2018
Cited by 6
Abstract
Polarimetric radar measurements and products perform as the cornerstones of modern severe weather warning and nowcast systems. Two radar quantitative precipitation estimation (QPE) frameworks, one based on a radar-gauge feedback mechanism and the other based on standard rain drop size distribution (DSD)-derived rainfall [...] Read more.
Polarimetric radar measurements and products perform as the cornerstones of modern severe weather warning and nowcast systems. Two radar quantitative precipitation estimation (QPE) frameworks, one based on a radar-gauge feedback mechanism and the other based on standard rain drop size distribution (DSD)-derived rainfall retrieval relationships, are both evaluated and investigated through an extreme severe convective rainfall event that occurred on 23 June 2015 in the mountainous region over eastern China, using the first routinely operational C-band polarimetric radar in China. Complex rainstorm characteristics, as indicated by polarimetric radar observables, are also presented to account for the severe rainfall field center located in the gap between gauge stations. Our results show that (i) the improvements of the gauge-feedback-derived radar QPE estimator can be attributed to the attenuation correction technique and dynamically adjusted Z–R relationships, but it greatly relies on the gauge measurement accuracy. (ii) A DSD-derived radar QPE estimator based on the specific differential phase (KDP) performs best among all rainfall estimators, and the interaction between the mesocyclone and the windward slope of the mountainous terrain can account for its apparent overestimation. (iii) The rainstorm is mainly dominated by small-sized and moderate-sized raindrops, with the mean volume diameter being less than 2 mm, but its KDP column (KDP > 3°·km−1) has a liquid water content that is higher than 2.4815 g·m−3, and a high raindrop concentration (Nw) with log10(Nw) exceeding 5.1 mm−1m−3. In addition, small hailstones falling and melting are also found in this event, which further aggregates Nw upon the severe rainfall center in the gap between gauge stations. Full article
(This article belongs to the Special Issue Radar Polarimetry—Applications in Remote Sensing of the Atmosphere)
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Open AccessArticle
An Inverse Model for Raindrop Size Distribution Retrieval with Polarimetric Variables
Remote Sens. 2018, 10(8), 1179; https://doi.org/10.3390/rs10081179 - 26 Jul 2018
Cited by 10
Abstract
This paper proposes an inverse model for raindrop size distribution (DSD) retrieval with polarimetric radar variables. In this method, a forward operator is first developed based on the simulations of monodisperse raindrops using a T-matrix method, and then approximated with a polynomial function [...] Read more.
This paper proposes an inverse model for raindrop size distribution (DSD) retrieval with polarimetric radar variables. In this method, a forward operator is first developed based on the simulations of monodisperse raindrops using a T-matrix method, and then approximated with a polynomial function to generate a pseudo training dataset by considering the maximum drop diameter in a truncated Gamma model for DSD. With the pseudo training data, a nearest-neighborhood method is optimized in terms of mass-weighted diameter and liquid water content. Finally, the inverse model is evaluated with simulated and real radar data, both of which yield better agreement with disdrometer observations compared to the existing Bayesian approach. In addition, the rainfall rate derived from the DSD by the inverse model is also improved when compared to the methods using the power-law relations. Full article
(This article belongs to the Special Issue Radar Polarimetry—Applications in Remote Sensing of the Atmosphere)
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Open AccessTechnical Note
Pointing Accuracy of an Operational Polarimetric Weather Radar
Remote Sens. 2019, 11(9), 1115; https://doi.org/10.3390/rs11091115 - 10 May 2019
Cited by 1
Abstract
Exact navigation of detected radar signals is crucial for usage of radar data in meteorological applications. The antenna pointing accuracy in azimuth and elevation of a polarimetric weather research radar depending on position of the sun is assessed using dedicated solar boxscans in [...] Read more.
Exact navigation of detected radar signals is crucial for usage of radar data in meteorological applications. The antenna pointing accuracy in azimuth and elevation of a polarimetric weather research radar depending on position of the sun is assessed using dedicated solar boxscans in a sequence of 10 min. The research radar of the German Meteorological Service (Deutscher Wetterdienst, DWD) is located at the meteorological observatory Hohenpeissenberg. It is identical to the 17 weather radars of the German weather radar network. A non-linear azimuthal variation of azimuthal pointing bias of up to 0.1 is found, which is significant as this is commonly viewed as the target pointing accuracy. This azimuthal variation can be attributed to the mechanical design of the drive train with the angle encoder. This includes the inherent backlash of the gear-drive assembly. The pointing bias estimates based on over 1000 boxscans from 26 days show a small case by case variability, which indicates that dedicated solar boxscans from one day are sufficient to characterize the pointing performance of a particular system. An azimuth and elevation range that is covered with this approach is limited and dependent on the time of the year. At Hohenpeißenberg, an azimuth range up to 50–300 was covered around summer solstice and about 90 boxscans were acquired. It is shown that the pointing bias based on solar boxscan data are consistent with results from the operational assessment of pointing bias using solar hits from operational scanning if we take into account the fact that the DWD operational scan definition has only a maximum elevation of 25 . The analysis of a full diurnal cycle of boxscans from four operational radar system shows that the azimuthal dependence of azimuth bias needs to be evaluated individually for each system. For one of the systems, the azimuthal variation of the pointing bias of about 0.2 seems related to the bull gear. A difference of the pointing bias for the horizontal and vertical polarization is an indication of beam squint and, eventually, that of a feed misalignment. Beam squint and, as such, the quality of the antenna assembly can easily be monitored with this method during the life-time of a weather radar. Full article
(This article belongs to the Special Issue Radar Polarimetry—Applications in Remote Sensing of the Atmosphere)
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Open AccessTechnical Note
On the Use of Bright Scatterers for Monitoring Doppler, Dual-Polarization Weather Radars
Remote Sens. 2018, 10(7), 1007; https://doi.org/10.3390/rs10071007 - 25 Jun 2018
Cited by 1
Abstract
“Bright” scatterers are useful for monitoring modern weather radars. In order to be “bright”, a point target with deterministic backscattering properties should be present at a near range and be hit by the antenna beam axis. In this note, a statistical characterization of [...] Read more.
“Bright” scatterers are useful for monitoring modern weather radars. In order to be “bright”, a point target with deterministic backscattering properties should be present at a near range and be hit by the antenna beam axis. In this note, a statistical characterization of the echoes from a metallic tower located on Cimetta, at an 18 km range and at the same altitude as the Monte Lema radar, is presented. The analysis is based on five clear sky days (1440 samples with a spatial resolution of 1° × 1° × 83.33 m). The spectral and polarimetric signatures are striking: The spectrum width is perfectly stable; the mean radial velocity is very stable; the radar reflectivity is also quite stable, with the vertical (V) polarization being more variable than the horizontal (H) one. As far as the polarimetric information is concerned, the daily average of the differential reflectivity is approximately 1 ± 0.9 dB. The copolar correlation coefficient between H and V is remarkably large (0.9962, on average) and stable. It is believed that these unique and stable ground clutter signals could be used to monitor operational dual-polarization weather radars. Full article
(This article belongs to the Special Issue Radar Polarimetry—Applications in Remote Sensing of the Atmosphere)
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