Relevant bibliographies by topics / Doppler Weather Radar Data

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Doppler Weather Radar Data'

Author: Grafiati
Published: 4 June 2021
Last updated: 7 September 2023

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Journal articles on the topic "Doppler Weather Radar Data"

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Norin, L. "A quantitative analysis of the impact of wind turbines on operational Doppler weather radar data." Atmospheric Measurement Techniques 8, no. 2 (February 5, 2015): 593–609. http://dx.doi.org/10.5194/amt-8-593-2015.

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Abstract. In many countries wind turbines are rapidly growing in numbers as the demand for energy from renewable sources increases. The continued deployment of wind turbines can, however, be problematic for many radar systems, which are easily disturbed by turbines located in the radar line of sight. Wind turbines situated in the vicinity of Doppler weather radars can lead to erroneous precipitation estimates as well as to inaccurate wind and turbulence measurements. This paper presents a quantitative analysis of the impact of a wind farm, located in southeastern Sweden, on measurements from a nearby Doppler weather radar. The analysis is based on 6 years of operational radar data. In order to evaluate the impact of the wind farm, average values of all three spectral moments (the radar reflectivity factor, absolute radial velocity, and spectrum width) of the nearby Doppler weather radar were calculated, using data before and after the construction of the wind farm. It is shown that all spectral moments, from a large area at and downrange from the wind farm, were impacted by the wind turbines. It was also found that data from radar cells far above the wind farm (near 3 km altitude) were affected by the wind farm. It is shown that this in part can be explained by detection by the radar sidelobes and by scattering off increased levels of dust and turbulence. In a detailed analysis, using data from a single radar cell, frequency distributions of all spectral moments were used to study the competition between the weather signal and wind turbine clutter. It is shown that, when weather echoes give rise to higher reflectivity values than those of the wind farm, the negative impact of the wind turbines is greatly reduced for all spectral moments.
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Norin, L. "A quantitative analysis of the impact of wind turbines on operational Doppler weather radar data." Atmospheric Measurement Techniques Discussions 7, no. 8 (August 27, 2014): 8743–76. http://dx.doi.org/10.5194/amtd-7-8743-2014.

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Abstract. In many countries wind turbines are rapidly growing in numbers as the demand for energy from renewable sources increases. The continued deployment of wind turbines can, however, be problematic for many radar systems, which are easily disturbed by turbines located in radar line-of-sight. Wind turbines situated in the vicinity of Doppler weather radars can lead to erroneous precipitation estimates as well as to inaccurate wind- and turbulence measurements. This paper presents a quantitative analysis of the impact of a wind farm, located in southeastern Sweden, on measurements from a nearby Doppler weather radar. The analysis is based on six years of operational radar data. In order to evaluate the impact of the wind farm, average values of all three spectral moments (the radar reflectivity factor, absolute radial velocity, and spectrum width) of the nearby Doppler weather radar were calculated, using data before and after the construction of the wind farm. It is shown that all spectral moments, from a large area at and downrange from the wind farm, were impacted by the wind turbines. It was also found that data from radar cells far above the wind farm (near 3 km altitude) were affected by the wind farm. We show that this is partly explained by changes in the atmospheric refractive index, bending the radar beams closer to the ground. In a detailed analysis, using data from a single radar cell, frequency distributions of all spectral moments were used to study the competition between the weather signal and wind turbine clutter. We show that when weather echoes give rise to higher reflectivity values than that of the wind farm, the negative impact of the wind turbines disappears for all spectral moments.
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Curtis, David C. "Use of Weather Surveillance Radars—88 Doppler Data in Hydrologic Modeling." Transportation Research Record: Journal of the Transportation Research Board 1647, no. 1 (January 1998): 61–66. http://dx.doi.org/10.3141/1647-08.

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Successful hydrologic modeling depends heavily on high-quality rainfall data sets. If hydrologists cannot determine what is coming into a watershed, there is little chance that any hydrologic model will accurately estimate what is coming out on a consistent basis. Hydrologists are frequently forced to use rainfall data sets derived from sparse rain gauge networks that poorly resolve critical rainfall features, leading to inadequate model results. Over the past several years, the modernizing National Weather Service, the Federal Aviation Administration, and the Department of Defense have installed a new nationwide network of weather radars, providing a rich suite of real-time meteorological observations. Radar rainfall estimates from the new radars cover vast areas at a spatial and temporal resolution that would be impossibly expensive to match with a conventional rain gauge network. Hydrologists can now literally see between the gauges and view truer representations of the spatial distribution of rainfall than ever before. Results from the analysis of the January 9-10, 1995, storms in Sacramento, California, show that gauge-adjusted radar rainfall estimates help resolve rainfall features that could not have been inferred from rain gauge analysis alone. Accurate estimates of the volume, timing, and distribution of rainfall helped create excellent modeling results. In Waco, Texas, radar rainfall estimates were used to improve the analysis of excess inflow and infiltration into city storm sewers. The radar rainfall analyses enabled modelers to account for inflow/infiltration variations down to the neighborhood level.
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Lakshmanan, Valliappa, Travis Smith, Kurt Hondl, Gregory J. Stumpf, and Arthur Witt. "A Real-Time, Three-Dimensional, Rapidly Updating, Heterogeneous Radar Merger Technique for Reflectivity, Velocity, and Derived Products." Weather and Forecasting 21, no. 5 (October 1, 2006): 802–23. http://dx.doi.org/10.1175/waf942.1.

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Abstract With the advent of real-time streaming data from various radar networks, including most Weather Surveillance Radars-1988 Doppler and several Terminal Doppler Weather Radars, it is now possible to combine data in real time to form 3D multiple-radar grids. Herein, a technique for taking the base radar data (reflectivity and radial velocity) and derived products from multiple radars and combining them in real time into a rapidly updating 3D merged grid is described. An estimate of that radar product combined from all the different radars can be extracted from the 3D grid at any time. This is accomplished through a formulation that accounts for the varying radar beam geometry with range, vertical gaps between radar scans, the lack of time synchronization between radars, storm movement, varying beam resolutions between different types of radars, beam blockage due to terrain, differing radar calibration, and inaccurate time stamps on radar data. Techniques for merging scalar products like reflectivity, and innovative, real-time techniques for combining velocity and velocity-derived products are demonstrated. Precomputation techniques that can be utilized to perform the merger in real time and derived products that can be computed from these three-dimensional merger grids are described.
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Zrnić, D. S., P. Zhang, V. Melnikov, and E. Kabela. "Fireworks on Weather Radar and Camera." Bulletin of the American Meteorological Society 101, no. 2 (February 1, 2020): E90—E108. http://dx.doi.org/10.1175/bams-d-18-0248.1.

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Abstract High-sensitivity weather radars easily detect nonmeteorological phenomena characterized by weak radar returns. Fireworks are the example presented here. To understand radar observations, an experiment was conducted in which the National Severe Storms Laboratory (NSSL)’s research (3-cm wavelength) dual-polarization radar and a video camera were located at 1 km from fireworks in Norman, Oklahoma. The fireworks from the 4 July 2017 celebration were recorded by both instruments. The experiment is described. Few bursts recorded by the camera are analyzed to obtain the height of the explosion, its maximum diameter, number of stars, and the duration of the visible image. Radar volume scans are examined to characterize the height of the observation, the maximum reflectivity, and its distribution with height. The fireworks location is close to the Terminal Doppler Weather Radar (TDWR) that operates in single polarization at a 5-cm wavelength and monitors hazardous weather over the Oklahoma City airport. A third radar with data from the event is the Weather Surveillance Radar-1988 Doppler (WSR-88D) located in Norman. It has a wavelength of 10 cm and supports technical developments at the Radar Operation Center. Reflectivity factors measured by the three radars are compared to infer the size of dominant scatterers. The polarimetric characteristics of fireworks returns are analyzed. Although these differ from those of precipitation, they are indistinguishable from insect returns. Radar observation of larger fireworks in Fort Worth, Texas, with a WSR-88D is included and compared with the observations of the smaller fireworks in Norman. We expect the detectability of explosions would be similar as of fireworks. Pinpointing locations would be useful to first responders, or air quality forecasters. A benefit of fireworks recognition in weather radar data is that it can prevent contamination of precipitation accumulations.
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Dolan, Brenda A., and Steven A. Rutledge. "An Integrated Display and Analysis Methodology for Multivariable Radar Data." Journal of Applied Meteorology and Climatology 46, no. 8 (August 1, 2007): 1196–213. http://dx.doi.org/10.1175/jam2524.1.

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Abstract Polarimetric Doppler radars provide valuable information about the kinematic and microphysical structure of storms. However, in-depth analysis using radar products, such as Doppler-derived wind vectors and hydrometeor identification, has been difficult to achieve in (near) real time, mainly because of the large volumes of data generated by these radars, lack of quick access to these data, and the challenge of applying quality-control measures in real time. This study focuses on modifying and automating several radar-analysis and quality-control algorithms currently used in postprocessing and merging the resulting data from several radars into an integrated analysis and display in (near) real time. Although the method was developed for a specific network of four Doppler radars: two Weather Surveillance Radar-1988 Doppler (WSR-88D) radars (KFTG and KCYS) and two Colorado State University (CSU) research radars [Pawnee and CSU–University of Chicago–Illinois State Water Survey (CSU–CHILL)], the software is easily adaptable to any radar platform or network of radars. The software includes code to synthesize radial velocities to obtain three-dimensional wind vectors and includes algorithms for automatic quality control of the raw polarimetric data, hydrometeor identification, and rainfall rate. The software was successfully tested during the summers of 2004 and 2005 at the CSU–CHILL radar facility, ingesting data from the four-radar network. The display software allows users the ability to view mosaics of reflectivity, wind vectors, and rain rates, to zoom in and out of radar features easily, to create vertical cross sections, to contour data, and to archive data in real time. Despite the lag time of approximately 10 min, the software proved invaluable for diagnosing areas of intense rainfall, hail, strong updrafts, and other features such as mesocyclones and convergence lines. A case study is presented to demonstrate the utility of the software.
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Li, Rui, Jianxin He, Shunxian Tang, Fang Miao, and Xingang Fan. "Observational Consistency Comparison and Analyses of an X-Band Solid-State Radar and an X-Band Klystron Doppler Radar." Journal of Atmospheric and Oceanic Technology 34, no. 10 (October 2017): 2177–202. http://dx.doi.org/10.1175/jtech-d-16-0220.1.

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AbstractSolid-state weather radar transmitters offer great potential for increased reliability and maintainability, which have been proven to be critical for practical use. Although they have been implemented in radar systems, solid-state transmitters are incapable of producing as high peak power as available in klystrons. The pulse compression technique coupled with mismatched methods allows for low peak-power transmission and can improve the range-resolution and detection performance on the receiving end of a radar system. However, applying solid-state transmitters with pulse compression in weather radar systems still requires strong evidence for data reliability. With side-by-side observational experiments, this study compares a solid-state weather radar with the combined-pulse transmission mode to a close-by klystron Doppler weather radar in an attempt to 1) analyze the capability of the solid-state radar to reduce the near-range blind zone and 2) validate the quality and reliability of data from a solid-state radar that is implemented with the pulse compression technique. The data from the klystron Doppler weather radar are considered accurate and are used as a reference for quantitatively evaluating the solid-state radar data quality and reliability. Comparisons and statistics show that the observations from the solid-state radar are consistent with that from the klystron Doppler weather radar, especially in heavy rainfall. Results from the analysis indicate that the solid-state weather radar has high estimation accuracy in both near and far ranges.
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Li, Nan, Xiyu Mu, Luan Li, and Nanqing Shao. "Preliminary Analysis on the Wind Retrieval Method in Nowcasting." Applied Mechanics and Materials 519-520 (February 2014): 1287–91. http://dx.doi.org/10.4028/www.scientific.net/amm.519-520.1287.

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Extrapolation nowcasting of radar echoes is implemented based on reflectivity data and radial velocity data of Doppler weather radars. VAD algorithm is used to retrieve wind fields, which are used as motion vectors to implement the extrapolation for the reflectivity data within 60 mins. Extrapolation nowcasting results of a weather case by the method agree well with the fact according to radar echo images and statistics. However, nowcasting accuracy decreases as the extrapolation time increases.
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Liou, Yu-Chieng, Howard B. Bluestein, Michael M. French, and Zachary B. Wienhoff. "Single-Doppler Velocity Retrieval of the Wind Field in a Tornadic Supercell Using Mobile, Phased-Array, Doppler Radar Data." Journal of Atmospheric and Oceanic Technology 35, no. 8 (August 2018): 1649–63. http://dx.doi.org/10.1175/jtech-d-18-0004.1.

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AbstractA three-dimensional data assimilation (3DVar) least squares–type single-Doppler velocity retrieval (SDVR) algorithm is utilized to retrieve the wind field of a tornadic supercell using data collected by a mobile, phased-array, Doppler radar [Mobile Weather Radar (MWR) 05XP] with very high temporal resolution (6 s). It is found that the cyclonic circulation in the hook-echo region can be successfully recovered by the SDVR algorithm. The quality of the SDVR analyses is evaluated by dual-Doppler syntheses using data collected by two mobile Doppler radars [Doppler on Wheels 6 and 7 (DOW6 and DOW7, respectively)]. A comparison between the SDVR analyses and dual-Doppler syntheses confirms the conclusion reached by an earlier theoretical analysis that because of the temporally discrete nature of the radar data, the wind speed retrieved by single-Doppler radar is always underestimated, and this underestimate occurs more significantly for the azimuthal (crossbeam) wind component than for the radial (along beam) component. However, the underestimate can be mitigated by increasing the radar data temporal resolution. When the radar data are collected at a sufficiently high rate, the azimuthal wind component may be overestimated. Even with data from a rapid scan, phased-array, Doppler radar, our study indicates that it is still necessary to calculate the SDVR in an optimal moving frame of reference. Finally, the SDVR algorithm’s robustness is demonstrated. Even with a temporal resolution (2 min) much lower than that of the phased-array radar, the cyclonic flow structure in the hook-echo region can still be retrieved through SDVR using data observed by DOW6 or DOW7, although a difference in the retrieved fields does exist. A further analysis indicates that this difference is caused by the location of the radars.
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French, Michael M., Howard B. Bluestein, Ivan PopStefanija, Chad A. Baldi, and Robert T. Bluth. "Reexamining the Vertical Development of Tornadic Vortex Signatures in Supercells." Monthly Weather Review 141, no. 12 (November 25, 2013): 4576–601. http://dx.doi.org/10.1175/mwr-d-12-00315.1.

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Abstract Observations from a hybrid phased-array Doppler radar, the Mobile Weather Radar, 2005 X-band, Phased Array (MWR-05XP), were used to investigate the vertical development of tornadic vortex signatures (TVSs) during supercell tornadogenesis. Data with volumetric update times of ∼10 s, an order of magnitude better than that of most other mobile Doppler radars, were obtained up to storm midlevels during the formation of three tornadoes. It is found that TVSs formed upward with time during tornadogenesis for two cases. In a third case, missing low-level data prevented a complete time–height analysis of TVS development; however, TVS formation occurred first near the ground and then at storm midlevels several minutes later. These results are consistent with the small number of volumetric mobile Doppler radar tornadogenesis cases from the past ∼10 years, but counter to studies prior to that, in which a descending TVS was observed in roughly half of tornado cases utilizing Weather Surveillance Radar-1988 Doppler (WSR-88D) data. A comparative example is used to examine the possible effects relatively long WSR-88D volumetric update times have on determining the mode of tornadogenesis.
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Dissertations / Theses on the topic "Doppler Weather Radar Data"

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Watson, Robert J. "Data comparisons for spatially separated meteorological radars." Thesis, University of Essex, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.337180.

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Ernvik, Aron. "3D visualization of weather radar data." Thesis, Linköping University, Department of Electrical Engineering, 2002. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-1053.

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There are 12 weather radars operated jointly by smhi and the Swedish Armed Forces in Sweden. Data from them are used for short term forecasting and analysis. The traditional way of viewing data from the radars is in 2D images, even though 3D polar volumes are delivered from the radars. The purpose of this work is to develop an application for 3D viewing of weather radar data.

There are basically three approaches to visualization of volumetric data, such as radar data: slicing with cross-sectional planes, surface extraction, and volume rendering. The application developed during this project supports variations on all three approaches. Different objects, e.g. horizontal and vertical planes, isosurfaces, or volume rendering objects, can be added to a 3D scene and viewed simultaneously from any angle. Parameters of the objects can be set using a graphical user interface and a few different plots can be generated.

Compared to the traditional 2D products used by meteorologists when analyzing radar data, the 3D scenes add information that makes it easier for the users to understand the given weather situations. Demonstrations and discussions with meteorologists have rendered positive reactions. The application will be installed and evaluated at Arlanda airport in Sweden.

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Tilford, Kevin A. "Weather radar data for operational hydrology." Thesis, University of Salford, 1992. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.315383.

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Wilson, Damian R. "Advanced polarization and Doppler radar techniques to study precipitation microphysics." Thesis, University of Reading, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.284066.

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Aygar, Alper. "Doppler Radar Data Processing And Classification." Master's thesis, METU, 2008. http://etd.lib.metu.edu.tr/upload/12609890/index.pdf.

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In this thesis, improving the performance of the automatic recognition of the Doppler radar targets is studied. The radar used in this study is a ground-surveillance doppler radar. Target types are car, truck, bus, tank, helicopter, moving man and running man. The input of this thesis is the output of the real doppler radar signals which are normalized and preprocessed (TRP vectors: Target Recognition Pattern vectors) in the doctorate thesis by Erdogan (2002). TRP vectors are normalized and homogenized doppler radar target signals with respect to target speed, target aspect angle and target range. Some target classes have repetitions in time in their TRPs. By the use of these repetitions, improvement of the target type classification performance is studied. K-Nearest Neighbor (KNN) and Support Vector Machine (SVM) algorithms are used for doppler radar target classification and the results are evaluated. Before classification PCA (Principal Component Analysis), LDA (Linear Discriminant Analysis), NMF (Nonnegative Matrix Factorization) and ICA (Independent Component Analysis) are implemented and applied to normalized doppler radar signals for feature extraction and dimension reduction in an efficient way. These techniques transform the input vectors, which are the normalized doppler radar signals, to another space. The effects of the implementation of these feature extraction algoritms and the use of the repetitions in doppler radar target signals on the doppler radar target classification performance are studied.
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Aulich, Graydon D. "Development of a bistatic Doppler radar system using an incoherent transmitter." Thesis, University of Reading, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.284452.

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Carlsson, Andreas. "A comparison between wind measurements with doppler weather radar and rawinds." Thesis, Uppsala universitet, Meteorologiska institutionen, 1996. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-392766.

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Comparisons between wind measurement with doppler weather radar and wind measurement with rawinds in different weather situations is done. The study is made in a statistical way with some comparable parameters as outcome. The importance of the weather and different weather situation’s effect on the results are discussed, both in form of the winds accuracy and the probability of getting any wind at all as outcome. The study shows that wind measurement with doppler radar at lower elevations not has so good accuracy, but it becomes better the higher up we measure. At the same time will we lose a lot of the measurements at higher levels by the reason that the reflected power is weakened very fast with the distance the transmitted ray travel.  The doppler effect is explained and the by SMHI used routine for wind measurement with radar is described. At the end of the work are some problems and disadvantages with the radar measurements and the used method discussed.
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Tomlin, Christopher Michael. "Adaptive flood forecasting using weather radar data." Thesis, Lancaster University, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.322340.

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Altube, Vázquez Patricia. "Procedures for improved weather radar data quality control." Doctoral thesis, Universitat de Barcelona, 2016. http://hdl.handle.net/10803/400398.

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Weather radar data and its downstream products are essential elements in weather surveillance and key parameters in the initialisation and validation of hydrological and meteorological models, among other downstream applications. Following the quality standards established by the European and global weather radar networking referents, the present thesis aims for the improvement of the base data quality control in the regional weather radar network operated by the Meteorological Service of Catalonia, the XRAD. This objective is accomplished through the analysis, development and implementation of new or existing procedures and algorithms for radar data quality assessment and improvement. Attending to the current radar technology and to the already implemented quality control procedures for the XRAD, the work is focused on the continuous evaluation of the radar system calibration status and on the correction of Doppler velocity data. The quality control algorithms and recommendations presented are easily translatable to any other operative weather radar networking environment. A Sun-based, fully automatic procedure for online monitoring the antenna alignment and the receiver chain calibration is adapted and operationally implemented for the XRAD. This Sun-monitoring technique was developed at the Royal Netherlands and Finnish Meteorological Institutes and is included in the quality control flow of numerous weather radar networks around the world. The method is modified for a robust detection and characterisation of solar interferences in raw data at all scan elevations, even when only data at relatively short ranges is available. The modified detection algorithm is also suitable for detecting interferences from wireless devices, which are stored for monitoring their incidence in the XRAD. The solar interferences detected, in turn, are input observations for the inversion of a two-dimensional Gaussian model that yields estimates of the calibration parameters of interest. A complete theoretical derivation of the model establishes its validity limits and provides analytical estimates of the effective solar widths directly from radar parameters. Results of application of this Sun-monitoring methodology to XRAD data reveal its ability to determine the accuracy of the antenna pointing and to detect changes in receiver calibration and radar system operation status. In order to facilitate the usage of the Sun-monitoring technique and the interpretation of its estimates, the methodology is reproduced under controlled conditions based on the distributions of solar observations collected by two of the XRAD radars. The analysis shows that the accuracy of the estimated calibration parameters is conditioned by the precision, number and distribution of the solar observations which constitute key variables that need to be controlled to ensure reliable estimates. In addition, the Sun-monitoring technique is compared under actual operative conditions with two other common techniques for quantifying the antenna azimuth and elevation pointing offsets. Pointing bias estimates gathered in a dedicated short-term campaign are studied in a direct inter- comparison of the methods that reflects the advantages and limitations in each case. The analysis of the bias estimates reported by the methods in the course of a one-year period reveals that the performance of the techniques depends on the antenna position at the time of the measurement. After this study, a reanalysis of the Sun-monitoring method results is proposed, which allows to additionally quantify the antenna pedestal levelling error. Finally, a post-processing, spatial image filtering algorithm for identification and correction of unfolding errors in dual-PRF Doppler velocity data is proposed. The correction of these errors benefits the usage of radar velocity data in downstream applications such as wind- shear and mesocyclone detection algorithms or assimilation in numerical weather prediction models. The main strengths of the proposed algorithm, in comparison with existing correction techniques, are its robustness to the presence of clustered unfolding errors and that it can be employed independently of post-processing dealiasing algorithms. By means of simulated dual-PRF velocity fields, the correction ability of the algorithm is quantitatively analysed and discussed with particular emphasis on the correction of clustered errors. The quality improvement in real dual-PRF data brought out by the new algorithm is illustrated through application to three selected severe weather events registered by the XRAD.
Seguint els estàndards de qualitat establerts per a les xarxes de radars meteorològics de referència a nivell europeu i global, la present tesi té com a objectiu la millora del control de qualitat de les dades de la xarxa regional de radars meteorològics operada pel Servei Meteorològic de Catalunya (la XRAD). Atenent als procediments de control de qualitat ja implementats per a la XRAD, el treball es centra en l'avaluació contínua de l'estat del calibratge del sistema radar i en la correcció de les dades de velocitat Doppler. Es presenta l'adaptació i aplicació d’un procediment totalment automàtic basat en el Sol, que permet la quantificació remota dels errors d'alineació de l'antena i de calibratge en recepció del radar a la XRAD. El mètode ha estat modificat per a la detecció i caracterització robusta d'interferències solars a les dades primàries de radar. Les interferències solars són utilitzades per a la inversió d'un model físic que proporciona estimacions dels paràmetres de calibratge d'interès. L'algoritme de detecció modificat també és adequat per a la identificació d'interferències procedents de dispositius electrònics externs. Aquestes interferències són emmagatzemades per al seguiment de la seva incidència a la XRAD. La metodologia solar esmentada es modelitza en condicions controlades a partir de la distribució de les observacions solars recollides per dos dels radars de la XRAD. L'anàlisi mostra que la precisió, el nombre i la distribució de les observacions solars constitueixen variables clau que necessiten ser controlades per garantir estimacions fiables dels paràmetres de calibrage. A més, la tècnica solar es compara, sota condicions operatives reals, amb altres dues tècniques habitualment emprades per a la quantificació de l'error d'apuntament de l'antena. A partir d'aquest estudi, es proposa un nou mètode d'anàlisi de les interferències solars, el cual permet quantificar l'error d'anivellament del pedestal de l'antena. Finalment, es desenvolupa i valida un algoritme de filtrat d'imatges per a la identificació i correcció dels errors característics que es donen lloc a les dades dual-PRF de velocitat Doppler. Els punts forts de l'algoritme proposat, en comparació amb les tècniques de correcció existents, són la seva robustesa en la correció d'errors agrupats i que pot emprar- se amb independència dels algoritmes de dealiasing. La millora de la qualitat de les dades reals de velocitat s'il·lustra mitjançant l'aplicació de l’algoritme a tres episodis de temps sever enregistrats per la XRAD.
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Shtarkalev, Bogomil Iliev. "Single data set detection for multistatic Doppler radar." Thesis, University of Edinburgh, 2015. http://hdl.handle.net/1842/10556.

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The aim of this thesis is to develop and analyse single data set (SDS) detection algorithms that can utilise the advantages of widely-spaced (statistical) multiple-input multiple-output (MIMO) radar to increase their accuracy and performance. The algorithms make use of the observations obtained from multiple space-time adaptive processing (STAP) receivers and focus on covariance estimation and inversion to perform target detection. One of the main interferers for a Doppler radar has always been the radar’s own signal being reflected off the surroundings. The reflections of the transmitted waveforms from the ground and other stationary or slowly-moving objects in the background generate observations that can potentially raise false alarms. This creates the problem of searching for a target in both additive white Gaussian noise (AWGN) and highly-correlated (coloured) interference. Traditional STAP deals with the problem by using target-free training data to study this environment and build its characteristic covariance matrix. The data usually comes from range gates neighbouring the cell under test (CUT). In non-homogeneous or non-stationary environments, however, this training data may not reflect the statistics of the CUT accurately, which justifies the need to develop SDS methods for radar detection. The maximum likelihood estimation detector (MLED) and the generalised maximum likelihood estimation detector (GMLED) are two reduced-rank STAP algorithms that eliminate the need for training data when mapping the statistics of the background interference. The work in this thesis is largely based on these two algorithms. The first work derives the optimal maximum likelihood (ML) solution to the target detection problem when the MLED and GMLED are used in a multistatic radar scenario. This application assumes that the spatio-temporal Doppler frequencies produces in the individual bistatic STAP pairs of the MIMO system are ideally synchronised. Therefore the focus is on providing the multistatic outcome to the target detection problem. It is shown that the derived MIMO detectors possess the desirable constant false alarm rate (CFAR) property. Gaussian approximations to the statistics of the multistatic MLED and GMLED are derived in order to provide a more in-depth analysis of the algorithms. The viability of the theoretical models and their approximations are tested against a numerical simulation of the systems. The second work focuses on the synchronisation of the spatio-temporal Doppler frequency data from the individual bistatic STAP pairs in the multistatic MLED scenario. It expands the idea to a form that could be implemented in a practical radar scenario. To reduce the information shared between the bistatic STAP channels, a data compression method is proposed that extracts the significant contributions of the MLED likelihood function before transmission. To perform the inter-channel synchronisation, the Doppler frequency data is projected into the space of potential target velocities where the multistatic likelihood is formed. Based on the expected structure of the velocity likelihood in the presence of a target, a modification to the multistatic MLED is proposed. It is demonstrated through numerical simulations that the proposed modified algorithm performs better than the basic multistatic MLED while having the benefit of reducing the data exchange in the MIMO radar system.
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Books on the topic "Doppler Weather Radar Data"

1

United States. Dept. of Commerce, ed. Weather forecasting: Recommendations to address new weather processing system development risks : report to the Secretary of Commerce. Washington, D.C. (P.O. Box 37050, Washington 20013): The Office, 1996.

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Office, General Accounting. Weather forecasting: Systems architecture needed for national weather service modernization : report to Congressional requesters. Washington, D.C: The Office, 1994.

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S, Zrnić Dušan, ed. Doppler radar and weather observations. 2nd ed. San Diego: Academic Press, 1993.

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S, Zrnić Dušan, ed. Doppler radar and weather observations. 2nd ed. Mineola, N.Y: Dover Publications, 2006.

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Office, General Accounting. Weather forecasting: Unmet needs and unknown costs warrant reassessment of observing system plans : report to Congressional requesters. Washington, D.C: The Office, 1995.

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P, McKinney, Ozmen F, and Langley Research Center, eds. Analysis of Doppler radar windshear data. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1989.

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Office, General Accounting. Weather forecasting: NWS has not demonstrated that new processing system will improve mission effectiveness : report to the Chairman, Committee on Science, House of Representatives. Washington, D.C: The Office, 1996.

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Bech, Joan, and Jorge Luis Chau. Doppler radar observations: Weather radar, wind profiler, ionospheric radar, and other advanced applications. Rijeka: InTech, 2012.

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United States. National Aeronautics and Space Administration. Scientific and Technical Information Program., ed. Designing clutter rejection filters with complex coefficients for airborne pulsed Doppler weather radar. [Washington, D.C.]: National Aeronautics and Space Administration, Office of Management, Scientific and Technical Information Program, 1993.

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United States. National Aeronautics and Space Administration. Scientific and Technical Information Program., ed. Designing clutter rejection filters with complex coefficients for airborne pulsed Doppler weather radar. [Washington, D.C.]: National Aeronautics and Space Administration, Office of Management, Scientific and Technical Information Program, 1993.

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Book chapters on the topic "Doppler Weather Radar Data"

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Schlatter, T. W. "An Integrated Approach to the Display of Doppler Radar and Other Meteorological Data." In Weather Radar Networking, 316–29. Dordrecht: Springer Netherlands, 1990. http://dx.doi.org/10.1007/978-94-009-0551-1_36.

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Jiela, Qutie, Haijiang Wang, Jiaoyang He, and Debin Su. "Doppler Weather Radar Network Joint Observation and Reflectivity Data Mosaic." In Lecture Notes in Electrical Engineering, 2169–72. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-13-9409-6_263.

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Du, Jianhua, and Shenghong Wu. "Research on Numerical Weather Prediction Based on Doppler Raw Radar Data and Cloud Model." In Advances in Intelligent Systems and Computing, 507–14. New Delhi: Springer India, 2014. http://dx.doi.org/10.1007/978-81-322-1759-6_58.

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Srivastava, Kuldeep, Vivek Sinha, and Rashmi Bharadwaj. "Assimilation of Doppler Weather Radar Data Through Rapid Intermittent Cyclic (RIC) for Simulation of Squall Line Event over India and Adjoining Bangladesh." In High-Impact Weather Events over the SAARC Region, 23–34. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-10217-7_2.

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Brown, Rodger A. "Doppler Weather Radar." In Encyclopedia of Natural Hazards, 188. Dordrecht: Springer Netherlands, 2013. http://dx.doi.org/10.1007/978-1-4020-4399-4_96.

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Nichols, T. R., P. I. Joe, and C. L. Crozier. "Canada’s Operational Doppler Radar." In Weather Radar Networking, 278–85. Dordrecht: Springer Netherlands, 1990. http://dx.doi.org/10.1007/978-94-009-0551-1_31.

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Meischner, Peter, Nikolai Dotzek, Martin Hagen, and Hartmut Höller. "Understanding Severe Weather Systems Using Doppler and Polarisation Radar." In Weather Radar, 167–98. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-662-05202-0_6.

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Petrov, R., D. Stoyanov, A. Savchenko, and L. Mladenov. "A Doppler Appliance to MRL-5." In Weather Radar Networking, 286–91. Dordrecht: Springer Netherlands, 1990. http://dx.doi.org/10.1007/978-94-009-0551-1_32.

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Bacon, P. J. "Doppler Facilities for the UK Met Office." In Weather Radar Networking, 292–93. Dordrecht: Springer Netherlands, 1990. http://dx.doi.org/10.1007/978-94-009-0551-1_33.

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Illingworth, Anthony. "Improved Precipitation Rates and Data Quality by Using Polarimetric Measurements." In Weather Radar, 130–66. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-662-05202-0_5.

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Conference papers on the topic "Doppler Weather Radar Data"

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Jinlian Zhou, Ming Wei, Tao Wu, and Nan Li. "Identification of gale weather with doppler weather radar data." In 2011 International Conference on Remote Sensing, Environment and Transportation Engineering (RSETE). IEEE, 2011. http://dx.doi.org/10.1109/rsete.2011.5965731.

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Ai, Wei-hua, Chao-ling Shen, Yun-xian Huang, and Zhi-guo Chang. "A comparative study of Doppler weather radar data compression." In Education (ICCSE). IEEE, 2009. http://dx.doi.org/10.1109/iccse.2009.5228121.

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Zhang, P., H. Shu, Y. Liu, and Y. Li. "Some Techniques for Three-dimensional Doppler Weather Radar Data Processing." In 2006 IEEE International Symposium on Geoscience and Remote Sensing. IEEE, 2006. http://dx.doi.org/10.1109/igarss.2006.741.

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Zakia, Irma, Andriyan Bayu Suksmono, Mohammad Ridwan Effendi, and Wervyan Shalannanda. "Reflectivity of I-WARP Pulse-Doppler Weather Radar from Measured Data." In 2020 14th International Conference on Telecommunication Systems, Services, and Applications (TSSA). IEEE, 2020. http://dx.doi.org/10.1109/tssa51342.2020.9310812.

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Zakia, Irma, Andriyan Bayu Suksmono, Mohammad Ridwan Effendi, and Wervyan Shalannanda. "Reflectivity of I-WARP Pulse-Doppler Weather Radar from Measured Data." In 2020 14th International Conference on Telecommunication Systems, Services, and Applications (TSSA). IEEE, 2020. http://dx.doi.org/10.1109/tssa51342.2020.9310812.

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Perfetti, B., J. Zheng, and M. Kaveh. "Signal processing for wind turbine interference mitigation in Doppler weather radars: data synthesis, clutter detector performance, and spectral interpolation in range-azimuth-Doppler." In IET International Conference on Radar Systems (Radar 2012). Institution of Engineering and Technology, 2012. http://dx.doi.org/10.1049/cp.2012.1682.

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Shou, Zehui, Debin Su, Xingang Fan, Yuelin Liu, Xiaoyi Wang, and Weiguo Wang. "Assimilating Doppler Weather Radar Data for a Hailstorm Event in Bayannur, China." In 2019 International Conference on Meteorology Observations (ICMO). IEEE, 2019. http://dx.doi.org/10.1109/icmo49322.2019.9025869.

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Foord, R., and J. M. Vaughan. "Wind Sensing Using a Conical Scanned CO2 Laser Doppler System." In Coherent Laser Radar. Washington, D.C.: Optica Publishing Group, 1987. http://dx.doi.org/10.1364/clr.1987.wd2.

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This paper describes low level wind measurements using the ground prototype of the LATAS CO2 laser velocimeter in conjunction with a conical scanner. Measurements of wind speed and direction as a function of altitude up to a few hundred metres are obtained under different weather conditions demonstrating the potential for rapid acquisition and display of local wind field data. A measurement giving clear indication of directional wind shear is shown together with cloud effects.
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Werner, Ch, J. Streicher, and G. Wildgruber. "Representativity of a single line-of-sight wind component." In Coherent Laser Radar. Washington, D.C.: Optica Publishing Group, 1991. http://dx.doi.org/10.1364/clr.1991.wd3.

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One of the most important inputs to numerical weather forecasting, climatology etc., that is still lacking is a full global set of three-dimensional wind data. A Doppler lidar holds promise of being able to help rectify this deficiency by monitoring winds globally in cloud free areas.
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Vinther, Morten Loell, Torbjørn Eide, Aurelia Paraschiv, and Dickon Bonvik-Stone. "Recent Progress in Applying Advanced Computation Methods to Radar-Based Wave Measurements." In Offshore Technology Conference. OTC, 2021. http://dx.doi.org/10.4043/31049-ms.

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Abstract High quality environmental data are critical for any offshore activity relying on data insights to form appropriate planning and risk mitigation routines under challenging weather conditions. Such data are the most significant driver of future footprint reduction in offshore industries, in terms of costs savings, as well as operational safety and efficiency, enabled through ease of data access for all relevant stakeholders. This paper describes recent advancements in methods used by a dual-footprint Pulse-Doppler radar to provide accurate and reliable ocean wave height measurements. Achieved improvements during low wind weather conditions are presented and compared to data collected from other sources such as buoys and acoustic doppler wave and current profiler (ADCP) or legacy. The study is based on comparisons of recently developed algorithms applied to different data sets recorded at various sites, mostly covering calm weather conditions.
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Reports on the topic "Doppler Weather Radar Data"

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Chiswell, S., and R. Buckley. ASSIMILATION OF DOPPLER RADAR DATA INTO NUMERICAL WEATHER MODELS. Office of Scientific and Technical Information (OSTI), January 2009. http://dx.doi.org/10.2172/971333.

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Sashegyi, Keith D. Shipboard Data Assimilation System/Doppler Radar. Fort Belvoir, VA: Defense Technical Information Center, September 2000. http://dx.doi.org/10.21236/ada610257.

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Zhao, Allen. Improved Doppler Radar/Satellite Data Assimilation. Fort Belvoir, VA: Defense Technical Information Center, September 2009. http://dx.doi.org/10.21236/ada531653.

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Zhao, Allen. Improved Doppler Radar/Satellite Data Assimilation. Fort Belvoir, VA: Defense Technical Information Center, September 2008. http://dx.doi.org/10.21236/ada533027.

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Zhao, Allen. Improved Doppler Radar/Satellite Data Assimilation. Fort Belvoir, VA: Defense Technical Information Center, September 2007. http://dx.doi.org/10.21236/ada541360.

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Barker, Edward H., and Keith D. Sashegyi. Shipboard Data Assimilation System/Doppler Radar. Fort Belvoir, VA: Defense Technical Information Center, September 1999. http://dx.doi.org/10.21236/ada630755.

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Zhao, Allen. Shipboard Data Assimilation System/Doppler Radar. Fort Belvoir, VA: Defense Technical Information Center, September 2006. http://dx.doi.org/10.21236/ada631042.

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Zhao, Allen. Data Assimilation for Doppler Radar/Shipboard Systems. Fort Belvoir, VA: Defense Technical Information Center, September 2003. http://dx.doi.org/10.21236/ada630182.

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Xu, Qin, and Richard J. Doviak. Doppler Radar and Analysis for Climate Model Verification and Numerical Weather Prediction. Fort Belvoir, VA: Defense Technical Information Center, May 1998. http://dx.doi.org/10.21236/ada353493.

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Nehrkorn, Thomas, James Hegarty, and Thomas M. Hamill. Real-Data Tests of a Single-Doppler Radar Assimilation System. Fort Belvoir, VA: Defense Technical Information Center, June 1994. http://dx.doi.org/10.21236/ada286638.

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