scholarly journals Multipatterns of the National Weather Radar Testbed Mitigate Clutter Received via Sidelobes

2011 ◽  
Vol 28 (3) ◽  
pp. 401-409 ◽  
Author(s):  
Guifu Zhang ◽  
Yinguang Li ◽  
Richard J. Doviak ◽  
Dave Priegnitz ◽  
John Carter ◽  
...  
Keyword(s):  
Standard Deviation ◽  
Phased Array ◽  
Weather Radar ◽  
Main Lobe ◽  
Mean Power ◽  
Sample Mean ◽  
Ground Clutter ◽  
Phased Array Radar ◽  
Weather Observations

Abstract The phased-array radar (PAR) of the National Weather Radar Testbed (NWRT) has a unique hybrid (mechanical and electrical) azimuth scan capability, allowing weather observations with different antenna patterns. Observations show the standard deviation of the sample mean power of weather echoes received through the main lobe of a set of squinted beams is less than the clutter received via sidelobes. This then allows use of a multipattern technique to cancel sidelobe echoes from moving scatterers, echoes that cannot be filtered with a ground-clutter canceler. Although the multipattern technique was developed to cancel clutter received through sidelobes, results show clutter from objects moving within the beam can also be canceled.

scholarly journals Adaptive Nullforming to Mitigate Ground Clutter on the National Weather Radar Testbed Phased Array Radar

2016 ◽  
Vol 54 (3) ◽  
pp. 1282-1291 ◽  
Author(s):  
Christopher D. Curtis ◽  
Mark Yeary ◽  
John L. Lake
Keyword(s):  
Phased Array ◽  
Weather Radar ◽  
Ground Clutter ◽  
Phased Array Radar

Dual-polarization challenges in weather radar requirements for multifunction phased array radar

2013 ◽  
Author(s):  
Caleb Fulton ◽  
Jeff Herd ◽  
Shaya Karimkashi ◽  
Guifu Zhang ◽  
Dusan Zrnic
Keyword(s):  
Phased Array ◽  
Weather Radar ◽  
Dual Polarization ◽  
Phased Array Radar

Adaptive Range Oversampling to Achieve Faster Scanning on the National Weather Radar Testbed Phased-Array Radar

2011 ◽  
Vol 28 (12) ◽  
pp. 1581-1597 ◽  
Author(s):  
Christopher D. Curtis ◽  
Sebastián M. Torres
Keyword(s):  
Signal Processing ◽  
Phased Array ◽  
Matched Filter ◽  
Meteorological Data ◽  
Weather Radar ◽  
Meteorological Variable ◽  
Seamless Integration ◽  
Computational Burden ◽  
Phased Array Radar ◽  
Spatial Coverage

Abstract This paper describes a real-time implementation of adaptive range oversampling processing on the National Weather Radar Testbed phased-array radar. It is demonstrated that, compared to conventional matched-filter processing, range oversampling can be used to reduce scan update times by a factor of 2 while producing meteorological data with similar quality. Adaptive range oversampling uses moment-specific transformations to minimize the variance of meteorological variable estimates. An efficient algorithm is introduced that allows for seamless integration with other signal processing functions and reduces the computational burden. Through signal processing, a new dimension is added to the traditional trade-off triangle that includes the variance of estimates, spatial coverage, and update time. That is, by trading an increase in computational complexity, data with higher temporal resolution can be collected and the variance of estimates can be improved without affecting the spatial coverage.

High-Temporal-Resolution Capabilities of the National Weather Radar Testbed Phased-Array Radar

2011 ◽  
Vol 50 (3) ◽  
pp. 579-593 ◽  
Author(s):  
Pamela L. Heinselman ◽  
Sebastián M. Torres
Keyword(s):  
Temporal Resolution ◽  
Phased Array ◽  
Weather Radar ◽  
High Temporal Resolution ◽  
Data Archiving ◽  
Phased Array Radar ◽  
Control Interface ◽  
Trade Offs ◽  
Address Data ◽  
Processing Techniques

Abstract Since 2007 the advancement of the National Weather Radar Testbed Phased-Array Radar (NWRT PAR) hardware and software capabilities has been supporting the implementation of high-temporal-resolution (∼1 min) sampling. To achieve the increase in computational power and data archiving needs required for high-temporal-resolution sampling, the signal processor was upgraded to a scalable, Linux-based cluster with a distributed computing architecture. The development of electronic adaptive scanning, which can reduce update times by focusing data collection on significant weather, became possible through functionality added to the radar control interface and real-time controller. Signal processing techniques were implemented to address data quality issues, such as artifact removal and range-and-velocity ambiguity mitigation, absent from the NWRT PAR at its installation. The hardware and software advancements described above have made possible the development of conventional and electronic scanning capabilities that achieve high-temporal-resolution sampling. Those scanning capabilities are sector- and elevation-prioritized scanning, beam multiplexing, and electronic adaptive scanning. Each of these capabilities and related sampling trade-offs are explained and demonstrated through short case studies.

scholarly journals Rapid-Scan Radar Observations of an Oklahoma Tornadic Hailstorm Producing Giant Hail

2018 ◽  
Vol 33 (5) ◽  
pp. 1263-1282 ◽  
Author(s):  
Arthur Witt ◽  
Donald W. Burgess ◽  
Anton Seimon ◽  
John T. Allen ◽  
Jeffrey C. Snyder ◽  
...  
Keyword(s):  
Phased Array ◽  
Rotational Velocity ◽  
Weather Radar ◽  
Dual Polarization ◽  
Radar Observations ◽  
Rapid Scan ◽  
Phased Array Radar ◽  
X Band ◽  
Low Altitude ◽  
Rapid Scanning

Abstract Rapid-scan radar observations of a supercell that produced near-record size hail in Oklahoma are examined. Data from the National Weather Radar Testbed Phased Array Radar (PAR) in Norman, Oklahoma, are used to study the overall character and evolution of the storm. Data from the nearby polarimetric KOUN WSR-88D and rapid-scanning X-band polarimetric (RaXPol) mobile radar are used to study the evolution of low- to midaltitude dual-polarization parameters above two locations where giant hailstones up to 16 cm in diameter were observed. The PAR observation of the supercell’s maximum storm-top divergent outflow is similar to the strongest previously documented value. The storm’s mesocyclone rotational velocity at midaltitudes reached a maximum that is more than double the median value for similar observations from other storms producing giant hail. For the two storm-relative areas where giant hail was observed, noteworthy findings include 1) the giant hail occurred outside the main precipitation core, in areas with low-altitude reflectivities of 40–50 dBZ; 2) the giant hail was associated with dual-polarization signatures consistent with past observations of large hail at 10-cm wavelength, namely, low ZDR, low ρHV, and low KDP; 3) the giant hail fell along both the northeast and southwest edges of the primary updraft at ranges of 6–10 km from the updraft center; and 4) with the exception of one isolated report, the giant hail fell to the northeast and northwest of the large tornado and the parent mesocyclone.

scholarly journals Phased-Array Radar System Simulator (PASIM): Development and Simulation Result Assessment

2019 ◽  
Vol 11 (4) ◽  
pp. 422 ◽  
Author(s):  
Zhe Li ◽  
Sudantha Perera ◽  
Yan Zhang ◽  
Guifu Zhang ◽  
Richard Doviak
Keyword(s):  
Data Quality ◽  
Pulse Compression ◽  
Phased Array ◽  
Weather Radar ◽  
Radar System ◽  
Quality Analysis ◽  
Convective Precipitation ◽  
Error Statistics ◽  
Phased Array Radar ◽  
The Impact

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.

Rapid Sampling of Severe Storms by the National Weather Radar Testbed Phased Array Radar

2008 ◽  
Vol 23 (5) ◽  
pp. 808-824 ◽  
Author(s):  
Pamela L. Heinselman ◽  
David L. Priegnitz ◽  
Kevin L. Manross ◽  
Travis M. Smith ◽  
Richard W. Adams
Keyword(s):  
Temporal Resolution ◽  
Phased Array ◽  
Weather Radar ◽  
Radar Data ◽  
Rapid Identification ◽  
High Temporal Resolution ◽  
Convective Storms ◽  
Rapid Sampling ◽  
Phased Array Radar ◽  
Frequent Sampling

Abstract A key advantage of the National Weather Radar Testbed Phased Array Radar (PAR) is the capability to adaptively scan storms at higher temporal resolution than is possible with the Weather Surveillance Radar-1988 Doppler (WSR-88D): 1 min or less versus 4.1 min, respectively. High temporal resolution volumetric radar data are a necessity for rapid identification and confirmation of weather phenomena that can develop within minutes. The purpose of this paper is to demonstrate the PAR’s ability to collect rapid-scan volumetric data that provide more detailed depictions of quickly evolving storm structures than the WSR-88D. Scientific advantages of higher temporal resolution PAR data are examined for three convective storms that occurred during the spring and summer of 2006, including a reintensifying supercell, a microburst, and a hailstorm. The analysis of the reintensifying supercell (58-s updates) illustrates the capability to diagnose the detailed evolution of developing and/or intensifying areas of 1) low-altitude divergence and rotation and 2) rotation through the depth of the storm. The fuller sampling of the microburst’s storm life cycle (34-s updates) depicts precursors to the strong surface outflow that are essentially indiscernible in the WSR-88D data. Furthermore, the 34-s scans provide a more precise sampling of peak outflow. The more frequent sampling of the hailstorm (26-s updates) illustrates the opportunity to analyze storm structures indicative of rapid intensification, the development of hail aloft, and the onset of the downdraft near the surface.

scholarly journals An Integrated Approach to Weather Radar Calibration and Monitoring Using Ground Clutter and Satellite Comparisons

2019 ◽  
Vol 36 (1) ◽  
pp. 17-39 ◽  
Author(s):  
Valentin Louf ◽  
Alain Protat ◽  
Robert A. Warren ◽  
Scott M. Collis ◽  
David B. Wolff ◽  
...  
Keyword(s):  
Standard Deviation ◽  
Prediction Models ◽  
Weather Prediction ◽  
Weather Radar ◽  
Integrated Approach ◽  
The Self ◽  
Absolute Calibration ◽  
Ground Clutter ◽  
Radar Calibration ◽  
Self Consistency

AbstractThe stability and accuracy of weather radar reflectivity calibration are imperative for quantitative applications, such as rainfall estimation, severe weather monitoring and nowcasting, and assimilation in numerical weather prediction models. Various radar calibration and monitoring techniques have been developed, but only recently have integrated approaches been proposed, that is, using different calibration techniques in combination. In this paper the following three techniques are used: 1) ground clutter monitoring, 2) comparisons with spaceborne radars, and 3) the self-consistency of polarimetric variables. These techniques are applied to a C-band polarimetric radar (CPOL) located in the Australian tropics since 1998. The ground clutter monitoring technique is applied to each radar volumetric scan and provides a means to reliably detect changes in calibration, relative to a baseline. It is remarkably stable to within a standard deviation of 0.1 dB. To obtain an absolute calibration value, CPOL observations are compared to spaceborne radars on board TRMM and GPM using a volume-matching technique. Using an iterative procedure and stable calibration periods identified by the ground echoes technique, we improve the accuracy of this technique to about 1 dB. Finally, we review the self-consistency technique and constrain its assumptions using results from the hybrid TRMM–GPM and ground echo technique. Small changes in the self-consistency parameterization can lead to 5 dB of variation in the reflectivity calibration. We find that the drop-shape model of Brandes et al. with a standard deviation of the canting angle of 12° best matches our dataset.

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