Robert D. Palmer

Doppler radars are susceptible to range–velocity ambiguities resulting from the use of uniformly spaced sequences of transmitted pulses. Dual-PRF batch scanning strategies, commonly employed in operational weather radars, mitigate some ambiguities by transmitting two pulse trains with different repetition frequencies in sequence. However, they still suffer from significant velocity ambiguities beyond the unambiguous range of the sequence with the shorter pulse repetition time. In this letter, the Velocity Recovery and Dealiasing (VRAD) algorithm is adapted for batch-mode scans to recover obscured Doppler velocities. The method blends data from both pulse sequences by dealiasing and filling censored regions using long-PRT velocities. Experimental results on WSR-88D data collected during Hurricane Ian demonstrate substantial improvements in velocity coverage; a correlation coefficient exceeding 0.99 between recovered long- and pre-existing short-PRT velocities (where available) was obtained to validate consistency of recovered velocities. These results highlight the potential to enhance operational Doppler velocity fields in dual-PRF batch scans.

Pointed herein are differences between turbulence measurements by radars with conventional pencil bean antennas and electronically steering Phased Array Radar (PAR) antennas. Differences are caused by the shape and orientation of the beam cross section on phased array antenna. These depend on the pointing direction and everywhere except at broadside the beam cross section is approximately elliptical. A formalism applicable to pencil beams of circular cross section is extended to elliptic beam cross sections. For lateral dimensions of the radar resolution volume larger than its range extent an approximate formula is suggested for computing the eddy dissipation rate ε. A field of ε^1/3 indicative of turbulence affecting aircraft and obtained with a digital PAR is presented as well as values along a radial pointing at a 41.5° elevation.

This study investigates the implementation of adaptive digital beamforming (DBF) for polarimetric phased array radar (PAR), focusing on the calibration challenges and performance benefits for weather observations. Traditional Fourier-based beamforming methods, while widely used, suffer from fixed and limited spatial resolution and susceptibility to contamination, particularly in the presence of strong reflectivity gradients or clutter. On the other hand, adaptive DBF using the Capon method offers improved data quality by minimizing contamination but requires careful calibration, particularly for maintaining the integrity of polarimetric measurements. This work presents a framework that includes beam pattern calibration and noise estimation to enable accurate polarimetric variable estimation. Simulation results demonstrate the advantages of the Capon method over Fourier processing in terms of resolution and clutter mitigation, while NEXRAD data serve as a basis for more realistic simulations highlighting the method’s practical applicability. These findings provide a critical step toward the application of adaptive DBF in polarimetric phased array weather radar.

This article presents advancements in the development and validation of the Radio Frequency Sonde (RFSonde) [1], an unmanned aerial system (UAS) specifically designed for in-situ antenna pattern measurements of fielded weather radar systems. The RFSonde employs a 3-axis gimbal stabilization system, ensuring accurate mechanical polarization alignment of the probe during flights for scanning antenna patterns. The methodology was tested using two operational phased array radar (PAR) systems—Horus [2] and the Advanced Technology Demonstrator (ATD) [3]. A simulation framework was developed to assess critical measurement uncertainties arising from factors such as GNSS positional errors, environmental wind effects, and polarization tracking accuracy. Measured and simulated antenna pattern comparisons allowed us to establish UAS requirements for accurate weather radar calibration. This study also quantified transmit co-polar beam matching biases in differential reflectivity (ΔZ_DR,tx) and co-polar correlation coefficient (ρ_hv,tx). Combined with prior work measuring transmitted differential phase (ϕ_DP,tx) [4], these results demonstrate that the RFSonde can reliably achieve stringent calibration requirements under realistic field conditions. Meeting such calibration standards is essential for accurate weather radar products, such as quantitative precipitation estimation (QPE). Thus, this work validates the RFSonde as a practical, precise, and scalable solution for routine weather radar calibration and validation, potentially enhancing the reliability of radar-based meteorological observations.

Radars are essential for monitoring rapidly intensifying severe weather phenomena, enabling timely warnings and informed decision-making to protect lives and property. The WSR-88D radar network, consisting of more than 160 polarimetric radars across the United States, has been recognized as one of the most reliable and highest-quality weather radar networks in the world but is reaching end-of-life in the coming decades. To confront this challenge, phased array radars (PARs) with their superior capability for rapid and flexible scanning are being considered as a replacement technology. Among PAR architectures, fully digital systems provide advanced capabilities and also are expected to reduce maintenance requirements and operational costs through software reconfigurability. Furthermore, fully digital PARs, which provide access to element-level In-phase (I) and Quadrature-phase (Q) data, can perform scans with increased flexibility with the potential for adaptive beamforming. However, they can generate an enormous volume of data, presenting a significant challenge for operational use. To address this “data challenge,” this study examines the impacts of I/Q data quantization, both uniform and non-uniform, on spectral moments and polarimetric variables using data from “Horus,” the first fully digital phased array weather radar developed at the Advanced Radar Research Center (ARRC) at the University of Oklahoma (OU). The findings demonstrate that non-uniform quantization has the potential to reduce data size while maintaining data quality and dynamic range.

Phased array radar represents the future of polarimetric weather surveillance, driven by the need for high-temporal resolution observations to improve storm monitoring and precipitation analysis. This study presents a novel technique for generating multiple simultaneous transmit beams using phase-only beamforming weights. Unlike previous methods, this approach generates multiple narrow and separate transmit peaks, minimizing sensitivity loss (compared to broadened beams) and improving sidelobe isolation. Bézier surfaces are used to parametrize the element-level phases across the array, producing a smooth distribution with reduced optimization complexity. The article outlines the theoretical formulation, demonstrates simulation results of the phase-only optimization, and validates the method with experimental data collected with the fully digital Horus phased array radar. Validation using a point target revealed precise beam pointing with angular accuracy within 0.1° , and measurements during a severe weather event resulted in high-quality polarimetric measurements. Scatterplots comparing the Horus radar data to that from the KCRI (WSR-88D) radar show high correlations (e.g., reflectivity correlation coefficient of 0.91), underscoring the accuracy and reliability of the approach. These findings highlight the potential of multiple simultaneous beams for next-generation weather radar systems, enabling high-temporal resolution observations and advanced capabilities for weather surveillance.

Weather radars play a crucial role in understanding severe storms. Through detailed and accurate observations, these sophisticated instruments significantly enhance the prediction and quantification of impactful weather events. Current operational weather radars, such as the WSR-88D in the USA, utilize dish antennas and operate at an S -band wavelength. These large (∼8.5 m) mechanically driven antennas are inherently limited in temporal resolution of the necessary volumetric measurements. Consequently, researchers have been exploring the potential of phased array technology for weather applications. This article provides a brief overview of the technology currently used for weather observations and envisions a future where advanced phased array radars meet and exceed the expectations of the broader weather community.

Fully digital phased array radars (PAR) enable rapid scanning of severe weather phenomena with high temporal and spatial resolution through adaptive beamforming and other advanced methods. An important challenge with such systems is the transferring, processing, and storing of the vast amount of data that can be produced, especially if element-level data are needed. Therefore, reduction of I/Q data size should be investigated when considering fully digital arrays for both scientific and operational needs. In this research, the effects I/Q linear quantization on polarimetric weather radar products has been examined. Among other effects, the results show that pulse compression effectively reduces quantization noise while maintaining the peak storm structure. As expected, negative quantization effects increase with lower signal-to-noise ratio (SNR).