Showing papers by "Guifu Zhang published in 2021"

Towards the Next Generation Operational Meteorological Radar

Abstract: This article summarizes research and risk reduction that will inform acquisition decisions regarding NOAA’s future national operational weather radar network. A key alternative being evaluated is polarimetric phased-array radar (PAR). Research indicates PAR can plausibly achieve fast, adaptive volumetric scanning, with associated benefits for severe-weather warning performance. We assess these benefits using storm observations and analyses, observing system simulation experiments, and real radar-data assimilation studies. Changes in the number and/or locations of radars in the future network could improve coverage at low altitude. Analysis of benefits that might be so realized indicates the possibility for additional improvement in severe-weather and flash-flood warning performance, with associated reduction in casualties. Simulations are used to evaluate techniques for rapid volumetric scanning and assess data quality characteristics of PAR. Finally, we describe progress in developing methods to compensate for polarimetric variable estimate biases introduced by electronic beam-steering. A research-to-operations (R2O) strategy for the PAR alternative for the WSR-88D replacement network is presented.

Polarimetric Phased Array Weather Radar Data Quality Evaluation Through Combined Analysis, Simulation, and Measurements

Abstract: This letter combines a time-domain modeling and simulation method for evaluating the impacts of system modules on polarimetric data quality of phased array weather radars with both theoretical analysis and actual measurements. In the presented phased array radar system simulator (PASIM), the distributed weather returns are modeled by randomly distributed scatterers, and Next-Generation Radar (NEXRAD) Level-II data or user-defined weather scenarios are utilized as weather truth fields. Based on a specially designed patch element, a dual-polarization phased array mobile demonstration system (Ten Panel Demonstrator or TPD) is simulated. In addition, the biases of differential reflectivity, copolar correlation coefficient, and differential phase along beam direction away from the broadside in principal plane and nonprincipal plane are used as data quality metrics. Moreover, theoretical analysis, system simulation, and actual TPD proof of concept measurements in a stratiform precipitation and a convective precipitation are presented, respectively, then similarities and discrepancies between simulations and measurements are compared and explained.

Design of a Cylindrical Crossed Dipole Phased Array Antenna for Weather Surveillance Radars

Abstract: We present a cylindrical dual-polarization phased array antenna for weather surveillance radars that features high isolation, matched copolar beams, low sidelobe levels, and adaptive null steering. We present a crossed dipole antenna element to replace the patch antenna on the currently deployed cylindrical polarimetric phased array radar (CPPAR). The crossed dipole element offers suppressed surface wave and lower coupling between adjacent elements of an array. As a result, we achieved lower backlobe and sidelobe levels, and a higher match between copolar beams of CPPAR compared to the currently deployed multi-layer patch antenna. Further reduction of the sidelobe level and adaptive null steering are obtained using a modified particle swarm optimization. The proposed null steering mitigates the interference among the four concurrent beams of a cylindrical phased array radar. The improvement in CPPAR radiation characteristics has been verified by comparing the presented crossed dipole antenna’s radiation patterns and the existing aperture coupled patch antenna. The proposed crossed dipole phased array can benefit national weather radar networks to provide accurate multiparameter measurements enabling reliable observation of severe weather phenomena.

Initial Observations With Electronic and Mechanical Scans Using a Cylindrical Polarimetric Phased Array Radar

Abstract: This letter presents initial weather measurements with a cylindrical polarimetric phased array radar (CPPAR) demonstrator developed at The University of Oklahoma. The overall system specifications, waveform design, beam pattern measurement, and beam-to-beam calibration of the CPPAR demonstrator are presented. The weather observations of convective precipitation are provided, employing a single-beam mechanical scan and commutating beam electronic scan. Measurement results from these two scan modes are compared, and the error statistics are derived and discussed. A new feature of the CPPAR commutating beam electronic scan in clutter detection is observed and explained.

Snow Particle Size Distribution From a 2-D Video Disdrometer and Radar Snowfall Estimation in East China

Abstract: In this study, as part of an effort to study snowfall characteristics and quantify winter precipitation in East China, we investigated the microphysical properties of snowfall, including size, shape, density, and terminal velocity using a 2-D video disdrometer (2-DVD) and a weighing precipitation gauge in Nanjing (NJ), East China during the winters of 2015–2019. We obtained larger snow density and terminal velocity values than those reported in the literature for this region. Higher snow density could account for higher snowflake terminal velocity, after removing the effects of observation altitude and surface temperature. We then fit the snow particle size distributions (PSDs) to the gamma model and explored the interrelationships among the model parameters and snowfall rate (SR). The relationship between radar reflectivity factor ( $Z_{e}$ ) and SR was derived based on snow PSD measurements and the snow density relation. Using this $Z_{e}-\mathrm {SR}$ relationship, the estimated liquid-equivalent SRs are obtained from S-band NJ radar data collected during several snowfall events. Radar-inferred SRs showed reasonable agreement with those measured on the ground, with a mean absolute error of 16% for the collected snowfall events in NJ.

Parameterized Forward Operators for Simulation and Assimilation of Polarimetric Radar Data with Numerical Weather Predictions

Abstract: Many weather radar networks in the world have now provided polarimetric radar data (PRD) that have the potential to improve our understanding of cloud and precipitation microphysics, and numerical weather prediction (NWP). To realize this potential, an accurate and efficient set of polarimetric observation operators are needed to simulate and assimilate the PRD with an NWP model for an accurate analysis of the model state variables. For this purpose, a set of parameterized observation operators are developed to simulate and assimilate polarimetric radar data from NWP model-predicted hydrometeor mixing ratios and number concentrations of rain, snow, hail, and graupel. The polarimetric radar variables are calculated based on the T-matrix calculation of wave scattering and integrations of the scattering weighted by the particle size distribution. The calculated polarimetric variables are then fitted to simple functions of water content and volume-weighted mean diameter of the hydrometeor particle size distribution. The parameterized PRD operators are applied to an ideal case and a real case predicted by the Weather Research and Forecasting (WRF) model to have simulated PRD, which are compared with existing operators and real observations to show their validity and applicability. The new PRD operators use less than one percent of the computing time of the old operators to complete the same simulations, making it efficient in PRD simulation and assimilation usage.

Assimilation of Polarimetric Radar Data in Simulation of a Supercell Storm with a Variational Approach and the WRF Model

Abstract: Polarimetric radar data (PRD) have potential to be used in numerical weather prediction (NWP) models to improve convective-scale weather forecasts. However, thus far only a few studies have been undertaken in this research direction. To assimilate PRD in NWP models, a forward operator, also called a PRD simulator, is needed to establish the relation between model physics parameters and polarimetric radar variables. Such a forward operator needs to be accurate enough to make quantitative comparisons between radar observations and model output feasible, and to be computationally efficient so that these observations can be easily incorporated into a data assimilation (DA) scheme. To address this concern, a set of parameterized PRD simulators for the horizontal reflectivity, differential reflectivity, specific differential phase, and cross-correlation coefficient were developed. In this study, we have tested the performance of these new operators in a variational DA system. Firstly, the tangent linear and adjoint (TL/AD) models for these PRD simulators have been developed and checked for the validity. Then, both the forward operator and its adjoint model have been built into the three-dimensional variational (3DVAR) system. Finally, some preliminary DA experiments have been performed with an idealized supercell storm. It is found that the assimilation of PRD, including differential reflectivity and specific differential phase, in addition to radar radial velocity and horizontal reflectivity, can enhance the accuracy of both initial conditions for model hydrometer state variables and ensuing model forecasts. The usefulness of the cross-correlation coefficient is very limited in terms of improving convective-scale data analysis and NWP.