Volume Coverage Pattern Research Articles

Extended Polarimetric Observations of Chaff Using the WSR-88D Weather Radar Network

Military chaff is a metallic, fibrous radar countermeasure that is released by aircraft and rockets for diversion and masking of targets. It is often released across the United States for training purposes, and, due to its resonant cut lengths, is often observed on the S-band Weather Surveillance Radar – 1988 Doppler (WSR-88D) network. Efforts to identify and characterize chaff and other non-meteorological targets algorithmically require a statistical understanding of the targets. Previous studies of chaff characteristics have provided important information that has proven to be useful for algorithmic development. However, recent changes to the WSR-88D processing suite have allowed for a vastly extended range of differential reflectivity, a prime topic of previous studies on chaff using weather radar. Motivated by these changes, a new dataset of 2.8 million range gates of chaff from 267 cases across the United States is analyzed. With a better spatiotemporal representation of cases compared to previous studies, new analyses of height dependence, as well as changes in statistics by volume coverage pattern are examined, along with an investigation of the new “full” range of differential reflectivity. A discussion of how these findings are being used in WSR-88D algorithm development is presented, specifically with a focus on machine learning and separation of different target types.

Real-Time Rainfall Forecasts Based on Radar Reflectivity during Typhoons: Case Study in Southeastern Taiwan.

This study developed a real-time rainfall forecasting system that can predict rainfall in a particular area a few hours before a typhoon’s arrival. The reflectivity of nine elevation angles obtained from the volume coverage pattern 21 Doppler radar scanning strategy and ground-weather data of a specific area were used for accurate rainfall prediction. During rainfall prediction and analysis, rainfall retrievals were first performed to select the optimal radar scanning elevation angle for rainfall prediction at the current time. Subsequently, forecasting models were established using a single reflectivity and all elevation angles (10 prediction submodels in total) to jointly predict real-time rainfall and determine the optimal predicted values. This study was conducted in southeastern Taiwan and included three onshore weather stations (Chenggong, Taitung, and Dawu) and one offshore weather station (Lanyu). Radar reflectivities were collected from Hualien weather surveillance radar. The data for a total of 14 typhoons that affected the study area in 2008–2017 were collected. The gated recurrent unit (GRU) neural network was used to establish the forecasting model, and extreme gradient boosting and multiple linear regression were used as the benchmarks. Typhoons Nepartak, Meranti, and Megi were selected for simulation. The results revealed that the input data set merged with weather-station data, and radar reflectivity at the optimal elevation angle yielded optimal results for short-term rainfall forecasting. Moreover, the GRU neural network can obtain accurate predictions 1, 3, and 6 h before typhoon occurrence.

Pseudo RHI Software Developing for Dual-polarization Weather Radar CAPPI Observation Variables

RHI (range height indicator) is one type of operation and display for radar detection. Pseudo RHI is applying other observation data without RHI operation to generate RHI looks like echoes. Data processing method with interpolation and filter, computer display technology with coordinate transformation and pseudo color, and software development with Python for pseudo RHI are described in this paper. It is shown that this processing is useful for easily analysis and application of weather radar VCP (volume coverage pattern) observation data in vertical distributions of targets echoes for weather nowcast and severe weather warning.

Investigation of observational error sources in multi-Doppler-radar three-dimensional variational vertical air motion retrievals

Abstract. Multi-Doppler-radar network observations have been used in different configurations over the last several decades to conduct three-dimensional wind retrievals in mesoscale convective systems. Here, the impacts of the selected radar volume coverage pattern (VCP), the sampling time for the VCP, the number of radars used, and the added value of advection correction on the retrieval of the vertical air motion in the upper part of convective clouds are examined using the Weather Research and Forecasting (WRF) model simulation, the Cloud Resolving Model Radar SIMulator (CR-SIM), and a three-dimensional variational multi-Doppler-radar retrieval technique. Comparisons between the model truth (i.e., WRF kinematic fields) and updraft properties (updraft fraction, updraft magnitude, and mass flux) retrieved from the CR-SIM-generated multi-Doppler-radar field are used to investigate these impacts. The findings are that (1) the VCP elevation strategy and sampling time have a significant effect on the retrieved updraft properties above 6 km in altitude; (2) 2 min or shorter VCPs have small impacts on the retrievals, and the errors are comparable to retrievals using a snapshot cloud field; (3) increasing the density of elevation angles in the VCP appears to be more effective to reduce the uncertainty than an addition of data from one more radar, if the VCP is performed in 2 min; and (4) the use of dense elevation angles combined with an advection correction applied to the 2 min VCPs can effectively improve the updraft retrievals, but for longer VCP sampling periods (5 min) the value of advection correction is challenging. This study highlights several limiting factors in the retrieval of upper-level vertical velocity from multi-Doppler-radar networks and suggests that the use of rapid-scan radars can substantially improve the quality of wind retrievals if conducted in a limited spatial domain.

Radar Performance Monitoring Using the Angular Width of the Solar Image

Abstract A method for the operational monitoring of the weather radar antenna mechanics and signal processing is presented. The method is based on the analysis of sun signals in the polar volume data produced during the operational scanning of weather radars. Depending on the hardware of the radar, the volume coverage pattern, the season, and the latitude of the radar, several tens of sun hits are found per day. The method is an extension of that for determining the weather radar antenna pointing and for monitoring the receiver stability and the differential reflectivity offset. In the method the width of the sun image in elevation and in azimuth is analyzed from the data, together with the center point position and the total power, analyzed in the earlier methods. This paper describes how the width values are obtained in the majority of cases without affecting the quality of the position and power values. Results from the daily analysis reveal signal processing features and failures that are difficult to find out otherwise in weather data. Moreover, they provide a tool for monitoring the stability of the antenna system, and hence the method has great potential for routine monitoring of radar signal processing and the antenna mechanics. Hence, it is recommended that the operational solar analysis be extended into the analysis of the width.

Improved Doppler Velocity Dealiasing for Radar Data Assimilation and Storm-Scale Vortex Detection

The Doppler velocity dealiasing technique based on alias-robust VAD and variational (AR-Var) analyses developed at the National Severe Storms Laboratory for radar data quality control and assimilation is further improved in its two-step procedures: the reference check in the first step and the continuity check in the second step. In the first step, the alias-robust variational analysis is modified adaptively and used in place of the alias-robust velocity-azimuth display (VAD) analysis for all scan modes (rather than solely the WSR-88D volume coverage pattern 31 with the Nyquist velocityvNreduced below 12 m s−1and the TDWR Mod80 withvNreduced below 15 m s−1), so more raw data can pass the stringent threshold conditions used by the reference check in the first step. This improves the dealiased data coverage without false dealiasing to better satisfy the high data quality standard required by radar data assimilation. In the second step, new procedures are designed and added to the continuity check to increase the dealiased data coverage over storm-scale areas threatened by intense mesocyclones and their generated tornados. The performances of the improved dealiasing technique versus the existing techniques are exemplified by the results obtained for tornadic storms scanned by the operational KTLX radar in Oklahoma.

Exploring Impacts of Rapid-Scan Radar Data on NWS Warning Decisions

Abstract Rapid-scan weather radars, such as the S-band phased array radar at the National Weather Radar Testbed in Norman, Oklahoma, improve precision in the depiction of severe storm processes. To explore potential impacts of such data on forecaster warning decision making, 12 National Weather Service forecasters participated in a preliminary study with two control conditions: 1) when radar scan time was similar to volume coverage pattern 12 (4.5 min) and 2) when radar scan time was faster (43 s). Under these control conditions, forecasters were paired and worked a tropical tornadic supercell case. Their decision processes were observed and audio was recorded, interactions with data displays were video recorded, and the products were archived. A debriefing was conducted with each of the six teams independently and jointly, to ascertain the forecaster decision-making process. Analysis of these data revealed that teams examining the same data sometimes came to different conclusions about whether and when to warn. Six factors contributing toward these differences were identified: 1) experience, 2) conceptual models, 3) confidence, 4) tolerance of possibly missing a tornado occurrence, 5) perceived threats, and 6) software issues. The three 43-s teams issued six warnings: three verified, two did not verify, and one event was missed. Warning lead times were the following: tornado, 18.6 and 11.5 min, and severe, 6 min. The three tornado warnings issued by the three 4.5-min teams verified, though warning lead times were shorter: 4.6 and 0 min (two teams). In this case, use of rapid-scan data showed the potential to extend warning lead time and improve forecasters’ confidence, compared to standard operations.

Beam Multiplexing Using the Phased-Array Weather Radar

Abstract The recently installed S-band phased-array radar (PAR) at the National Weather Radar Testbed (NWRT) offers fast and flexible beam steering through electronic beam forming. This capability allows the implementation of a novel scanning strategy termed beam multiplexing (BMX), with the goal of providing fast updates of weather information with high statistical accuracy. For conventional weather radar the data acquisition time for a sector scan or a volume coverage pattern (VCP) can be reduced by increasing the antenna’s rotation rate to the extent that the pedestal allows. However, statistical errors of the spectral moment estimates will increase due to the fewer samples that are available for the estimation. BMX is developed to exploit the idea of collecting independent samples and maximizing the usage of radar resources. An improvement factor is introduced to quantify the BMX performance, which is defined by the reduction in data acquisition time using BMX when the same data accuracy obtained by a conventional scanning strategy is maintained. It is shown theoretically that a fast update without compromising data quality can be achieved using BMX at small spectrum widths and a high signal-to-noise ratio (SNR). Applications of BMX to weather observations are demonstrated using the PAR, and the results indicate that an average improvement factor of 2–4 can be obtained for SNR higher than 10 dB.

New WSR-88D Volume Coverage Pattern 12: Results of Field Tests

Abstract For the first time since the installation of the national network of Weather Surveillance Radar-1988 Doppler (WSR-88D), a new scanning strategy—Volume Coverage Pattern 12 (VCP 12)—has been added to the suite of scanning strategies. VCP 12 is a faster version of VCP 11 and has denser vertical sampling at lower elevation angles. This note discusses results of field tests in Oklahoma and Mississippi during 2001–03 that led to the decision to implement VCP 12. Output from meteorological algorithms for a test-bed radar using an experimental VCP were compared with output for a nearby operational WSR-88D using VCP 11 or 21. These comparisons were made for severe storms that were at comparable distances from both radars. Findings indicate that denser vertical sampling at lower elevation angles leads to earlier and longer algorithm identifications of storm cells and mesocyclones, especially those more distant from a radar.

Impact of WSR-88D Scanning Strategies on Severe Storm Algorithms

The operational meteorological community generally recognizes that the greater spatial and temporal resolution of WSR-88D volume coverage pattern (VCP) 11 is preferable to VCP 21 when using algorithms to identify severe storm characteristics. The coarser vertical sampling of storms with VCP 21 likely produces less accurate results. An experiment was conducted to investigate the comparative effects of VCPs 11 and 21. Since VCP 21 is nearly a subset of VCP 11, the appropriate elevation angles were deleted from two VCP 11 datasets to produce proxy datasets for VCP 21 (called VCP 22). Various WSR-88D operational algorithms and National Severe Storms Laboratory prototype severe storm algorithms were run on the VCP 11 and VCP 21/22 datasets. At heights above 5° elevation angle, where VCP 21/22 had missing elevation angles relative to VCP 11, the majority of algorithm parameters had different values at least 50%–70% of the time. Therefore, this study confirms that VCP 11—not VCP 21—should be used in those convective storm situations where there is a contribution to critical warning parameters from elevation angles greater than 5°.

Echo Height Measurements with the WSR-88D: Use of Data from One Versus Two Radars

Abstract The new Doppler radars of the National Weather Service (i.e., the WSR-88D radars) are operated continuously in a volume scanning mode (called Volume Coverage Pattern, VCP) with the elevation tilt angles fixed for several VCPs. Because of the fixed VCPs, the radar data can be used to determine the heights of precipitation echo features only to limits of accuracy that depend upon the elevation angles used in the VCP, the radar beamwidth, and the range of echoes. Data from adjacent WSR-88D radars, if used simultaneously, could reduce significantly the height uncertainties inherent in single radar measurements. This is illustrated for idealized situations and also for an event involving a long-lived, tornadic thunderstorm. The use of coordinated scan strategies and combined data analysis procedures for adjacent WSR-88D radars during significant thunderstorm events should be considered for operational applications.

Detection of Nonprecipitating Clouds with the WSR-88D: A Theoretical and Experimental Survey of Capabilities and Limitations

Abstract Theoretical calculations and experiments verify that the National Weather Service WSR-88D radars have the sensitivity to detect nonprecipitating clouds, but show that significant obstacles impair the generality of this cloud sensing technique. Bragg scatter from refractive index inhomogeneities can be of the same magnitude as cloud echoes under many conditions, whereupon interpretation of WSR-88D echoes can be either complicated or impossible. Moreover, problems with echoes from ground clutter and from insects, birds, and other floating debris hinder WSR-88D cloud detection capabilities, particularly at low elevation angles. To illustrate these problems WSR-88D reflectivities collected using volume coverage pattern (VCP) 21 from the months of March and October 1996 were compared with collocated reflectivities obtained from a zenith-pointing 94-GHz cloud radar located in central Pennsylvania. Coincident echo detection occurred 82% and 39% of the time, while the WSR-88D had significant detections 7...

A WSR-88D Assessment of Tropical Cyclone Outer Rainband Tornadoes

As part of the National Weather Service (NWS) Modernization and Restructuring Program, WSR-88D (NEXRAD) Doppler radar installation has been completed at each Weather Service Office in Florida. Recently, this powerful new tool provided unique opportunities for Jacksonville, Tampa Bay, and Melbourne NEXRAD Weather Service Office personnel to investigate tropical cyclone (TC) rainbands for evidence of tornadogenesis. This study provides a radar-based analysis of known tornadic mesocyclones associated with two mature tropical cyclones that were not landfalling in the vicinity of the tornado occurrence, namely, Tropical Storm Gordon (1994) and Hurricane Allison (1995). Based on successful NEXRAD sampling strategies, detailed analyses of storm-scale reflectivity and velocity signatures are conducted in the context of establishing preliminary critical criteria for use in the tornado detection and warning process. Important characteristics were found to include detection of discrete, small diameter .50 dBZ echos collocated with storm-relative rotational velocities of 6.5‐ 15 ms 2 1. Rotational features, although often subtle, were identifiable for an average of 30 min prior to tornado production, with total durations of 1‐2 h. Near the time of tornado touchdown, the core diameter of the lowlevel circulation couplets contracted to approximately 1.85 km (1 n mi), leading to an associated increase of shear across the circulation to 0.010 s 21 or greater. A comparison between the well-studied Great Plains tornadic supercell and the observed TC-tornado cells revealed a common trait of persistence. While the average depth of rotation associated with the TC-tornado cells (3.5 km) was much more shallow than their midwest counterparts, the ratio of depth of rotation to storm top were comparable. However, the shallow depth and weaker detectable rotation of the TC (tornadic) mesocyclones greatly reduced the detection capability of the current WSR-88D mesocyclone algorithm when compared to identification of traditional supercells. Based upon the analyzed data, the authors offer several recommendations to assist operational radar meteorologists with the challenging task of detecting outer rainband tornadoes. Additionally, the authors propose a new WSR-88D scan strategy (volume coverage pattern, VCP) that would provide additional low-level slices in lieu of several current upper-elevation angles. This new VCP would facilitate improved vertical sampling at lower heights where TC mesoscale circulations are most likely to be detected.