ZDR Bias Research Articles

Identifying ZDR Columns in Radar Data with the Hotspot Technique

Abstract A novel differential reflectivity (ZDR) column detection method, the hotspot technique, has been developed. Utilizing constant altitude plan projection indicators (CAPPI) of ZDR, reflectivity, and a proxy for circular depolarization ratio at the height of the −10°C isotherm, the method identifies the location of the base of the ZDR column rather than the entire ZDR column depth. The new method is compared to two other existing ZDR column detection methods and shown to be an improvement in regions where there is a ZDR bias. Significance Statement Thunderstorm updrafts are the area of a storm where precipitation grows, electrification is initiated, and tornadoes may form. Therefore, accurate detection and quantification of updraft properties using weather radar data is of great importance for assessing a storm’s damage potential in real time. Current methods to automatically detect updraft areas, however, are error-prone due to common deficiencies in radar measurements. We present a novel algorithmic approach to identify storm updrafts that eliminates some of the known shortcomings of existing methods. In the future, our method could be used to develop new hail detection algorithms, or to improve short-term weather forecasting models.

Tornado Formation and Intensity Prediction Using Polarimetric Radar Estimates of Updraft Area

AbstractA sample of 198 supercells are investigated to determine if a radar proxy for the area of the storm midlevel updraft may be a skillful predictor of imminent tornado formation and/or peak tornado intensity. A novel algorithm, a modified version of the Thunderstorm Risk Estimation from Nowcasting Development via Size Sorting (TRENDSS) algorithm is used to estimate the area of the enhanced differential radar reflectivity factor (ZDR) column in Weather Surveillance Radar – 1988 Doppler data; the ZDR column area is used as a proxy for the area of the midlevel updraft. The areas of ZDR columns are compared for 154 tornadic supercells and 44 non-tornadic supercells, including 30+ supercells with tornadoes rated EF1, EF2, and EF3; nine supercells with EF4+ tornadoes also are analyzed. It is found that (i) at the time of their peak 0-1 km azimuthal shear, non-tornadic supercells have consistently small (< 20 km2) ZDR column areas while tornadic cases exhibit much greater variability in areas, and (ii) at the time of tornadogenesis, EF3+ tornadic cases have larger ZDR column areas than tornadic cases rated EF1/2. In addition, all nine violent tornadoes sampled have ZDR column areas > 30 km2 at the time of tornadogenesis. However, only weak positive correlation is found between ZDR column area and both radar-estimated peak tornado intensity and maximum tornado path width. Planned future work focused on mechanisms linking updraft size and tornado formation and intensity is summarized and the use of the modified TRENDSS algorithm, which is immune to ZDR bias and thus ideal for real-time operational use, is emphasized.

Monitoring the differential reflectivity and receiver calibration of the German polarimetric weather radar network

Abstract. It is a challenge to calibrate differential reflectivity ZDR to within 0.1–0.2 dB uncertainty for dual-polarization weather radars that operate 24∕7 throughout the year. During operations, a temperature sensitivity of ZDR larger than 0.2 dB over a temperature range of 10 ∘C has been noted. In order to understand the source of the observed ZDR temperature sensitivity, over 2000 dedicated solar box scans, two-dimensional scans of 5∘ azimuth by 8∘ elevation that encompass the solar disk, were made in 2018 from which horizontal (H) and vertical (V) pseudo antenna patterns are calculated. This assessment is carried out using data from the Hohenpeißenberg research radar which is identical to the 17 operational radar systems of the German Meteorological Service (Deutscher Wetterdienst, DWD). ZDR antenna patterns are calculated from the H and V patterns which reveal that the ZDR bias is temperature dependent, changing about 0.2 dB over a 12 ∘C temperature range. One-point-calibration results, where a test signal is injected into the antenna cross-guide coupler outside the receiver box or into the low-noise amplifiers (LNAs), reveal only a very weak differential temperature sensitivity (<0.02 dB) of the receiver electronics. Thus, the observed temperature sensitivity is attributed to the antenna assembly. This is in agreement with the NCAR (National Center for Atmospheric Research) S-Pol (S-band polarimetric radar) system, where the primary ZDR temperature sensitivity is also related to the antenna assembly (Hubbert, 2017). Solar power measurements from a Canadian calibration observatory are used to compute the antenna gain and to validate the results with the operational DWD monitoring results. The derived gain values agree very well with the gain estimate of the antenna manufacturer. The antenna gain shows a quasi-linear dependence on temperature with different slopes for the H and V channels. There is a 0.6 dB decrease in gain for a 10 ∘C temperature increase, which directly relates to a bias in the radar reflectivity factor Z which has not been not accounted for previously. The operational methods used to monitor and calibrate ZDR for the polarimetric DWD C-band weather radar network are discussed. The prime sources for calibrating and monitoring ZDR are birdbath scans, which are executed every 5 min, and the analysis of solar spikes that occur during operational scanning. Using an automated ZDR calibration procedure on a diurnal timescale, we are able to keep ZDR bias within the target uncertainty of ±0.1 dB. This is demonstrated for data from the DWD radar network comprising over 87 years of cumulative dual-polarization radar operations.

Continuous Monitoring of Differential Reflectivity Bias for C-Band Polarimetric Radar Using Online Solar Echoes in Volume Scans

The measurement error of differential reflectivity (ZDR), especially systematic ZDR bias, is a fundamental issue for the application of polarimetric radar data. Several calibration methods have been proposed and applied to correct ZDR bias. However, recent studies have shown that ZDR bias is time-dependent and can be significantly different on two adjacent days. This means that the frequent monitoring of ZDR bias is necessary, which is difficult to achieve with existing methods. As radar sensitivity has gradually been enhanced, large amounts of online solar echoes have begun to be observed in volume-scan data. Online solar echoes have a high frequency, and a known theoretical value of ZDR (0 dB) could thus allow the continuous monitoring of ZDR bias. However, online solar echoes are also affected by low signal-to-noise ratio and precipitation attenuation for short-wavelength radar. In order to understand the variation of ZDR bias in a C-band polarimetric radar at the Nanjing University of Information Science and Technology (NUIST-CDP), we analyzed the characteristics of online solar echoes from this radar, including the daily frequency of occurrence, the distribution along the radial direction, precipitation attenuation, and fluctuation caused by noise. Then, an automatic method based on online solar echoes was proposed to monitor the daily ZDR bias of the NUIST-CDP. In the proposed method, a one-way differential attenuation correction for solar echoes and a maximum likelihood estimation using a Gaussian model were designed to estimate the optimal daily ZDR bias. The analysis of three months of data from the NUIST-CDP showed the following: (1) Online solar echoes occurred very frequently regardless of precipitation. Under the volume-scan mode, the average number of occurrences was 15 per day and the minimum number was seven. This high frequency could meet the requirements of continuous monitoring of the daily ZDR bias under precipitation and no-rain conditions. (2) The result from the proposed online solar method was significantly linearly correlated with that from the vertical pointing method (observation at an elevation angle of 90°), with a correlation coefficient of 0.61, suggesting that the proposed method is feasible. (3) The day-to-day variation in the ZDR bias was relatively large, and 32% of such variations exceeded 0.2 dB, meaning that a one-time calibration was not representative in time. Accordingly, continuous calibration will be necessary. (4) The ZDR bias was found to be largely influenced by the ambient temperature, with a large negative correlation between the ZDR bias and the temperature.

Bragg Scatter Detection by the WSR-88D. Part II: Assessment of ZDR Bias Estimation

AbstractClear-air Bragg scatter (CABS) is a refractivity gradient return generated by turbulent eddies that operational Weather Surveillance Radar-1988 Doppler (WSR-88D) systems can detect. The randomly oriented nature of the eddies results in a differential reflectivity (ZDR) value near 0 dB, and thus CABS can be used as an assessment of ZDR calibration in the absence of excessive contamination from precipitation or biota. An automated algorithm to estimate ZDR bias from CABS was developed by the Radar Operations Center and can be used to assess the calibration quality of the dual-polarized WSR-88D fleet. This technique supplements existing ZDR bias assessment tools, especially the use of other external targets, such as light rain and dry snow.The estimates of ZDR bias from CABS using a 1700–1900 UTC time window were compared to estimates from the light rain and dry snow methods. Output from the automated CABS algorithm had approximately the same amount of bias reported as the light rain and dry snow estimates (within ±0.1 dB). As the 1700–1900 UTC time window appeared too restrictive, a modified version of the algorithm was tested to detect CABS diurnally on a volume-by-volume basis (continuous monitoring). Continuous monitoring resulted in a two- to fourfold increase in the number of days with CABS detections. Results suggest estimates from CABS are viable for many sites throughout the year and provide an important addition to existing bias estimation techniques.

Bragg Scatter Detection by the WSR-88D. Part I: Algorithm Development

AbstractStudies have shown that echo returns from clear-air Bragg scatter (CABS) can be used to detect the height of the convective boundary layer and to assess the systematic differential reflectivity (ZDR) bias for a radar site. However, these studies did not use data from operational Weather Surveillance Radar-1988 Doppler (WSR-88D) or data from a large variety of sites. A new algorithm to automatically detect CABS from any operational WSR-88D with dual-polarization capability while excluding contamination from precipitation, biota, and ground clutter is presented here. Visual confirmation and tests related to the sounding parameters’ relative humidity slope, refractivity gradient, and gradient Richardson number are used to assess the algorithm. Results show that automated detection of CABS in operational WSR-88D data gives useful ZDR bias information while omitting the majority of contaminated cases. Such an algorithm holds potential for radar calibration efforts and Bragg scatter studies in general.

Evaluation of the Self-Consistency Principle for Calibration of the CASA Radar Network Using Properties of the Observed Precipitation Medium

A network of four weather radars was deployed as part of the Center for Collaborative and Adaptive Sensing of the Atmosphere (CASA). The radars operate at the X-band frequency and are capable of polarimetric measurements. The rainfall polarimetric self-consistency principle for absolute calibration is evaluated and applied to the CASA radars' data to estimate any bias in the reflectivity (Z) measurements. Moreover, prior to the application of the self-consistency principle, bias error correction of differential reflectivity (ZDR) measurements is required. Two different approaches were evaluated for ZDR bias correction, the dry aggregated snow approach and the light rain approach. Results of ZDR calibration show an accuracy of 0.2 dB or better in bias estimation for the two events analyzed when both methods are compared. Moreover, results show a calibration accuracy of 0.6 dB or better for the Z bias estimated using the self-consistency principle. For verification of results, Z bias estimates from the self-consistency principle are compared with Z bias estimated from the comparison between the CASA X-band and the two nearby WSR-88D S-band radars' data. Comparison of the two approaches shows a difference in the Z bias estimation of 0.61 dB or better, which validates the use of the self-consistency principle in rainfall for the absolute radar calibration of the CASA radars. Results show that the self-consistency principle provides a means to estimate bias errors in the radar power measurements from a specific observed medium with a set of space-time characteristics that are not taken into account in the radar hardware relative calibration.

Polarimetric Radar–Based Estimates of Spatial Variability in Characteristic Sizes of Raindrops in Stratiform Rainfall

AbstractPolarimetric X-band radar measurements of differential reflectivity ZDR in stratiform rainfall were used for retrieving mean mass-weighted raindrop diameters Dm and estimating their spatial variability δDm at different scales. The ZDR data were calibrated and corrected for differential attenuation. The results revealed greater variability in Dm for larger spatial scales. Mean values of δDm were respectively around 0.32–0.34, 0.28–0.30, and 0.24–0.26 mm at scales of 20, 10, and 4.5 km, which are representative of footprints of various spaceborne sensors. For a given spatial scale, δDm decreases when the mean value of Dm increases. At the 20-km scale the decreasing trend exhibits a factor-of-1.7 decrease of δDm when the average Dm changes from 1 to 2 mm. Estimation data suggest that this trend diminishes as the spatial scale decreases. Measurement noise and other uncertainties preclude accurate estimations of Dm variability at smaller spatial scales because for many data points estimated variability values are equal to or less than the expected retrieval errors. Even though they are important for retrievals of absolute values of Dm, the details of the drop shape–size relation did not significantly affect estimates of size spatial variability. The polarization cross coupling in simultaneous transmission–simultaneous receiving measurement mode presents another limiting factor for accurate estimations of Dm. This factor, however, was not too severe in estimations of the size variability. There are indications that tuning the differential attenuation correction scheme might balance off some possible cross-coupling ZDR bias if differential phase accumulation is less than approximately 40°.

Modeling, Error Analysis, and Evaluation of Dual-Polarization Variables Obtained from Simultaneous Horizontal and Vertical Polarization Transmit Radar. Part II: Experimental Data

Abstract In this second article in a two-part work, the biases of weather radar polarimetric variables from simultaneous horizontally and vertically transmit (SHV) data are investigated. The biases are caused by cross coupling of the simultaneously transmitted vertical (V) and horizontal (H) electric fields. There are two primary causes of cross coupling: 1) the nonzero mean canting angle of the propagation medium (e.g., canted ice crystals) and 2) antenna polarization errors. Given herein are experimental data illustrating both bias sources. In Part I, a model is developed and used to quantify cross coupling and its impact on polarization measurements. Here, in Part II, experimental data from the National Center for Atmospheric Research’s (NCAR’s) S-band dual-polarimetric Doppler radar (S-Pol) and the National Severe Storms Laboratory’s polarimetric Weather Surveillance Radar-1988 Doppler (WSR-88D), KOUN, are used to illustrate biases in differential reflectivity (Zdr). The S-Pol data are unique: both SHV data and fast alternating H and V transmit (FHV) data are gathered in close time proximity, and thus the FHV data provide “truth” for the SHV data. Specifically, the SHV Zdr bias in rain caused by antenna polarization errors is clearly demonstrated by the data. This has not been shown previously in the literature.

Differential Reflectivity Calibration for Operational Radars

Abstract The conventional technique for calibrating Zdr using natural scatterers is based on vertical-looking observations. In some operational weather radar, this method is not applicable because of mechanical constraints that prohibit vertical measurement or choices in the scanning strategies. A technique for calibrating Zdr based on properties of rain returns is proposed and analyzed. The technique is based on an examination of properties of differential reflectivity measurements collected at increasing elevations. Differential reflectivity observed in rain decreases with increasing elevation due to the increasing view angle. Using the hypothesis of uniform microphysical profiles below the bright band, deviations of the profile of differential reflectivity with elevation with respect to the theoretical profile can be used to detect and quantify the presence of a bias on differential reflectivity. To apply this concept in the presence of a nonuniform microphysical profile, the contribution of vertical changes in microphysics to Zdr variation in height is also accounted for. An error parameter associated with the estimated Zdr bias can be used as a quality indicator of the bias estimation; it allows definition of a criterion based on a threshold of root-mean-square error that permits acceptance or rejection of a Zdr bias estimation obtained with the proposed method. The technique is demonstrated using data collected by an operational weather radar at Arpa Piemonte (Italy) and evaluated using independent disdrometer measurement. Results show that under certain conditions discussed in the paper, this method can provide Zdr calibration within an accuracy of 0.1 dB.

Calibration of Dual-Polarization Radar in the Presence of Partial Beam Blockage

Abstract In the presence of partial beam blockage (PBB), weather radar measurements can experience significant bias that directly compromises the accuracy of the hydrologic applications. Techniques for the calibration of the radar reflectivity factor Z and differential reflectivity ZDR, measured with dual-polarization weather radars in the presence of partial beam obstruction, are examined in this paper. The proposed ZDR calibration technique utilizes radar measurements of ZDR in light rain and dry aggregated snow at unblocked and blocked elevations. This calibration technique was tested for the National Severe Storms Laboratory’s (NSSL’s) Cimarron radar that suffers from PBB, and a polarimetric prototype of the Weather Surveillance Radar-1988 Doppler (WSR-88D) that does not experience PBB. Results indicate that the ZDR bias that is associated with PBB can be calibrated with an accuracy of 0.2–0.3 dB, provided that the dataset is sufficiently large. Calibration of Z in the presence of PBB is based on the idea of self-consistency among Z, ZDR, and the specific differential phase KDP in rain. The self-consistency calibration of Z from the Cimarron radar is performed following an area–time integral method. Integration is partitioned into small azimuthal sectors to assess the azimuthal modulation of the Z bias. The suggested technique is validated by direct comparisons of reflectivity factors that are measured by the Cimarron radar and the unobstructed operational WSR-88D radar. It is shown that the azimuthal modulation of Z that is caused by PBB is well captured, and the accuracy of the Z calibration is within 2–3 dB.

Antenna Pattern Analysis and Measurements for Multiparameter Radars

Abstract Measuring the full polarization matrix using a research radar requires knowledge of the complex (i.e., amplitude and phase) antenna pattern to properly correct for bias errors in the measurements. However, generally only power patterns are available for analysis. Techniques are presented for obtaining bounds on the system differential reflectivity ZDR bias and the integrated cross-polarization ratio. A method for use of the phase shift between pulses to simultaneously estimate the differential phase and the radial velocity over the full Nyquist interval is described. NCAR's CP-2 10-cm antenna patterns with different horizontal and vertical polarization sidelobes were matched by rotating the feed support struts to be aligned on the diagonals so no preferential blockage occurred. The matched antenna patterns show much improved ZDR measurements in strong reflectivity gradients. The CP-2 3-cm antenna patterns were shown to be axially symmetric and typical of a well-designed, unblocked parabolic refle...