Search Results

You are looking at 1 - 9 of 9 items for :

  • Author or Editor: J. C. Hubbert x
  • Journal of Atmospheric and Oceanic Technology x
  • All content x
Clear All Modify Search
J. C. Hubbert

Abstract

Temporal differential reflectivity bias variations are investigated using the National Center for Atmospheric Research (NCAR) S-band dual-polarization Doppler radar (S-Pol). Using data from the Multi-Angle Snowflake Camera-Ready (MASCRAD) Experiment, S-Pol measurements over extended periods reveal a significant correlation between the ambient temperature at the radar site and the bias. Using radar scans of the sun and the ratio of cross-polar powers, the components of the radar that cause the variation of the bias are identified. It is postulated that the thermal expansion of the antenna is likely the primary cause of the observed bias variation. The cross-polar power (CP) calibration technique, which is based on the solar and cross-polar power measurements, is applied to data from the Plains Elevated Convection at Night (PECAN) field project. The bias from the CP technique is compared to vertical-pointing bias measurements, and the uncertainty of the bias estimates is given. An algorithm is derived to correct the radar data for the time- and temperature-varying bias. Bragg scatter measurements are used to corroborate the CP technique bias measurements.

Full access
J. C. Hubbert and V. N. Bringi

Abstract

Effects of three-body scattering on reflectivity signatures at S and C bands can be seen on the back side of large reflectivity storm cores that contain hail. The fingerlike protrusions of elevated reflectivity have been termed flare echoes or “hail spikes.” Three-body scattering occurs when radiation from the radar scattered toward the ground is scattered back to hydrometeors, which then scatter some of the radiation back to the radar. Three-body scatter typically causes differential reflectivity to be very high at high elevations and to be negative at lower elevations at the rear of the storm core. This paper describes a model that can simulate the essential features of the three-body scattering that has been observed in hailstorms. The model also shows that three-body scatter can significantly affect the polarimetric Z DR (differential reflectivity) radar signatures in hailshafts at very low elevation and thus is a possible explanation of the frequently reported negative Z DR signatures in hailshafts near ground.

Full access
J. C. Hubbert and V. N. Bringi

Abstract

A polarimetric radar covariance matrix model is described to study the behavior of the co-to-cross covariances in precipitation. The 2 × 2 propagation matrix with attenuation, differential attenuation, and differential phase is coupled to the backscatter matrix leading to a propagation-modified covariance matrix model. System polarization errors are included in this model as well. This model is used to study the behavior of the magnitude and phase of the co-to-cross covariances and the linear depolarization ratio (LDR) in rainfall. It is shown that the model predictions are consistent with data collected with the Colorado State University (CSU)–University of Chicago–Illinois State Water Survey (CHILL) radar in intense rainfall. A method is also given for estimating the system polarization errors from covariance matrix data collected in intense rainfall.

Full access
J. C. Hubbert, M. Dixon, S. M. Ellis, and G. Meymaris

Abstract

Real-time ground-clutter identification and subsequent filtering of clutter-contaminated data is addressed in this two-part paper. Part I focuses on the identification, modeling, and simulation of S-band ground-clutter echo. A new clutter identification parameter, clutter phase alignment (CPA), is presented. CPA is a measure primarily of the phase variability of the in-phase and quadrature-phase time series samples for a given radar resolution volume. CPA is also a function of amplitude variability of the time series. It is shown that CPA is an excellent discriminator of ground clutter versus precipitation echoes. A typically used weather model, time series simulator is shown to inadequately describe experimentally observed CPA. Thus, a new technique for the simulation of ground-clutter echo is developed that better predicts the experimentally observed CPA. Experimental data from the Denver Next Generation Weather Radar (NEXRAD) at the Denver, Colorado, Front Range Airport (KFTG), and NCAR’s S-band dual-polarization Doppler radar (S-Pol) are used to illustrate CPA. In Part II, CPA is used in a fuzzy logic algorithm for improved clutter identification.

Full access
J. C. Hubbert, M. Dixon, and S. M. Ellis

Abstract

The identification and mitigation of anomalous propagation (AP) and normal propagation (NP) ground clutter is an ongoing problem in radar meteorology. Scatter from ground-clutter targets routinely contaminates radar data and masks weather returns causing poor data quality. The problem is typically mitigated by applying a clutter filter to all radar data, but this also biases weather data at near-zero velocity. Modern radar processors make possible the real-time identification and filtering of AP clutter. A fuzzy logic algorithm is used to distinguish between clutter echoes and precipitation echoes and, subsequently, a clutter filter is applied to those radar resolution volumes where clutter is present. In this way, zero-velocity weather echoes are preserved while clutter echoes are mitigated. Since the radar moments are recalculated from clutter-filtered echoes, the underlying weather echo signatures are revealed, thereby significantly increasing the visibility of weather echo. This paper describes the fuzzy logic algorithm, clutter mitigation decision (CMD), for clutter echo identification. A new feature field, clutter phase alignment (CPA), is introduced and described. A detailed discussion of CPA is given in Part I of this paper. The CMD algorithm is illustrated with experimental data from the Denver Next Generation Weather Radar (NEXRAD) at the Denver, Colorado, Front Range Airport (KFTG); and NCAR’s S-band dual-polarization Doppler radar (S-Pol).

Full access
J. C. Hubbert, S. M. Ellis, M. Dixon, and G. Meymaris

Abstract

In this two-part paper the biases of polarimetric variables from simultaneous horizontally and vertically transmitted (SHV) data are investigated. Here, in Part I, a radar-scattering model is developed and antenna polarization errors are investigated and estimated. In , experimental data from the National Center for Atmospheric Research S-band dual-polarization Doppler radar (S-Pol) and the National Severe Storms Laboratory polarimetric Weather Surveillance Radar-1988 Doppler (WSR-88D) radar, KOUN, are used to illustrate biases in differential reflectivity (Z dr). The biases in the SHV polarimetric variables are caused by cross coupling of the horizontally (H) and vertically (V) polarized signals. The cross coupling is caused by the following two primary sources: 1) the nonzero mean canting angle of the propagation medium and 2) antenna polarization errors. The biases are strong functions of the differential propagation phase (ϕ dp) and the phase difference between the H and V transmitted field components. The radar-scattering model developed here allows for the evaluation of biases caused by cross coupling as a function of ϕ dp, with the transmission phase difference as a parameter. Also, antenna polarization errors are estimated using solar scan measurements in combination with estimates of the radar system’s linear depolarization ratio (LDR) measurement limit. Plots are given that show expected biases in SHV Z dr for various values of the LDR system’s limit.

Full access
J. C. Hubbert, V. N. Bringi, and D. Brunkow

Abstract

A procedure for calibration of the radar covariance matrix for the Colorado State University–University of Chicago–Illinois State Water Survey (CSU–CHILL) radar and S-Band Dual-Polarization Doppler Radar (S-Pol) systems is described. Two relative magnitudes and three offset phases are determined that allow for the calibrated covariance matrix to be constructed. Precise calibration of Z dr is accomplished with use of only sun calibration measurements and crosspolar power measurements from precipitation. No assumptions about the precipitation medium are made. It is also shown how to determine the co-to-cross phase offsets for the CSU–CHILL radar from precipitation data. A novel method for calculating linear depolarization ratio (LDR) that is effective in low signal-to-noise-ratio regions and that requires no knowledge of the background noise temperature is given. This technique utilizes the cross-to-cross covariances. CSU–CHILL data from the Severe Thunderstorm Electrification and Precipitation Study (STEPS) are used to illustrate the LDR estimator and the Z dr calibration technique.

Full access
J. C. Hubbert, S. M. Ellis, M. Dixon, and G. Meymaris

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 , 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 Z dr bias in rain caused by antenna polarization errors is clearly demonstrated by the data. This has not been shown previously in the literature.

Full access
Alexander V. Ryzhkov, Dusan S. Zrnic, John C. Hubbert, V. N. Bringi, J. Vivekanandan, and Edward A. Brandes

Abstract

Preliminary analysis of all components of the polarimetric radar covariance matrix for precipitation measured with the NCAR S-band dual-polarization Doppler radar (S-Pol) and the Colorado State University–University of Chicago–Illinois State Water Survey (CSU–CHILL) radars is presented. Radar reflectivity at horizontal polarization Z h, differential reflectivity Z DR, linear depolarization ratio LDR, specific differential phase K DP, cross-correlation coefficient |ρ hv|, and two co-cross-polar correlation coefficients, ρ xh and ρ xv, have been measured and examined for two rain events: the 14 August 1998 case in Florida and the 8 August 1998 case in Colorado.

Examination of the coefficients ρ xh and ρ xv is the major focus of the study. It is shown that hydrometeors with different types of orientation can be better delineated if the coefficients ρ xh and ρ xv are used. Rough estimates of the raindrop mean canting angles and the rms width of the canting angle distribution are obtained from the co-cross-polar correlation coefficients in combination with other polarimetric variables.

Analysis of the two cases indicates that the raindrop net canting angles averaged over the propagation paths near the ground in typical convective cells do not exceed 2.5°. Nonetheless, the mean canting angles in individual radar resolution volumes in rain can be noticeably higher. Although the net canting angle for individual convective cells can deviate by a few degrees from zero, the average over a long propagation path along several cells is close to zero, likely because canting angles in different cells vary in sign.

The rms width of the canting angle distribution in rain is estimated to vary mainly between 5° and 15° with the median value slightly below 10°.

Full access