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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.

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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.

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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.

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G. K. Mather, M. J. Dixon, and J. M. de Jager

Abstract

The experimental design, analyses, and results of the first Nelspruit randomized cloud seeding experiment are described. The experiment ran for three years, commencing in October 1984, and involved the on-top seeding of new cloud turrets growing on the flanks of isolated multicellular storms using dry ice delivered from a Learjet at around the height of the −10°C isotherm. All storms were tracked by a radar operating in computer-controlled volume scan mode. A total of 169 storms were examined, of which 94 passed the selection criteria. The most important criterion was based upon a microphysical classification scheme obtained from measurements made by the instrumented Learjet. This scheme, based upon a ratio of cloud-base temperature to potential buoyancy at 500 mb, rejected those storms in which the production of precipitation via coalescence was unlikely.

A key element of the experiment was the ability to objectively track the storms using an automatic storm tracking algorithm. Storms were analyzed in terms of their track properties, some of the more important of which were storm volume, area, and rain flux. Analyses of these track properties in 10-min time intervals either side of decision time (the time the seed/no-seed decision was made) proved to be the most revealing in terms of observed changes and rates of changes in convective cloud processes. This analysis showed an almost fourfold percentage increase in radar-measured rain flux and storm area when the seeded and control storms were compared.

A confirmatory experiment was conducted in the third season. Storm track properties that showed an apparent response to seeding in each of the first two seasons were selected prior the commencement of the third season. All but one of these track properties either stayed the same or showed increases in the third season, confirming the hypothesis that there were radar-detected differences between the seeded and control storms.

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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).

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T. Loridan, E. Scherer, M. Dixon, E. Bellone, and S. Khare

Abstract

Risk-assessment systems for wind hazards (e.g., hurricanes or typhoons) often rely on simple parametric wind field formulations. They are built using extensive observations of tropical cyclones and make assumptions about wind field asymmetry. In this framework, maximum winds are always simulated to the right of the cyclone, but analysis of the Climate Forecast System Reanalysis database for the western North Pacific Ocean suggests that wind fields from cyclones undergoing extratropical transition around Japan often present features that cannot be adequately simulated under these assumptions. These “left-hand-side contribution” (LHSC) wind fields exhibit strong winds on both sides of the moving cyclone with the maximum magnitude often located to the left. Classification of cyclones in terms of their most frequent patterns reveals that 67% of cases that make a transition around Japan are dominantly LHSC. They are more likely in autumn and have more intense maximum winds. The results from this study show the need for a new approach to the modeling of transitioning wind fields in the context of risk-assessment systems.

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T. Loridan, S. Khare, E. Scherer, M. Dixon, and E. Bellone

Abstract

Probabilistic risk assessment systems for tropical cyclone hazards rely on large ensembles of model simulations to characterize cyclones tracks, intensities, and the extent of the associated damaging winds. Given the computational costs, the wind field is often modeled using parametric formulations that make assumptions that are based on observations of tropical systems (e.g., satellite, or aircraft reconnaissance). In particular, for the Northern Hemisphere, most of the damaging contribution is assumed to be from the right of the moving cyclone, with the left-hand-side winds being much weaker because of the direction of storm motion. Recent studies have highlighted that this asymmetry assumption does not hold for cyclones undergoing extratropical transitions around Japan. Transitioning systems can exhibit damaging winds on both sides of the moving cyclone, with wind fields often characterized as resembling a horseshoe. This study develops a new parametric formulation of the extratropical transition phase for application in risk assessment systems. A compromise is sought between the need to characterize the horseshoe shape while keeping the formulation simple to allow for implementation within a risk assessment framework. For that purpose the tropical wind model developed by Willoughby et al. is selected as a starting point and parametric bias correction fields are applied to build the target shape. Model calibration is performed against a set of 37 extratropical transition cases simulated using the Weather Research and Forecasting Model. This newly developed parametric model of the extratropical transition phase shows an ability to reproduce wind field features observed in the western North Pacific Ocean while using only a restricted number of input parameters.

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John C. Hubbert, James W. Wilson, Tammy M. Weckwerth, Scott M. Ellis, Mike Dixon, and Eric Loew

Abstract

The National Center for Atmospheric Research (NCAR) operates a state-of-the-art S-band dual-polarization Doppler radar (S-Pol) for the National Science Foundation (NSF). This radar has some similar and some distinguishing characteristics to the National Weather Service (NWS) operational Weather Surveillance Radar-1988 Doppler Polarimetric (WSR-88DP). One key difference is that the WSR-88DP is used for operational purposes where rapid 360° volumetric scanning is required to monitor rapid changes in storm characteristics for nowcasting and issuing severe storm warnings. Since S-Pol is used to support the NSF research community, it usually scans at much slower rates than operational radars. This results in higher resolution and higher data quality suitable for many research studies. An important difference between S-Pol and the WSR-88DP is S-Pol’s ability to use customized scan strategies including scanning on vertical surfaces ([range–height indicators (RHIs)], which are presently not done by WSR-88DPs. RHIs provide high-resolution microphysical structures of convective storms, which are central to many research studies. Another important difference is that the WSR-88DP simultaneously transmits horizontal (H) and vertical (V) polarized pulses. In contrast, S-Pol typically transmits alternating H and V pulses, which results in not only higher data quality for research but also allows for the cross-polar signal to be measured. The cross-polar signal provides estimates of the linear depolarization ratio (LDR) and the co- to cross-correlation coefficient that give additional microphysical information. This paper presents plots and interpretations of high-quality, high-resolution polarimetric data that demonstrate the value of S-Pol’s polarimetric measurements for atmospheric research.

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J. C. Hubbert, S. M. Ellis, W.-Y. Chang, S. Rutledge, and M. Dixon

Abstract

Data collected by the National Center for Atmospheric Research S-band polarimetric radar (S-Pol) during the Terrain-Influenced Monsoon Rainfall Experiment (TiMREX) in Taiwan are analyzed and used to infer storm microphysics in the ice phase of convective storms. Both simultaneous horizontal (H) and vertical (V) (SHV) transmit polarization data and fast-alternating H and V (FHV) transmit polarization data are used in the analysis. The SHV Z dr (differential reflectivity) data show radial stripes of biased data in the ice phase that are likely caused by aligned and canted ice crystals. Similar radial streaks in the linear depolarization ratio (LDR) are presented that are also biased by the same mechanism. Dual-Doppler synthesis and sounding data characterize the storm environment and support the inferences concerning the ice particle types. Small convective cells were observed to have both large positive and large negative K dp (specific differential phase) values. Negative K dp regions suggest that ice crystals are vertically aligned by electric fields. Since high |K dp| values of 0.8° km−1 in both negative and positive K dp regions in the ice phase are accompanied by Z dr values close to 0 dB, it is inferred that there are two types of ice crystals present: 1) smaller aligned ice crystals that cause the K dp signatures and 2) larger aggregates or graupel that cause the Z dr signatures. The inferences are supported with simulated ice particle scattering calculations. A radar scattering model is used to explain the anomalous radial streaks in SHV and LDR.

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Matthew R. Kumjian, Steven A. Rutledge, Roy M. Rasmussen, Patrick C. Kennedy, and Mike Dixon

Abstract

High-resolution X-band polarimetric radar data were collected in 19 snowstorms over northern Colorado in early 2013 as part of the Front Range Orographic Storms (FROST) project. In each case, small, vertically erect convective turrets were observed near the echo top. These “generating cells” are similar to those reported in the literature and are characterized by ~1-km horizontal and vertical dimensions, vertical velocities of 1–2 m s−1, and lifetimes of at least 10 min. In some cases, these generating cells are enshrouded by enhanced differential reflectivity Z DR, indicating a “shroud” of pristine crystals enveloping the larger, more isotropic particles. The anticorrelation of radar reflectivity factor at horizontal polarization Z H and Z DR suggests ongoing aggregation or riming of particles in the core of generating cells. For cases in which radiosonde data were collected, potential instability was found within the layer in which generating cells were observed. The persistence of these layers suggests that radiative effects are important, perhaps by some combination of cloud-top cooling and release of latent enthalpy through depositional and riming growth of particles within the cloud. The implications for the ubiquity of generating cells and their role as a mechanism for ice crystal initiation and growth are discussed.

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