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One pivotal factor affecting the accuracy of HF radar current measurements is the direction of arrival (DOA) estimation performance of the current signal. The beamforming technology or superresolution algorithm cannot always perform best in practical applications because of the phase errors existing in array channels. These phase errors, which cause uncertain estimation of DOA, lead to confused values in radial current maps. To solve this problem, this paper is focused on discussing the performances of two autocalibration methods using sea echoes for multifrequency high-frequency (MHF) radar current measurements. These two array calibration methods, based on maximum likelihood (ML) and multiple signal classification (MU), first seek single-DOA sea echoes and then gather them for array calibration using different cost functions. The ML and MU methods provide approximate mean phases, while the standard phase errors of the MU method are smaller. After array calibration using these two methods, the results show significant improvements in current retrievals. Comparisons between the MHF radar and ADCPs reveal that array calibration using the ML and MU methods also improves the estimation of radial currents clearly, with correlation coefficients over 0.93 and rms differences of 0.09-0.18 m s−1 at different operating frequencies and sampling locations. The performance of the bearing offset is also improved. Only small bearing offsets less than 10° exist in radial current measurements. Therefore, this paper demonstrates that array calibration is a crucial part for current measurements, especially for direction-finding HF radar. [ABSTRACT FROM AUTHOR]

A new attenuation correction method has been developed for the dual-frequency precipitation radar (DPR) on the core satellite of the Global Precipitation Measurement (GPM) mission. The new method is based on Hitschfeld and Bordan's attenuation correction method (HB method), but the relationship between the specific attenuation k and the effective radar reflectivity factor Z e ( k- Z e relationship) is modified by using the dual-frequency ratio (DFR) of Z e and the surface reference technique (SRT). Therefore, the new method is called the HB-DFR-SRT method (H-D-S method). The previous attenuation correction method, called the HB-DFR method (H-D method), results in an underestimation of precipitation rates for heavy precipitation, but the H-D-S method mitigates the negative bias by means of the SRT. When only a single-frequency measurement is available, the H-D-S method is identical to the HB-SRT method (H-S method). The attenuation correction methods were tested with a simple synthetic DPR dataset. As long as the SRT gives perfect estimates of path-integrated attenuation and the adjustment factor of the k- Z e relationship (denoted by ε) is vertically constant, the H-S method is much better than the dual-frequency methods. Tests with SRT error and vertical variation in ε showed that the H-D method was better than the H-S method for weak precipitation, whereas the H-S method was better than the H-D method for heavy precipitation. The H-D-S method did not produce the best results for both weak and heavy precipitation, but the results are stable. Quantitative evaluation should be done with real DPR measurement datasets. [ABSTRACT FROM AUTHOR]

Because of its extensive quality control procedures and uniform space-time grid, the NCEP Stage IV merged Weather Surveillance Radar-1988 Doppler (WSR-88D) radar and surface rain gauge dataset is often considered to be the best long-term gridded dataset of precipitation observations covering the contiguous United States. Stage IV accumulations are employed in a variety of applications, and while the WSR-88D systems are well suited for observing heavy rain events that are likely to affect flooding, limitations in surface radar and gauge measurements can result in missed precipitation, especially near topography and in the western United States. This paper compares hourly Stage IV observations of precipitation occurrence to collocated observations from the 94-GHz CloudSat Cloud Profiling Radar, which provides excellent sensitivity to light and frozen precipitation. Statistics from 4 yr of comparisons show that the CloudSat observes precipitation considerably more frequently than the Stage IV dataset, especially in northern states where frozen precipitation is prevalent in the cold season. The skill of Stage IV for precipitation detection is found to decline rapidly when the near-surface air temperature falls below 0°C. As a result, agreement between Stage IV and CloudSat tends to be best in the southeast, where radar coverage is good and moderate-to-heavy liquid precipitation dominates. Stage IV and CloudSat precipitation detection characteristics are documented for each of the individual river forecast centers that contribute to the Stage IV dataset to provide guidance regarding potential sampling biases that may impact hydrologic applications. [ABSTRACT FROM AUTHOR]

Lightning initiation (LI) events over Florida and Oklahoma are examined and statistically compared to understand the behavior of observed radar and infrared satellite interest fields (IFs) in the 75-min time frame surrounding LI. Lightning initiation is defined as the time of the first lightning, of any kind, generated in a cumulonimbus cloud. Geostationary Operational Environmental Satellite (GOES) infrared IFs, contoured frequency by altitude diagrams (CFADs) of radar reflectivity, and model sounding data, analyzed in concert, show the mean characteristics over time for 36 and 23 LI events over Florida and Oklahoma, respectively. CFADs indicate that radar echoes formed 60 min before Florida LI, yet Oklahoma storms exhibited a ~30-min delayed development. Large ice volumes in Florida developed from the freezing of lofted liquid hydrometeors formed by long-lived (~45 min) warm rain processes, which are mostly absent in Oklahoma. However, ice volumes developed abruptly in Oklahoma storms despite missing a significant warm rain component. GOES fields were significantly different before 30 min prior to LI between the two locations. Compared to Florida storms, lower precipitable water (PW), higher convective available potential energy, and higher 3.9- μm reflectance in Oklahoma, suggest stronger and drier updrafts producing a greater abundance of small ice particles. Somewhat larger 15-min 10.7- μm cooling rates in Oklahoma confirm stronger updrafts, while clouds in the 60-30-min pre-LI period show more IF variability (e.g., in the 6.5-10.7- μm difference). Florida storms (high PW, slower growth) offer more lead time for LI predictability, compared to Oklahoma storms (low PW, explosive growth), with defined anvils being obvious at the time of LI. [ABSTRACT FROM AUTHOR]

Polarimetric weather radars significantly enhance the capability to infer the properties of scatterers within a resolution volume. Previous studies have identified several consistently seen polarimetric signatures in supercells observed in the central United States. Nearly all of these studies used data collected by fixed-site S- and C-band radars. Because there are few polarimetric mobile radars, relatively little has been documented in high-resolution polarimetric data from mobile radars. Compared to S and C bands, there has been very limited examination of polarimetric signatures at X band. The primary focus of this paper is on one signature that has not been documented previously and one that has had little documentation at X band. The first signature, seen in at least seven supercell datasets collected by a mobile, X-band, polarimetric radar, consists of a narrow band of locally reduced reflectivity factor ZH and differential reflectivity, typically near the location where the hook echo 'attaches' to the main body of the storm echo. No consistent pattern is seen in radial velocity VR or copolar cross correlation ρHV. The small size of this feature suggests a significant heterogeneity in precipitation microphysics, the cause and impact of which are unknown. The greater resolution and the scattering differences at X band compared to other frequencies may make this feature more apparent. The second signature consists of anomalously low ρHV in areas of high ZH along the left section (relative to storm motion) of the bounded weak-echo region. Examples of other polarimetric signatures at X band are provided. [ABSTRACT FROM AUTHOR]

A simplified framework is presented for assessing the qualitative sensitivities of computed microwave properties, satellite brightness temperatures, and radar reflectivities to assumptions concerning the physical properties of ice-phase hydrometeors. Properties considered included the shape parameter μ of a gamma size distribution and the melted-equivalent mass median diameter D0, the particle density, the dielectric mixing formula, and the choice of complex index of refraction for ice. These properties are examined for selected radiometer frequencies of 18.7, 36.5, 89.0, and 150.0 GHz and radar frequencies at 2.8, 13.4, 35.6, and 94.0 GHz-consistent with existing and planned remote sensing instruments. Passive and active microwave observables of ice particles are found to be extremely sensitive to the D0 of the size distribution. Similar large sensitivities are found for variations in the ice volume fraction whenever the geometric mass median diameter exceeds approximately ⅛th of the wavelength. At 94 GHz the two-way path-integrated attenuation is potentially large for dense/compact particles. The distribution parameter μ has a comparatively weak effect on any observable: less than 1-2 K in brightness temperature and a maximum of 2.7 dB (S band only) in the effective radar reflectivity. Reversal of the roles of ice and air in the Maxwell Garnett dielectric mixing formula leads to a substantial change in both microwave brightness temperature (~10 K) and radar reflectivity (approximately 2 dB across all frequencies). The choice of the complex index of refraction of ice can produce a 3%-4% change in the brightness temperature depression. [ABSTRACT FROM AUTHOR]

Ten years of data from the Tropical Rainfall Measurement Mission satellite's Precipitation Radar (TRMM PR) show the vertical structure of tropical cyclone rainbands. Radar-echo statistics show that rainbands have a two-layered structure, with distinct modes separated by the melting layer. The ice layer is a combination of particles imported from the eyewall and ice left aloft as convective cells collapse. This layering is most pronounced in the inner region of the storm, and the layering is enhanced by storm strength. The inner-region rainbands are vertically confined by outflow from the eyewall but nevertheless are a combination of strong embedded convective cells and robust stratiform precipitation, both of which become more pronounced in stronger cyclones. Changes in rainband coverage, vertical structure, and the amount of active convection indicate a change in the nature of rainbands between the regions inward and outward of a radius of approximately 200 km. Beyond this radius, rainbands consist of more sparsely distributed precipitation that is more convective in nature than that of the inner-region rainbands, and the outer-region rainband structures are relatively insensitive to changes in storm intensity. The rainbands in both inner and outer regions are organized with respect to the environmental wind shear vector. The right-of-shear quadrants contain newer convection while in the left-of-shear quadrants the radar echoes are predominantly stratiform. This asymmetric distribution of rainband structures strengthens with environmental wind shear. Cool sea surfaces discourage rainband convection uniformly. [ABSTRACT FROM AUTHOR]

This paper describes the Collaborative Adaptive Sensing of the Atmosphere (CASA) Integrated Project 1 (IP1) weather radar network, the first distributed collaborative adaptive sensing test bed of the Engineering Research Center for Collaborative Adaptive Sensing of the Atmosphere. The radar network and radar node hardware and software architectures are described, as well as the different interfaces between the integrated subsystems. The system’s operation and radar node control and weather data flow are explained. The key features of the radar nodes are presented, as well as examples of different data products. [ABSTRACT FROM AUTHOR]

The specific differential phase Kdp is one of the important parameters measured by dual-polarization radar that is being considered for the upgrade of the current Next Generation Weather Radar (NEXRAD) system. Estimation of the specific differential phase requires computing the derivative of range profiles of the differential propagation phase. The existence of possible phase wrapping, noise, and associated fluctuation in the differential propagation phase makes the evaluation of derivatives an unstable numerical process. In this paper, a robust algorithm is presented to estimate the specific differential phase, which is able to work on wrapped phases and keep up with the spatial gradients of rainfall, to provide a high-resolution specific differential phase. [ABSTRACT FROM AUTHOR]

A method is presented by which combined S-band polarimetric weather radar and UHF wind profiler observations of precipitation can be used to extract the properties of liquid phase hydrometeors and the vertical velocity of the air through which they are falling. Doppler spectra, which contain the air motion and/or fall speed of hydrometeors, are estimated using the vertically pointing wind profiler. Complementary to these observations, spectra of rain drop size distribution (DSD) are simulated by several parameters as related to the DSD, which are estimated through the two polarimetric parameters of radar reflectivity (ZH) and differential reflectivity (ZDR) from the scanning weather radar. These DSDs are then mapped into equivalent Doppler spectra (fall speeds) using an assumed relationship between the equivolume drop diameter and the drop’s terminal velocity. The method is applied to a set of observations collected on 11 March 2007 in central Oklahoma. In areas of stratiform precipitation, where the vertical wind motion is expected to be small, it was found that the fall speeds obtained from the spectra of the rain DSD agree well with those of the Doppler velocity estimated with the profiler. For those cases when the shapes of the Doppler spectra are found to be similar in shape but shifted in velocity, the velocity offset is attributed to vertical air motion. In convective rainfall, the Doppler spectra of the rain DSD and the Doppler velocity can exhibit significant differences owing to vertical air motions together with atmospheric turbulence. Overall, it was found that the height dependencies of Doppler spectra measured by the profiler combined with vertical profiles of Z, ZDR, and the cross correlation (ρHV) as well as the estimated spectra of raindrop physical terminal fall speeds from the polarimetric radar provide unique insight into the microphysics of precipitation. Vertical air motions (updrafts/downdrafts) can be estimated using such combined measurements. [ABSTRACT FROM AUTHOR]

The clutter present in the Doppler spectra of atmospheric targets can be removed by using polarimetry. The purpose is to suppress the Doppler velocity bins where spectral polarimetric parameters have atypical values. This procedure largely improves profiles of moments and polarimetric parameters of atmospheric targets. Several spectral polarimetric clutter-reduction techniques, which are based on thresholding and intended for real-time processing, are discussed in this paper. A new method, the double spectral linear depolarization ratio clutter-suppression technique, is proposed. Very satisfactory performances are obtained with this method, which can be used in the full range of elevations (0°–90°). Spectral polarimetric clutter-suppression techniques for real-time processing were studied for the S-band high-resolution Transportable Atmospheric Radar (TARA) profiler. For this study, precipitation, cloud, and clear-air scattering are considered examples of atmospheric echoes. After successful testing in 2008, the double spectral linear depolarization ratio filter was implemented in the real-time processing of the X-band scanning drizzle radar (IDRA). [ABSTRACT FROM AUTHOR]

A method is proposed to retrieve raindrop shape–size relations from the radar measurements of reflectivity factor Zh, differential reflectivity Zdr, and specific differential phase Kdp at S band. This procedure is obtained using a domain defined by the two variables Kdp/Zh and Zdr where the drop size distribution (DSD) variability is collapsed onto a line and any variation is essentially due to the drop shape variability. To obtain information on the raindrop shape–size relation underlying a set of radar observations, this domain is studied in conjunction with another domain describing the relation between the drop axial ratio (or shape) and its equivolumetric diameter. Using an initial drop shape and choosing a set of DSDs described by a normalized gamma model, polarimetric radar measurements are produced by simulation. An averaged curve of Kdp/Zh versus Zdr is obtained and compared with the same curve obtained from the radar data. By changing the initial axial ratio relation, a procedure of minimization between the two curves is developed to derive the underlying drop shape–size relation governing the radar measurements under consideration. Three sets of radar data collected in different climatic regions are analyzed to evaluate whether there is a unique shape–size relation. [ABSTRACT FROM AUTHOR]

Polarimetric weather radars offer the promise of accurate rainfall measurements by including polarimetric measurements in rainfall estimation algorithms. Questions still remain on how accurately polarimetric measurements represent the parameters of the raindrop size distribution (DSD). In particular, this study propagates polarimetric radar measurement uncertainties through a power-law median raindrop diameter D0 algorithm to quantify the statistical uncertainties of the power-law regression. For this study, the power-law statistical uncertainty of D0 ranged from 0.11 to 0.17 mm. Also, the polarimetric scanning radar D0 estimates were compared with the median raindrop diameters retrieved from two vertically pointing profilers observing the same radar volume as the scanning radar. Based on over 900 observations, the standard deviation of the differences between the two radar estimates was approximately 0.16 mm. Thus, propagating polarimetric measurement uncertainties through D0 power-law regressions is comparable to uncertainties between polarimeteric and profiler D0 estimates. [ABSTRACT FROM AUTHOR]

A decrease in copolar correlation coefficient (ρco) at C band has been observed for several rain events with broad drop size distributions (DSDs). Observational evidence comes from simultaneous measurements with a C-band dual-polarization radar and a 2D video disdrometer. The possibility of utilizing the ρco decrease for DSD retrievals is discussed. A preliminary method using the copolar reflectivity, differential reflectivity, and ρco is given for estimating the DSD parameters. Validation is carried out by deriving the differential propagation phase (Φdp) from the estimated DSD parameters and comparing against measurements. The method presented here shows potential but needs to be further assessed in different rain climatologies. [ABSTRACT FROM AUTHOR]

This note assesses the improvements in dual-Doppler wind syntheses by employing a multipass Barnes objective analysis in the interpolation of radial velocities to a Cartesian grid, as opposed to a more typical single-pass Barnes objective analysis. Steeper response functions can be obtained by multipass objective analyses; that is, multipass objective analyses are less damping at well-resolved wavelengths (e.g., 8–20Δ, where Δ is the data spacing) than single-pass objective analyses, while still suppressing small-scale (<4Δ) noise. Synthetic dual-Doppler data were generated from a three-dimensional numerical simulation of a supercell thunderstorm in a way that emulates the data collection by two mobile radars. The synthetic radial velocity data from a pair of simulated radars were objectively analyzed to a grid, after which the three-dimensional wind field was retrieved by iteratively computing the horizontal divergence and integrating the anelastic mass continuity equation. Experiments with two passes and three passes of the Barnes filter were performed, in addition to a single-pass objective analysis. Comparison of the analyzed three-dimensional wind fields to the model wind fields suggests that multipass objective analysis of radial velocity data prior to dual-Doppler wind synthesis is probably worth the added computational cost. The improvements in the wind syntheses derived from multipass objective analyses are even more apparent for higher-order fields such as vorticity and divergence, and for trajectory calculations and pressure/buoyancy retrievals. [ABSTRACT FROM AUTHOR]

The U.S. Department of Energy Atmospheric Radiation Measurement (ARM) Program operates 35-GHz millimeter-wavelength cloud radars (MMCRs) in several climatologically distinct regions. The MMCRs, which are centerpiece instruments for the observation of clouds and precipitation, provide continuous, vertically resolved information on all hydrometeors above the ARM Climate Research Facilities (ACRF). However, their ability to observe clouds in the lowest 2–3 km of the atmosphere is often obscured by the presence of strong echoes from insects, especially during the warm months at the continental midlatitude Southern Great Plains (SGP) ACRF. Here, a new automated technique for the detection and elimination of insect-contaminated echoes from the MMCR observations is presented. The technique is based on recorded MMCR Doppler spectra, a feature extractor that conditions insect spectral signatures, and the use of a neural network algorithm for the generation of an insect (clutter) mask. The technique exhibits significant skill in the identification of insect radar returns (more than 92% of insect-induced returns are identified) when the sole input to the classifier is the MMCR Doppler spectrum. The addition of circular polarization observations by the MMCR and ceilometer cloud-base measurements further improve the performance of the technique and form an even more reliable method for the removal of insect radar echoes at the ARM site. Recently, a 94-GHz Doppler polarimetric radar was installed next to the MMCR at the ACRF SGP site. Observations by both radars are used to evaluate the potential of the 94-GHz radar as being insect free and to show that dual wavelength radar reflectivity measurements can be used to identify insect radar returns. [ABSTRACT FROM AUTHOR]

In this paper, two different numerical methods capable of computing multiple scattering effects in pulsed-radar systems are compared. Both methods are based on the solution of the time-dependent vectorial form of the radiative transfer equation: one exploits the successive order of scattering approximation, the other a forward Monte Carlo technique. Different benchmark results are presented (including layers of monodisperse spherical water and ice particles), which are of specific interest for W-band spaceborne cloud radars such as CloudSat’s or EarthCARE’s cloud profiling radars. Results demonstrate a good agreement between the two methods. The pros and cons of the two models are discussed, with a particular focus on the validity of the second order of scattering approximation. [ABSTRACT FROM AUTHOR]

The effect of tilt angle on horizontal wind estimation is studied using Indian mesosphere–stratosphere–troposphere (MST) radar located at Gadanki (13.45°N, 79.18°E). It operates in Doppler beam swinging (DBS) mode with a beamwidth of 3°. Horizontal winds are computed for different tilt angles from 3° to 15° with an increment of 3° from a height range of 3.6–18 km. The effective beam pointing angle (θeff) is calculated to determine the effect of aspect sensitivity on the determination of horizontal wind components. For different tilt angles radar-derived winds are compared with simultaneous GPS sonde wind measurements, which were launched from a nearby site. The first method utilizes direct comparison of radar-derived winds with those of GPS sondes using the actual beam pointing angle; the second method uses the effective beam pointing angle derived from the ratios of two oblique beams. For this study a variety of statistics were explored in terms of standard deviation, correlation coefficient, and percentage error. From the results it is observed that in agreement with previous studies, the effective beam pointing angle deviates from the actual beam pointing angle, which results in the underestimation of horizontal wind components, and also when tilt angle is close to zenith and far from zenith, the estimation of horizontal winds is found to be far from true values at different heights. Radar wind estimation has better agreement with GPS sonde measurement when the off-zenith angle is around 10°. It is also found that correction to the actual beam pointing angle provides 3%–6% improved agreement between the radar and GPS wind measurements. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The article focuses on the implementation of dual-polarization radar in the validation process of Global Precipitation Measurement (GPM) mission, currently a prototype which measure precipitation accurately. GPM is a science mission designed to provide detailed information on global water/energy cycle variability and to improve meteorological predictions. Its GPM core satellite is equipped with a dual-frequency precipitation radar (DPR) which will gather precipitation measurement that needs to be validated. It says that the dual-polarization weather radar can be used as a validation tool that could be applied to GPM to provide data related to hydrometeor phase/type information and droplet size distribution properties.

On 8 May 2003, a tornadic supercell tracked through portions of the Oklahoma City, Oklahoma, metropolitan area and produced violent damage along portions of its path. This storm passed through the dense in situ radar network in central Oklahoma and provided close-range operational, prototype polarimetric and terminal Doppler weather radar observations of the storm as it made the transition into the tornadic phase. The time-evolving polarimetric features were scrutinized with regard to storm morphology, particularly as related to the development of a rear-flank downdraft pulse within the storm immediately preceding the long-track tornado event. Two new polarimetric terms are introduced, the Zdr shield and Kdp foot, along with a discussion of the orientation of the Zdr and Kdp columns relative to midlevel rotation signatures. Storm downdraft and gust front characteristics are discussed relative to polarimetric fields and background environment characteristics. Highlighted for this event are a “warm” forward-flank downdraft and a particularly cold rear-flank downdraft. Emphasis is also placed on demonstrating key polarimetric field characteristics relative to traditional features at low and midlevels defined in familiar conceptual models of severe storms. [ABSTRACT FROM AUTHOR]

To obtain statistically stable reflectivity measurements by meteorological radars, it is common practice to average over several consecutive pulses during which the antenna rotates at a certain angular velocity. Taking into account the antenna’s continuous motion, the measured reflectivity is determined by an effective beam weighting function, which is different from a single-pulse weighting function—a fact that is widely ignored in applications involving beam weighting. In this paper, the effective beam weighting function is investigated in detail. The theoretical derivation shows that the effective weighting function is essentially a simple moving sum of single-beam weighting functions. Assuming a Gaussian shape of a single pulse, a simple and easy-to-use parameterization of the effective beam weighting function is arrived at, which depends only on the single beamwidth and the ratio of the single beamwidth to the rotational angular averaging interval. The derived relation is formulated in the “radar system” (i.e., the spherical coordinate system consisting of azimuth and elevation angles) that is often applied in practice. Formulas for the “beam system” (two orthogonal angles relative to the beam axis) are also presented. The final parameterization should be applicable to almost all meteorological radars and might be used (i) in specialized radar data analyses (with ground-based or satellite radars) and (ii) for radar forward operators to calculate simulated radar parameters from the results of NWP models. [ABSTRACT FROM AUTHOR]

Tornado vortices observed from Doppler radars are often associated with strong azimuthal shear and Doppler spectra that are wide and flattened. The current operational tornado detection algorithm (TDA) primarily searches for shear signatures that are larger than the predefined thresholds. In this work, a tornado detection procedure based on a fuzzy logic system is developed to integrate tornadic signatures in both the velocity and spectral domains. A novel feature of the system is that it is further enhanced by a neural network to refine the membership functions through a feedback training process. The hybrid approach herein, termed the neuro–fuzzy tornado detection algorithm (NFTDA), is initially verified using simulations and is subsequently tested on real data. The results demonstrate that NFTDA can detect tornadoes even when the shear signatures are degraded significantly so that they would create difficulties for typical vortex detection schemes. The performance of the NFTDA is assessed with level I time series data collected by the KOUN radar, a research Weather Surveillance Radar-1988 Doppler (WSR-88D) operated by the National Severe Storms Laboratory (NSSL), during two tornado outbreaks in central Oklahoma on 8 and 10 May 2003. In these cases, NFTDA and TDA provide good detections up to a range of 43 km. Moreover, NFTDA extends the detection range out to approximately 55 km, as the results indicate here, to detect a tornado of F0 magnitude on 10 May 2003. [ABSTRACT FROM AUTHOR]

A time-expanded sampling approach is proposed for the ensemble Kalman filter (EnKF). This approach samples a series of perturbed state vectors from each prediction run not only at the analysis time (as the conventional approach does) but also at other time levels in the vicinity of the analysis time. Since all the sampled state vectors are used to construct the ensemble, the number of required prediction runs can be much smaller than the ensemble size and this can reduce the computational cost. Since the sampling time interval can be adjusted to optimize the ensemble spread and enrich the ensemble structures, the proposed approach can improve the EnKF performance even though the number of prediction runs is greatly reduced. The potential merits of the time-expanded sampling approach are demonstrated by assimilation experiments with simulated radar observations for a supercell storm case. [ABSTRACT FROM AUTHOR]

Data from polarimetric radars offer remarkable insight into the microphysics of convective storms. Numerous tornadic and nontornadic supercell thunderstorms have been observed by the research polarimetric Weather Surveillance Radar-1988 Doppler (WSR-88D) in Norman, Oklahoma (KOUN); additional storm data come from the Enterprise Electronics Corporation “Sidpol” C-band polarimetric radar in Enterprise, Alabama, as well as the King City C-band polarimetric radar in Ontario, Canada. A number of distinctive polarimetric signatures are repeatedly found in each of these storms. The forward-flank downdraft (FFD) is characterized by a signature of hail observed as near-zero ZDR and high ZHH. In addition, a shallow region of very high ZDR is found consistently on the southern edge of the FFD, called the ZDR “arc.” The ZDR and KDP columns and midlevel “rings” of enhanced ZDR and depressed ρHV are usually observed in the vicinity of the main rotating updraft and in the rear-flank downdraft (RFD). Tornado touchdown is associated with a well-pronounced polarimetric debris signature. Similar polarimetric features in supercell thunderstorms have been reported in other studies. The data considered here are taken from both S- and C-band radars from different geographic locations and during different seasons. The consistent presence of these features may be indicative of fundamental processes intrinsic to supercell storms. Hypotheses on the origins, as well as microphysical and dynamical interpretations of these signatures, are presented. Implications about storm morphology for operational applications are suggested. [ABSTRACT FROM AUTHOR]

The recent advances in attenuation correction methodology are based on the use of a constraint represented by the total amount of the attenuation encountered along the path shared over each range bin in the path. This technique is improved by using the inner self-consistency of radar measurements. The full self-consistency methodology provides an optimization procedure for obtaining the best estimate of specific and cumulative attenuation and specific and cumulative differential attenuation. The main goal of the study is to examine drop size distribution (DSD) retrieval from X-band radar measurements after attenuation correction. A new technique for estimating the slope of a linear axis ratio model from polarimetric radar measurements at attenuated frequencies is envisioned. A new set of improved algorithms immune to variability in the raindrop shape–size relation are presented for the estimation of the governing parameters characterizing a gamma raindrop size distribution. Simulations based on the use of profiles of gamma drop size distribution parameters obtained from S-band observations are used for quantitative analysis. Radar data collected by the NOAA/Earth System Research Laboratory (ESRL) X-band polarimetric radar are used to provide examples of the DSD parameter retrievals using attenuation-corrected radar measurements. Retrievals agree fairly well with disdrometer data. The radar data are also used to observe the prevailing shape of raindrops directly from the radar measurements. A significant result is that oblateness of drops is bounded between the two shape models of Pruppacher and Beard, and Beard and Chuang, the former representing the upper boundary and the latter the lower boundary. [ABSTRACT FROM AUTHOR]

In a recent study, Rozoff et al. proposed a possible mechanism to explain the formation and maintenance of the weak-echo annulus (or moat) outside of the primary eyewall of a tropical cyclone observed in radar images. By this mechanism, the moat is determined to be a region of the strain-dominated flow outside of the radius of maximum wind in which essentially all fields are filamented and deep convection is hypothesized to be highly distorted and even suppressed. This strain-dominated region is defined as the rapid filamentation zone wherein the filamentation time is shorter than the overturning time of deep convection. An attempt has been made in this study to test the hypothesis in a full-physics tropical cyclone model under idealized conditions and to extend the concept to the study of the inner-core dynamics of tropical cyclones. The foci of this paper are the evolution of the rapid filamentation zone during the storm intensification, the potential roles of rapid filamentation in the organization of inner spiral rainbands, and the damping of high azimuthal wavenumber asymmetries in the tropical cyclone inner core. The presented results show that instead of suppressing deep convection, the strain flow in the rapid filamentation zone outside the elevated potential vorticity core provides a favorable environment for the organized inner spiral rainbands, which generally have time scales of several hours, much longer than the typical overturning time scale of individual convective clouds. Although the moat in the simulated tropical cyclone is located in the rapid filamentation zone, it is mainly controlled by the subsidence associated with the overturning flow from eyewall convection and downdrafts from the anvil stratiform precipitation outside of the eyewall. It is thus suggested that rapid filamentation is likely to play a secondary role in the formation of the moat in tropical cyclones. Although the deformation field is determined primarily by the structure of the tropical cyclone, it can have a considerable effect on the evolution of the storm. Because of strong straining deformation, asymmetries with azimuthal wavenumber >4 are found to be damped effectively in the rapid filamentation zone. The filamentation time thus provides a quantitative measure of the stabilization and axisymmetrization of high-wavenumber asymmetries in the inner core by shearing deformation and filamentation. [ABSTRACT FROM AUTHOR]

A full radar simulator, which works with the 3D output fields from a numerical mesoscale model, has been developed. This simulator uses a T-matrix code to calculate synthetic radar measurements, accounts for both backscattering and propagation effects, and includes polarimetric variables. The tool is modular to allow several options in the derivation of the synthetic radar variables. A measurement uncertainty can be taken into account on both the simulated reflectivities and the differential phase shift. A scheme can also be switched on to allow for the gate-to-gate variability of the rain drops size distribution or, also, their oblateness. This work was done in the framework of the installation in West Africa of a polarimetric X-band radar for the observation of tropical rain. Accordingly, the first objective pursued with this simulation setup is a detailed analysis of X-band polarimetric rain retrieval algorithms. Two retrieval schemes, a simple R–KDP formula and a profiler that uses both reflectivity and φDP, are tested. For that purpose the simulator is run on a model case study of an African squall line, then the two schemes are used to retrieve the rain rates from the synthetic radar variables and compare them to the original. The scores of the schemes are discussed and compared. The authors analyze the sensitivity of the results to the measurement uncertainty and also to several aspects of drop size distribution and drop shape variability. [ABSTRACT FROM AUTHOR]

A three-dimensional radar simulator capable of generating simulated raw time series data for a weather radar has been designed and implemented. The characteristics of the radar signals (amplitude, phase) are derived from the atmospheric fields from a high-resolution numerical weather model, although actual measured fields could be used. A field of thousands of scatterers is populated within the field of view of the virtual radar. Reflectivity characteristics of the targets are determined from well-known parameterization schemes. Doppler characteristics are derived by forcing the discrete scatterers to move with the three-dimensional wind field. Conventional moment-generating radar simulators use atmospheric conditions and a set of weighting functions to produce theoretical moment maps, which allow for the study of radar characteristics and limitations given particular configurations. In contrast to these radar simulators, the algorithm presented here is capable of producing sample-to-sample time series data that are collected by a radar system of virtually any design. Thus, this new radar simulator allows for the test and analysis of advanced topics, such as phased array antennas, clutter mitigation schemes, waveform design studies, and spectral-based methods. Limited examples exemplifying the usefulness and flexibility of the simulator will be provided. [ABSTRACT FROM AUTHOR]

The Precipitation Occurrence Sensor System (POSS) is a small X-band Doppler radar originally developed by the Meteorological Service of Canada for reporting the occurrence, type, and intensity of precipitation from Automated Weather Observing Stations. This study evaluates POSS as a gauge for measuring amounts of both liquid and solid precipitation. Different precipitation rate estimation algorithms are described. The effect of different solid precipitation types on the Doppler velocity spectrum is discussed. Lacking any accepted reference for high temporal resolution rates, the POSS precipitation rate measurements are integrated over time periods ranging from 6 h to one day and validated against international and Canadian reference gauges. Data from a wide range of sites across Canada and for periods of several years are used. The statistical performance of POSS is described in terms of the distribution of ratios of POSS to reference gauge amounts (catch ratios). In liquid precipitation the median of the catch ratio distribution is 82% and the interquartile range was between -12% and 19% about the median. In solid precipitation the median is 90% and the interquartile range is between -17% and 24% about the median. The underestimation in both liquid and solid precipitation is shown to be a function of precipitation rate and phase. The effects of radome wetting, raindrop splashing, wind, and the radar “brightband” effect on the estimation of precipitation rates are discussed. [ABSTRACT FROM AUTHOR]

The maximum cross-correlation (MCC) technique is utilized to estimate the Adriatic Sea surface currents in regions characterized by strong horizontal temperature gradients using sequential pairs of sea surface temperature images from the Advanced Very High Resolution Radiometer data collected between September 2002 and December 2003. A variety of filtering techniques are used to eliminate erroneous MCC-derived currents resulting in velocity and direction estimates that are spatially coherent in most of the thermal features observed. The results are compared quantitatively to the currents measured by surface drifters and high-frequency coastal radars, operating simultaneously in the vicinity of the thermal structures considered. These comparisons show that surface MCC-derived velocities agree with the typical circulation pattern generally observed in the Adriatic basin. The MCC velocity estimates agree well with collocated and cotemporal drifter and radar measurements averaged on the time interval separating the pairs of images. Since the MCC method provides only estimates of surface currents when thermal features exist and are not covered by clouds, it is proposed that this technique be used preferably with other measurements of surface circulation (high-frequency coastal radars, drifters, etc.) to construct more accurate, more frequent, and more extended circulation maps for scientific and operational purposes in marginal seas such as the Adriatic. [ABSTRACT FROM AUTHOR]

A method of analyzing radar data is developed and applied to determine whether the X-band radar reflectivity evolution of clouds observed during summertime on the northeast Florida coast during the Small Cumulus Microphysics Study (SCMS) shows distinct differences in precipitation development that can be associated with the clouds’ maritime or continental characteristics. For this study, the entire National Center for Atmospheric Research CP2 radar dataset from SCMS was examined, and 38 clouds were used. For these clouds the evolution in X-band radar reflectivity, from the clouds’ earliest detection through precipitation, was clearly documented and met specific requirements concerning the clouds’ location relative to the coastline and direction of movement. Since cloud condensation nuclei (CCN) and giant and ultragiant nuclei (GN) measurements were not available for the specific clouds used in this study, proxies were used to partition the clouds into four groups based on the cloud location and direction of movement. Specifically, it was assumed that clouds forming over the ocean during onshore flow had maritime characteristics (group 1: low CCN, high GN), clouds forming over land during onshore flow would have modified maritime characteristics (group 2: high CCN, high GN), clouds forming over land during offshore flow would have continental characteristics (group 3: high CCN, low GN), and clouds forming over the ocean during offshore flow would have modified continental characteristics (group 4: high CCN, high GN). These assumptions are based on past measurements presented by Sax and Hudson. Then, these populations were statistically compared using the nonparametric multiresponse permutation procedure developed by Mielke et al. A comparison of groups 1 and 2 provided a test of the role of CCN concentrations in precipitation development in these cloud populations. A comparison of groups 3 and 4 provided a test of the role of GN concentrations in precipitation development in these cloud populations. The two cloud populations that were disjoint at a statistically significant level were groups 1 and 2. For these groups, the analysis showed that the median characteristic total water content of the truly maritime clouds (group 1) was about half that of the modified maritime clouds (group 2) at the time of precipitation formation. The characteristic time to precipitation formation was about 60% smaller for the truly maritime clouds. Thus, the characteristic reflectivity threshold for precipitation development was reached at a much lower altitude above cloud base in a much faster time in the truly maritime clouds. This result supports the conclusions of Hudson and Yum that precipitation development in the SCMS clouds was primarily controlled by CCN concentrations rather than GN concentrations. [ABSTRACT FROM AUTHOR]

A series of poststorm surveys were conducted in the wake of hailstorms observed by the Colorado State University–University of Chicago–Illinois State Water Survey (CSU-CHILL) S-Band polarimetric radar. Information on hail characteristics (maximum diameter, building damage, apparent hailstone density, etc.) was solicited from the general-public storm observers that were contacted during the surveys; the locations of their observations were determined using GPS equipment. Low-elevation angle radar measurements of reflectivity, differential reflectivity ZDR, and linear depolarization ratio (LDR) were interpolated to the ground-observer locations. Relationships between the hail differential reflectivity parameter HDR and the observer-reported hail characteristics were examined. It was found that HDR thresholds of 21 and 30 dB were reasonably successful (critical success index values of ∼0.77) in respectively identifying regions where large (>19 mm in diameter) and structurally damaging hail were observed. The LDR characteristics in the observed hail areas were also examined. Because of sensitivities to variations in the hailstone bulk ice density, degree of surface wetness, and shape irregularities, the basic correlation between LDR magnitude and hail diameter was poor. However, when the reported hail diameters exceeded ∼25 mm, LDR levels below ∼-24 dB were uncommon. [ABSTRACT FROM AUTHOR]

The U.S. Department of Energy Atmospheric Radiation Measurement (ARM) Program operates millimeter-wavelength cloud radars in several climatologically distinct regions. The digital signal processors for these radars were recently upgraded and allow for enhancements in the operational parameters running on them. Recent evaluations of millimeter-wavelength cloud radar signal processing performance relative to the range of cloud dynamical and microphysical conditions encountered at the ARM Program sites have indicated that improvements are necessary, including significant improvement in temporal resolution (i.e., less than 1 s for dwell and 2 s for dwell and processing), wider Nyquist velocities, operational dealiasing of the recorded spectra, removal of pulse compression while sampling the boundary layer, and continuous recording of Doppler spectra. A new set of millimeter-wavelength cloud radar operational modes that incorporate these enhancements is presented. A significant change in radar sampling is the introduction of an uneven mode sequence with 50% of the sampling time dedicated to the lower atmosphere, allowing for detailed characterization of boundary layer clouds. The changes in the operational modes have a substantial impact on the postprocessing algorithms that are used to extract cloud information from the radar data. New methods for postprocessing of recorded Doppler spectra are presented that result in more accurate identification of radar clutter (e.g., insects) and extraction of turbulence and microphysical information. Results of recent studies on the error characteristics of derived Doppler moments are included so that uncertainty estimates are now included with the moments. The microscale data product based on the increased temporal resolution of the millimeter-wavelength cloud radars is described. It contains the number of local maxima in each Doppler spectrum, the Doppler moments of the primary peak, uncertainty estimates for the Doppler moments of the primary peak, Doppler moment shape parameters (e.g., skewness and kurtosis), and clear-air clutter flags. [ABSTRACT FROM AUTHOR]

Echoes in clear air from two types of biological scatterers mixed within the resolution volumes over a large region, observed with S-band dual polarization radar, are presented. This case occurred in the evening of 7 September 2004, at the beginning of the fall migrating season of song birds (passerines). Polarimetric spectral analyses are used for distinguishing birds and insects in multimodal spectra. Spatial continuity of spectral peaks shows clear separation of insect (wind) speeds from bird speeds. Spectral densities of polarimetric variables exhibit vastly different values at speeds corresponding to insects than from those of birds, allowing the separation of the two scatterer types. Therefore, the statistics of the intrinsic polarimetric variables computed from spectral densities are unbiased and closer to the ensemble statistics of the echo type than the ones obtained with standard processing techniques. A novel display of the spectral densities versus azimuth, termed spectral velocity–azimuth display (SVAD), is constructed for easier viewing and interpretation of the velocity field. Analyses of the SVADs reveal the mean velocities and the directions of the two types of scatterers. [ABSTRACT FROM AUTHOR]

Three-dimensional cloud-resolving model simulations of a mesoscale region around Kwajalein Island during the Kwajalein Experiment (KWAJEX) are performed. Using observed winds along with surface and large-scale thermodynamic forcings, the model tracks the observed mean thermodynamic soundings without thermodynamic nudging during 52-day simulations spanning the whole experiment time period, 24 July–14 September 1999. Detailed comparisons of the results with cloud and precipitation observations, including radar reflectivities from the Kwajalein ground validation radar and International Satellite Cloud Climatology Project (ISCCP) cloud amounts and radiative fluxes, reveal the biases and sensitivities of the model’s simulated clouds. The amount and optical depth of high cloud are underpredicted by the model during less rainy periods, leading to excessive outgoing longwave radiation (OLR) and insufficient albedo. The simulated radar reflectivities tend to be excessive, especially in the upper troposphere, suggesting that simulated high clouds are precipitating large hydrometeors too efficiently. Occasionally, large-scale advective forcing errors also seem to contribute to upper-level cloud and relative humidity biases. An extensive suite of sensitivity studies to different microphysical and radiative parameterizations is performed, with surprisingly little impact on the results in most cases. [ABSTRACT FROM AUTHOR]

The impact of beam broadening on the quality of radar polarimetric data in the presence of nonuniform beam filling (NBF) is examined both theoretically and experimentally. Cross-beam gradients of radar reflectivity Z, differential reflectivity ZDR, and differential phase ΦDP within the radar resolution volume may produce significant biases of ZDR, ΦDP, and the cross-correlation coefficient ρhv. These biases increase with range as a result of progressive broadening of the radar beam. They are also larger at shorter radar wavelengths and wider antenna beams. Simple analytical formulas are suggested for estimating the NBF-induced biases from the measured vertical and horizontal gradients of Z, ZDR, and ΦDP. Analysis of polarimetric data collected by the KOUN Weather Surveillance Radar-1988 Doppler (WSR-88D) demonstrates that frequently observed perturbations of the radial ΦDP profiles and radially oriented “valleys” of ρhv depression can be qualitatively and quantitatively explained using the suggested NBF model. [ABSTRACT FROM AUTHOR]

Communities and many industries are affected by severe weather and have a need for real-time accurate Weather Surveillance Radar-1988 Doppler (WSR-88D) data spanning several regions. To fulfill this need the National Severe Storms Laboratory has developed a Four-Dimensional Dynamic Grid (4DDG) to accurately represent discontinuous radar reflectivity data over a continuous 4D domain. The objective is to create a seamless, rapidly updating radar mosaic that is well suited for use by forecasters in addition to advance radar applications such as qualitative precipitation estimates. Several challenges are associated with creating a 3D radar mosaic given the nature of radar data and the spherical coordinates of radar observations. The 4DDG uses spatial and temporal weighting schemes to overcome these challenges, with the intention of applying minimal smoothing to the radar data. Previous multiple radar mosaics functioned in two or three dimensions using a variety of established weighting schemes. The 4DDG has the advantage of temporal weighting to smooth radar observations over time. Using an exponentially decaying weighting scheme, this paper will examine different weather scenarios and show the effects of temporal smoothing using different time scales. Specifically, case examples of the 4DDG approach involving a rapidly evolving convective event and a slowly developing stratiform weather regime are considered. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Among the single-Doppler radar wind analysis methods, the velocity–azimuth display (VAD), velocity–azimuth process (VAP), and uniform-wind (UW) methods are widely used because of their simplicity. This paper shows that the VAD, VAP, and UW methods can all be derived from the same relationship based on the azimuthal uniform-wind assumption. Using this assumption, an integrating VAP (IVAP) method is developed that can provide a smoother wind field than the VAP and UW methods and a higher resolution than the VAD method. Using the IVAP technique, the wind fields associated with a heavy rainfall case in Shanghai, China, are retrieved and compared with those from surface observations and wind-profiler data. [ABSTRACT FROM AUTHOR]

This study aims at determining the three-dimensional distribution of ice water content over a broad area near the Atmospheric Radiation Measurement Program Southern Great Plains site, where cloud radar and meteorological observations have been routinely conducted. Together with wind fields from other measurements, the ice water content retrievals can be used to derive the cloud ice water advective tendency terms needed for single-column model simulations. In this study, a Bayesian retrieval algorithm has been developed that combines multiple data sources from satellite high-frequency microwave radiometry, ground cloud radar observations, and mesoscale numerical model analysis. The cloud radar observations allow the characteristics of vertical ice water content structures to be inferred. The numerical model data are used to locate the cloud height. The satellite data provide information on the integrated ice water path, its horizontal distribution over a broad area, and, to a lesser extent, the vertical structure of ice water content. The approach herein is to retrieve the three-dimensional cloud ice water content in a 10° × 10° area surrounding the cloud radar site by combining all the information contained in the above datasets through a Bayesian framework. Validation of the algorithm has been done by comparing the retrievals with measurements from two ground radars. The comparison shows that the mean ice water content profiles and the two-dimensional (height–ice water content) probability density functions retrieved for 19 coincident cases agree fairly well with the validation data. However, the retrieved ice water contents generally lack detailed vertical structures because of the low sensitivity of satellite data to the vertical variation of cloud ice. [ABSTRACT FROM AUTHOR]

To design X-band radar systems as well as evaluate algorithm development, it is useful to have simultaneous X-band observation with and without the impact of path attenuation. One way to develop that dataset is through theoretical models. This paper presents a methodology to generate realistic range profiles of radar variables at attenuating frequencies, such as X band, for rain medium. Fundamental microphysical properties of precipitation, namely, size and shape distribution information, are used to generate realistic profiles of X band starting with S-band observation. Conditioning the simulation from S band maintains the natural distribution of rainfall microphysical parameters. Data from the Colorado State University’s University of Chicago–Illinois State Water Survey (CHILL) radar and the National Center for Atmospheric Research S-band dual-polarization Doppler radar (S-POL) are used to simulate X-band radar variables. Three procedures to simulate the radar variables and sample applications are presented. [ABSTRACT FROM AUTHOR]

This paper explores the removal of normal ground echoes (GREs) and anomalous propagation (AP) in ground-based radars using a fuzzy logic approach. Membership functions and their weights are derived from the characteristics of radar echoes as a function of radar reflectivity. The dependence on echo intensity is shown to significantly improve the proper identification of GRE/AP. In addition, the proposed method has a better performance at lower elevation angles. The overall performance is comparable with that from a polarimetric approach and can thus be easily implemented in operational radars. [ABSTRACT FROM AUTHOR]

A high-resolution radar data assimilation system is presented for high-resolution numerical weather prediction models. The system is under development at the Naval Research Laboratory for the Navy’s Coupled Ocean–Atmosphere Mesoscale Prediction System. A variational approach is used to retrieve three-dimensional dynamical fields of atmospheric conditions from multiple-Doppler radar observations of radial velocity within a limited area. The methodology is described along with a preliminary evaluation of the impact of assimilated radar data on model forecasts using a case study of a squall line that occurred along the east coast of the United States on 9 May 2003. Results from the experiments show a significant impact from the assimilated radar radial velocity data on the model forecast of not just dynamical but also hydrological fields at all model levels for the duration of the storm. A verification system has also been developed to assess the radar data assimilation impact, and the results show improvements in the three-dimensional wind forecasts but relatively small changes in the prediction of storm locations. This study highlights the need to develop a continuous radar data assimilation system to maximize the impact of the data. [ABSTRACT FROM AUTHOR]

Over the last few years the use of weather radar data has become a fundamental part of various applications like rain-rate estimation, nowcasting of severe weather events, and assimilation into numerical weather prediction models. The increasing demand for radar data necessitates an automated, flexible, and modular quality control. In this paper a quality control procedure is developed for radar reflectivity factors, polarimetric parameters, and Doppler velocity. It consists of several modules that can be extended, modified, and omitted depending on the user requirement, weather situation, and radar characteristics. Data quality is quantified on a pixel-by-pixel basis and encoded into a quality-index field that can be easily interpreted by a nontrained end user or an automated scheme that generates radar products. The quality-index algorithms detect and quantify the influence of beam broadening, the height of the first radar echo, ground clutter contamination, return from non-weather-related objects, and attenuation of electromagnetic energy by hydrometeors on the quality of the radar measurement. The quality-index field is transferred together with the radar data to the end user who chooses the amount of data and the level of quality used for further processing. The calculation of quality-index fields is based on data measured by the polarimetric C-band Doppler radar (POLDIRAD) located in the Alpine foreland in southern Germany. [ABSTRACT FROM AUTHOR]

A method to estimate ocean wave directional spectra using a high-frequency (HF) ocean radar was developed. The governing equations of wave spectra are integral equations of first- and second-order radar cross sections, the wave energy balance equation, and the continuity equation of surface winds. The parameterization of the source function is the same as that in WAM. Furthermore, the method uses the constraints that wave spectral values are smooth in both wave frequency and direction and that the propagation terms are small. The unknowns to be estimated are surface wind vectors at radial grids whose centers are the radar position, and wave spectral values at radial and wave frequency–direction grids. The governing equations are discretized in the radial and wave frequency–direction grids and are converted into a nonlinear minimization problem. Identical twin experiments showed that the present method can estimate wave spectra and dynamically extrapolate wave spectra, even in an inhomogeneous wave field. [ABSTRACT FROM AUTHOR]

A novel resolution enhancement technique using range oversampling (RETRO) is presented. Oversampled signals are radar returns from shifted and overlapped resolution volumes in range. It has been recently shown that these signals can be whitened and averaged to optimally reduce the statistical error of weather spectral moment estimations for the case of uniform reflectivity and velocity. Using the same oversampled data, when the resolution is of interest, RETRO can reveal the variation of reflectivity and velocity in range at finescale. The idea is to utilize the redundant information contained in oversampled signals, which come from common regions, to improve the resolution defined by the range weighting function. As a result, oversampled data are optimally combined to produce high-resolution signals for spectral moment estimations. RETRO is demonstrated and verified using numerical simulations for two cases. In the first case, range variation of a tornadic vortex with a diameter of 120 m can be reconstructed by RETRO at a scale of 25 m when a 250-m pulse and an oversampling factor of 10 are used. Application of RETRO to mitigate ground clutter contamination is demonstrated in the second case. [ABSTRACT FROM AUTHOR]

A very short-term rainfall forecast model is tested on actual radar data. This model, called RadVil, takes advantages of voluminal radar data through vertically integrated liquid (VIL) water content measurements. The model is tested on a dataset collected during the intensive observation period of the Mesoscale Alpine Program (MAP). Five rain events have been studied during this experiment. The results confirm the interest of VIL for quantitative precipitation forecasting at very short lead time. The evaluation is carried out in qualitative and quantitative ways according to Nash and correlation criteria on forecasting times ranging from 10 to 90 min and spatial scales from 4 to 169 km2. It attempts to be consistent with the hydrological requirements concerning the rainfall forecasting, for instance, by taking account of the relation between the catchments' size, their response time, and the required forecasting time. Several versions of RadVil corresponding to several VIL measurement strategies have been tested. Improvements offered by RadVil depend on meteorological situations. They are related to the spatial and temporal evolution of the VIL field structure and the validity of the models assumptions. Finally, a relationship between the temporal structure of VIL fields and forecast quality is established. [ABSTRACT FROM AUTHOR]

Intense tropical cyclones often possess relatively little convection around their cores. In radar composites, this surrounding region is usually echo-free or contains light stratiform precipitation. While subsidence is typically quite pronounced in this region, it is not the only mechanism suppressing convection. Another possible mechanism leading to weak-echo moats is presented in this paper. The basic idea is that the strain-dominated flow surrounding an intense vortex core creates an unfavorable environment for sustained deep, moist convection. Strain-dominated regions of a tropical cyclone can be distinguished from rotation-dominated regions by the sign of S21 + S22 - ζ2, where S1 = ux - υy and S2 = υx + uy are the rates of strain and ζ = υx - uy is the relative vorticity. Within the radius of maximum tangential wind, the flow tends to be rotation-dominated (ζ2 > S21 + S22), so that coherent structures, such as mesovortices, can survive for long periods of time. Outside the radius of maximum tangential wind, the flow tends to be strain-dominated (S21 + S22 > ζ2), resulting in filaments of anomalous vorticity. In the regions of strain-dominated flow the filamentation time is defined as τfil = 2(S21 + S22 - ζ2)-1/2. In a tropical cyclone, an approximately 30-km-wide annular region can exist just outside the radius of maximum tangential wind, where τfil is less than 30 min and even as small as 5 min. This region is defined as the rapid filamentation zone. Since the time scale for deep moist convective overturning is approximately 30 min, deep convection can be significantly distorted and even suppressed in the rapid filamentation zone. A nondivergent barotropic model illustrates the effects of rapid filamentation zones in category 1–5 hurricanes and demonstrates the evolution of such zones during binary vortex interaction and mesovortex formation from a thin annular ring of enhanced vorticity. [ABSTRACT FROM AUTHOR]

A procedure for estimating radar rainfall in real time consists of three main steps: 1) the measurement of reflectivity and removal of known sources of errors, 2) the conversion of the reflectivity to a rainfall rate (Z–R conversion), and 3) the adjustment of the mean field bias as assessed using a rain gauge network. Error correction is associated with the first two steps and incorporates removing erroneous measurements and correcting biases in the Z–R conversion. This paper investigates the relative importance of error correction and the mean field bias–adjustment processes. In addition to the correction for ground clutter, the bright band, and hail, the two error correction strategies considered here are 1) a scale transformation function to remove range-dependent bias in measured reflectivity resulting from an increase in observation volume with range, and 2) the classification of storm types to account for the variation in Z–R relationships for convective and stratiform rainfall. The mean field bias is removed using two alternatives: 1) estimation of the bias at each time step based on the sample of observations available, and 2) use of a Kalman filter to estimate the bias under assumptions of a Markovian dependence structure. A 7-month record of radar and rain gauge rainfall for Sydney, Australia, were used in this study. The results show a stepwise decrease in the root-mean-square error (rmse) of radar rainfall with added levels of error correction using either of the two mean field bias–adjustment methods considered in our study. It was found that although the effects of the two error correction strategies were small compared to bias adjustment, they do form an important step of radar-rainfall estimation. [ABSTRACT FROM AUTHOR]