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Previous work has shown that vorticity mixing in the tropical cyclone (TC) inner core can promote mesovortex (MV) formation and impact storm intensity. Observations of MVs have largely been serendipitous but are necessary to improve understanding of these features and their role in TC dynamics. This study presents nearly 10 h of ground-based dual-Doppler analysis of MVs in the eyewall of Hurricane Ike (2008) near and during landfall. Derived 3D winds, vertical vorticity, horizontal divergence, and perturbation pressures are analyzed. Results indicate persistent kinematic field arrangements and evolving vertical structures. Perturbation pressure retrievals suggest local pressure minima associated with the MVs. Preferential updraft locations appear to transition cyclonically about the local vorticity maximum as the MVs progress around the eye. Based on published observational datasets, the dual-Doppler updraft magnitudes in Ike's MVs are within the top 5%-10% of TC vertical velocities. The MVs are marked by peak vorticity in the lowest 2 km and contain vertically coherent vorticity structures extending to 8 km AGL. After prolonged land interaction, the MV structures deteriorate. First, the vertical extent of localized vorticity diminishes, followed by a deterioration in the prelandfall characteristic kinematic arrangements. This supports the notion that the replenishment of a high vorticity annulus contributes to MV production and maintenance, and when the elevated vorticity aloft is not maintained, MV kinematic patterns become less consistent. It is unclear whether the decay of the vertically coherent vorticity structures occurs in response to land interaction, TC inner core processes, or some combination of both. [ABSTRACT FROM AUTHOR]

S-band profiling (S-PROF) radar measurements from different southeastern U.S. Hydrometeorology Testbed sites indicated a frequent occurrence of rain that did not exhibit radar bright band (BB) and was observed outside the periods of deep-convective precipitation. This common nonbrightband (NBB) rain contributes ~15%-20% of total accumulation and is not considered as a separate rain type by current precipitation-segregation operational radar-based schemes, which separate rain into stratiform, convective, and, sometimes, tropical types. Collocated with S-PROF, disdrometer measurements showed that drop size distributions (DSDs) of NBB rain have much larger relative fractions of smaller drops when compared with those of BB and convective rains. Data from a year of combined DSD and rain-type observations were used to derive S-band-radar estimators of rain rate R, including those based on traditional reflectivity Z e and ones that also use differential reflectivity ZDR and specific differential phase KDP. Differences among same-type estimators for mostly stratiform BB and deep-convective rain were relatively minor, but estimators derived for the common NBB rain type were distinct. Underestimations in NBB rain-rate retrievals derived using other rain-type estimators (e.g., those for BB or convective rain or default operational radar estimators) for the same values of radar variables can be on average about 40%, although the differential phase-based estimators are somewhat less susceptible to DSD details. No significant differences among the estimators for the same rain type derived using DSDs from different observational sites were present despite significant separation and differing terrain. Identifying areas of common NBB rain could be possible from Z e and Z DR measurements. [ABSTRACT FROM AUTHOR]

The Thunderstorm Observation by Radar (ThOR) algorithm is an objective and tunable Lagrangian approach to cataloging thunderstorms. ThOR uses observations from multiple sensors (principally multisite surveillance radar data and cloud-to-ground lightning) along with established techniques for fusing multisite radar data and identifying spatially coherent regions of radar reflectivity (clusters) that are subsequently tracked using a new tracking scheme. The main innovation of the tracking algorithm is that, by operating offline, the full data record is available, not just previous cluster positions, so all possible combinations of object sequences can be developed using all observed object positions. In contrast to Eulerian methods reliant on thunder reports, ThOR is capable of cataloging nearly every thunderstorm that occurs over regional-scale and continental United States (CONUS)-scale domains, thereby enabling analysis of internal properties and trends of thunderstorms. ThOR is verified against 166 manually analyzed cluster tracks and is also verified using descriptive statistics applied to a large (~35 000 tracks) sample. Verification also relied on a benchmark tracking algorithm that provides context for the verification statistics. ThOR tracks are shown to match the manual tracks slightly better than the benchmark tracks. Moreover, the descriptive statistics of the ThOR tracks are nearly identical to those of the manual tracks, suggesting good agreement. When the descriptive statistics were applied to the ~35 000-track dataset, ThOR tracking produces longer (statistically significant), straighter, and more coherent tracks than those of the benchmark algorithm. Qualitative assessment of ThOR performance is enabled through application to a multiday thunderstorm event and comparison to the behavior of the Storm Cell Identification and Tracking (SCIT) algorithm. [ABSTRACT FROM AUTHOR]

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]

The authors present observations of the microphysical characteristics of deep convection that overshoots the altitude of the extratropical tropopause from analysis of the polarimetric radar variables of radar reflectivity factor at horizontal polarization ZH, differential reflectivity ZDR, and specific differential phase KDP. Identified overshooting convective storms are separated by their organization and intensity into three classifications: organized convection, discrete ordinary convection, and discrete supercell convection. Composite analysis of identified storms for each classification reveals microphysical features similar to those found in previous studies of deep convection, with deep columns of highly positive ZDR and KDP representing lofting of liquid hydrometeors within the convective updraft and above the melting level. In addition, organized and discrete supercell classifications show distinct near-zero ZDR minima aligned horizontally with and at altitudes higher than the updraft column features, likely indicative of the frequent presence of large hail in each case. Composites for organized convective systems show a similar ZDR minimum throughout the portion of the convective core that is overshooting the tropopause, corresponding to ZH in the range of 15-30 dB Z and negative KDP observations, in agreement with the scattering properties of small hail and/or lump or conical graupel. Additional analyses of the evolution of overshooting storms reveals that the ZDR minima indicative of hail in the middle and upper troposphere and graupel in the overshooting top are associated with the mature and decaying stages of overshooting, respectively, supporting their inferred contributions to the observed polarimetric fields. [ABSTRACT FROM AUTHOR]

This study uses Dynamics of the Madden-Julian Oscillation (DYNAMO) shipborne [Research Vessel (R/V) Roger Revelle] radar and Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) datasets to investigate MJO-associated convective systems in specific organizational modes [mesoscale convective system (MCS) versus sub-MCS and linear versus nonlinear]. The Revelle radar sampled many 'climatological' aspects of MJO convection as indicated by comparison with the long-term TRMM PR statistics, including areal-mean rainfall (6-7 mm day−1), convective intensity, rainfall contributions from different morphologies, and their variations with MJO phase. Nonlinear sub-MCSs were present 70% of the time but contributed just around 20% of the total rainfall. In contrast, linear and nonlinear MCSs were present 10% of the time but contributed 20% and 50%, respectively. These distributions vary with MJO phase, with the largest sub-MCS rainfall fraction in suppressed phases (phases 5-7) and maximum MCS precipitation in active phases (phases 2 and 3). Similarly, convective-stratiform rainfall fractions also varied significantly with MJO phase, with the highest convective fractions (70%-80%) in suppressed phases and the largest stratiform fraction (40%-50%) in active phases. However, there are also discrepancies between the Revelle radar and TRMM PR. Revelle radar data indicated a mean convective rain fraction of 70% compared to 55% for TRMM PR. This difference is mainly due to the reduced resolution of the TRMM PR compared to the ship radar. There are also notable differences in the rainfall contributions as a function of convective intensity between the Revelle radar and TRMM PR. In addition, TRMM PR composites indicate linear MCS rainfall increases after MJO onset and produce similar rainfall contributions to nonlinear MCSs; however, the Revelle radar statistics show the clear dominance of nonlinear MCS rainfall. [ABSTRACT FROM AUTHOR]

Most of the recent hydrometeor classification schemes are based on fuzzy logic. When the input radar observations are noisy, the output classification could also be noisy, since the process is bin based and the information from neighboring radar cells is not considered. This paper employs cluster analysis, in combination with fuzzy logic, to improve the hydrometeor classification from dual-polarization radars using a multistep approach. The first step involves a radar-based optimization of an input temperature profile from auxiliary data. Then a first-guess fuzzy logic processing produces the classification to initiate a cluster analysis with contiguity and penalty constraints. The result of the cluster analysis is eventually processed to identify the regions populated with adjacent bins assigned to the same hydrometeor class. Finally, the set of connected regions is passed to the fuzzy logic algorithm for the final classification, exploiting the statistical sample composed by the distribution of the dual-polarization and temperature observations within the regions. Example applications to radar in different environments and meteorological situations, and using different operating frequency bands-namely, S, C, and X bands-are shown. The results are discussed with specific attention to the robustness of the method and the segregation of the data space. Furthermore, the sensitivity to noise and bias in the input variables is also analyzed. [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]

Biological scatterers, consisting of birds and insects, may become trapped near the circulation center of tropical cyclones, particularly if a well-developed eyewall is present. These scatterers may be observed using weather radar, where they may appear to the radar operator as areas of light precipitation. Polarimetric radar characteristics of these scatterers, informed by additional observations of known bioscatter, include a combination of very high differential reflectivity (3-7.9 dB) and very low copolar correlation coefficient (0.3-0.8). Polarimetric radar observations of bioscatter are presented for Hurricane Irene (2011) and Hurricane Sandy (2012). In these storms, the bioscatter signature first appeared at the 0.5° elevation angle at a distance of 100-120 km from the radar. The signature appeared on successively higher tilts as the circulation center neared the radar, and its areal coverage in constant altitude plan position indicator (CAPPI) slices was primarily governed by the distribution of convection in the eye and by the timing of landfall. The highest altitude at which the signature appears may represent the inversion level within certain tropical cyclone eyes. For Hurricane Irene, inland observations of oceanic bird species support biological transport. Knowledge of the bioscatter signature has value to meteorologists monitoring tropical cyclones within the range of a polarimetric radar, possible value for estimating inversion height changes within the eyes of well-structured tropical cyclones, and value to biologists who wish to estimate the magnitude of biological transport in tropical cyclones. [ABSTRACT FROM AUTHOR]

This paper presents new methods for rainfall estimation from X-band dual-polarization radar observations along with advanced techniques for quality control, hydrometeor classification, and estimation of specific differential phase. Data collected from the Hydrometeorology Testbed (HMT) in orographic terrain of California are used to demonstrate the methodology. The quality control and hydrometeor classification are specifically developed for X-band applications, which use a 'fuzzy logic' technique constructed from the magnitude of the copolar correlation coefficient and the texture of differential propagation phase. In addition, an improved specific differential phase retrieval and rainfall estimation method are also applied. The specific differential phase estimation is done for both the melting region and rain region, where it uses a conventional filtering method for the melting region and a self-consistency-based method that distributes the total differential phase consistent with the reflectivity factor for the rain region. Based on the specific differential phase, rainfall estimations were computed using data obtained from the NOAA polarimetric X-band radar for hydrometeorology (HYDROX) and evaluated using HMT rain gauge observations. The results show that the methodology works well at capturing the high-frequency rainfall variations for the events analyzed herein and can be useful for mountainous terrain applications. [ABSTRACT FROM AUTHOR]

Radar refractivity retrievals can capture near-surface humidity changes, but noisy phase changes of the ground clutter returns limit the accuracy for both klystron- and magnetron-based systems. Observations with a C-band (5.6 cm) magnetron weather radar indicate that the correction for phase changes introduced by local oscillator frequency changes leads to refractivity errors no larger than 0.25 N units: equivalent to a relative humidity change of only 0.25% at 20°C. Requested stable local oscillator (STALO) frequency changes were accurate to 0.002 ppm based on laboratory measurements. More serious are the random phase change errors introduced when targets are not at the range-gate center and there are changes in the transmitter frequency (Δ fTx) or the refractivity (Δ N). Observations at C band with a 2-μs pulse show an additional 66° of phase change noise for a Δ fTx of 190 kHz (34 ppm); this allows the effect due to Δ N to be predicted. Even at S band with klystron transmitters, significant phase change noise should occur when a large Δ N develops relative to the reference period [e.g., ~55° when Δ N = 60 for the Next Generation Weather Radar (NEXRAD) radars]. At shorter wavelengths (e.g., C and X band) and with magnetron transmitters in particular, refractivity retrievals relative to an earlier reference period are even more difficult, and operational retrievals may be restricted to changes over shorter (e.g., hourly) periods of time. Target location errors can be reduced by using a shorter pulse or identified by a new technique making alternate measurements at two closely spaced frequencies, which could even be achieved with a dual-pulse repetition frequency (PRF) operation of a magnetron transmitter. [ABSTRACT FROM AUTHOR]

This paper presents an analysis of a hail event that occurred 27 May 2012 over Brignoles, located in southeastern France. The event was observed by an X-band polarimetric radar located in Mont Maurel, 75 km northeast of the hailstorm. Lightning data from the French national network (owned and operated by Météorage) are also used in the study. The analysis highlights that the lightning and radar data provide complementary information that may allow a better microphysical interpretation of the hailstorm and potentially increase the probability of its detection. [ABSTRACT FROM AUTHOR]

HF radar data are often collected for time periods that are optimized for current measurement applications where, in many cases, very high temporal resolution is needed. Previous work has demonstrated that this does not provide sufficient averaging for robust wave measurements to be made. It was shown that improvements could be made by averaging the radar data for longer time periods. HF radar provides measurements over space as well as in time, so there is also the possibility to average in space. However, the radar data are correlated in space because of the range and azimuth processing. The implications of this are discussed and estimates of the impact on the reduction in variance in the radar Doppler spectral estimates are obtained. Spatial inhomogeneities and temporal nonstationarity in the ocean wave field itself also need to be taken into account. It is suggested that temporal averaging over periods of up to one hour and spatial averaging over 9-25 nearest neighbors may be suitable, and these will be explored in later work. [ABSTRACT FROM AUTHOR]

Sea surface height (SSH) measurements provided by pulse-limited radar altimeters are one-dimensional profiles along the satellite's nadir track, with no information whatsoever in the cross-track direction. The anisotropy of resulting SSH profiles is the most limiting factor of mesoscale SSH maps that merge the 1D profiles. This paper explores the potential of the cross-track slope derived from the Cryosphere Satellite-2 ( CryoSat-2)'s synthetic aperture radar interferometry (SARin) mode to increase the resolution of mesoscale fields in the cross-track direction. Through idealized 1D simulations, this study shows that it is possible to exploit the dual SARin measurement (cross-track slope and SSH profile) in order to constrain mesoscale mapping in the cross-track direction. An error-free SSH slope allows a single SARin instrument to recover almost as much SSH variance as two coordinated altimeters. Noise-corrupted slopes can also be exploited to improve the mapping, and a breakthrough is observed for SARin errors ranging from 1 to 5 μrad for 150-km-radius features in strong currents, and 0.1-0.5 μrad for global mesoscale. Although only limited experiments might be possible with the error level of current CryoSat-2 data, this paper shows the potential of the SAR interferometry technology to reduce the anisotropy of altimeter measurements if the SARin error is significantly reduced in the future, and in particular in the context of a prospective SARin demonstrator optimized for oceanography. [ABSTRACT FROM AUTHOR]

An X-band polarimetric radar was deployed in the eastern Swiss Alps at an altitude of 2133 m. Radar measurements were complemented with several weather stations deployed in an altitude range from 1500 to 3100 m as well as with a fixed GPS ground station that was used to infer integrated water vapor estimates. Around 8000 vertical profiles of polarimetric radar observables above the melting layer collected during two months are analyzed. First, the behavior of the mean profiles of reflectivity at horizontal polarization Zh, differential reflectivity Zdr, copolar cross correlation ρhv, and specific differential phase shift Kdp are interpreted from a microphysical point of view. It is shown that the whole evolution of snowflakes, from pristine crystals at temperatures around −30°C to dendritic crystals around −15°C, to large aggregates around 0°C, is well captured by the polarimetric radar variables. In a second step, the profiles are analyzed as functions of high and low water vapor and snow accumulation conditions. It is found that the vertical profiles of polarimetric radar variables have distinct features in low versus high water vapor conditions. High water vapor conditions appear to favor the occurrence of crystal aggregates at high altitudes/low temperatures. It is shown with a hydrometeor identification scheme that graupel-like particles are found to be dominant right above the melting layer for snow events with high accumulation intensities. The present analyses show that measurements from X-band dual-polarization radar can be useful to characterize the dominant microphysical processes during precipitation in mountainous regions. [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]

The estimation of the drop size distribution parameter [median volume diameter ( D0)] and rain rate ( R) from the Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) as well as from combined PR-TRMM Microwave Imager (TMI) algorithms are considered in this study for two TRMM satellite overpasses near the Kwajalein Atoll. An operational dual-polarized S-band radar (KPOL) located in Kwajalein is central as the only TRMM ground validation site for measurement of precipitation over the open ocean. The accuracy of the TRMM PR in retrieving D0 and R is better for precipitation over the ocean based on a more stable surface reference technique for estimating the path-integrated attenuation. Also, combined PR-TMI methods are more accurate over the open ocean because of better knowledge of the surface microwave emissivity. Using Zh (horizontal polarized radar reflectivity) and Zdr (differential reflectivity) data for the two TRMM overpass events over Kwajalein, D0 and R from KPOL are retrieved. Herein, the main objective is to see if the D0 retrieved from either PR or the combined PR-TMI algorithms are in agreement with KPOL-derived values. Also, the variation of D0 versus R is compared for convective rain pixels from KPOL, PR, and PR-TMI. It is shown that the PR-TMI optimal estimation scheme does indeed adjust the D0 in the 'correct' direction, on average, from the a priori state if the KPOL data are considered to be the ground truth. This correct adjustment may be considered as evidence of the value added by the TMI brightness temperatures in the combined PR-TMI variational scheme, at least for the two overpass events considered herein. [ABSTRACT FROM AUTHOR]

Retrieving atmospheric refractivity profiles from the sea surface backscattered radar clutter is known as the refractivity-from-clutter (RFC) technique. Because the relationship between refractivity and radar sea clutter is clearly nonlinear and ill posed, it is difficult to get analytical solutions according to current theories. Previous works treat this problem as a model parameter estimation issue and some optimization algorithms are selected to get approximate solutions. Two main factors that limit the accuracy of the estimation are that 1) the refractive environments are described by using some idealized refractivity parameter models that cannot describe the exact information of the refractivity profile, and 2) accurate modeling of the sea surface radar cross section (RCS) is very difficult. Rather than estimating a few model parameters, this paper puts forward possibilities of using the variational adjoint approach to jointly retrieve the every-height refractivity values and sea surface RCS using radar clutter data. The derivation of the adjoint model is accomplished by an analytical transformation of the parabolic equation (PE) in the continuous domain. Numerical simulations including range-independent and range-dependent RCS cases are presented to demonstrate the ability of this method for RFC estimations. Making use of the refractivity retrievals, propagation loss predictions are also presented. [ABSTRACT FROM AUTHOR]

This paper presents the sensing aspects and performance evaluation of the quantitative precipitation estimation (QPE) system in an X-band dual-polarization radar network developed by the Collaborative Adaptive Sensing of the Atmosphere (CASA) Engineering Research Center. CASA's technology enables precipitation observation close to the ground and QPE is one of the important applications. With expanding urbanization all over the world, vulnerability to floods has increased from intense rainfall such as urban flash floods. The QPE products that are derived at high spatiotemporal resolution, which is enabled by the deployment of a dense radar network, have the potential to improve the prediction of flash-flooding threats when coupled with hydrological models. Derivation of QPE from radar observations is a challenging process, in which the use of dual-polarization radar variables is advantageous. At X band, the specific differential propagation phase ( Kdp) between the orthogonal linear polarization states is particularly appealing. The Kdp field is robustly acquired using an adaptive estimation method, and a simple R( Kdp) relation is used to perform precipitation estimation in this X-band radar network. Radar observations and QPE from multiyear field experiments are used to demonstrate the performance of rainfall estimation from the single-parameter Kdp-based rainfall product. The operational feasibility of radar QPE using an X-band radar network is critically assessed. [ABSTRACT FROM AUTHOR]

Three long-range (5 MHz) Coastal Ocean Dynamics Application Radar (CODAR) SeaSonde HF radars overlooking an array of as many as eight moored acoustic Doppler current profilers (ADCPs) have operated on the West Florida Shelf since September 2003 for the purpose of observing the coastal ocean currents. HF radar performance on this low-energy (currents and waves) continental shelf is evaluated with respect to data returns, the rms differences between the HF radar and the ADCP radial currents, bearing offsets, and radial velocity uncertainties. Possible environmental factors affecting the HF radar performance are discussed, with the findings that both the low-energy sea state and the unfavorable surface wave directions are the main limiting factors for these HF radar observations of currents on the WFS. Despite the challenge of achieving continuous backscatter from this low-energy environment, when acquired the data quality is good in comparison with the ADCP measurements. The rms differences range from 6 to 10 cm s−1 for hourly and from 3 to 6 cm s−1 for 36-h low-pass-filtered radial currents, respectively. Bearing offsets are in the range from −15° to +9°. Coherent variations of the HF radar and ADCP radial currents are seen across both tidal and subtidal frequency bands. By examining the HF radar radial velocities at low wave energy, it is found that the data returns decrease rapidly for significant wave heights smaller than 1 m, and that the rms differences between the HF radar and ADCP radials are degraded when the significant wave height is smaller than 0.3 m. [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 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]

A dense weather radar network is an emerging concept advanced by the Engineering Research Center for Collaborative Adaptive Sensing of the Atmosphere (CASA). In a weather radar environment, the specific radar units employed and the network topology will influence the characteristics of the data obtained. To define this, a general framework is developed to describe the radar network space, and formulations are obtained that can be used for weather radar network characterization. The models developed are useful for quantifying and comparing the performance of different weather radar networks. Starting with system characteristics that are used to specify individual radars, a theoretical basis is developed to extend the concept to network configurations of interest. A general network elemental cell is defined and employed as the parameterized domain over which different coverage aspects (such as detection sensitivity, beam size, and minimum beam height) are studied using analytical tools developed in the paper. Other important parameters are the number of different radars with overlapping coverage at a given point in the network domain and the coverage area and number of radars of a network and its elemental cells. A combination of analytical and numerically derived expressions is employed to obtain these parameters for several configurations. The radar network characterization tools developed are applied to the comparison of individual radar and networked radar configurations of interest. The values used in the calculations illustrate the CASA Integrated Project 1 (IP1) radar network and are compared to other radar systems. [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 system for reflectivity and attenuation retrieval for rain medium in a networked radar environment is described. Electromagnetic waves backscattered from a common volume in networked radar systems are attenuated differently along the different paths. A solution for the specific attenuation distribution is proposed by solving the integral equation for reflectivity and attenuation. The set of governing integral equations describing the backscatter and propagation of common resolution volume are solved simultaneously with constraints on total path attenuation. The proposed algorithm is evaluated based on simulated X-band radar observations synthesized from S-band measurements collected by the Colorado State University–University of Chicago–Illinois State Water Survey (CSU–CHILL) radar. Retrieved reflectivity and specific attenuation using the proposed method show good agreement with simulated reflectivity and specific attenuation. Preliminary demonstration of the network-based retrieval using data from the Center for Collaborative Adaptive Sensing of the Atmosphere (CASA) IP-1 radar network are also presented. [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]

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]

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]

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]

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]

Observations of raindrop size distributions (DSDs) have validated the use of three-parameter distribution functions in representing the observed spectra. However, dual-frequency radar measurements are limited to retrieving two independent parameters of the DSD, thus requiring a constraint on a three-parameter distribution. In this study, disdrometer observations from a variety of climate regions are employed to develop constraints on the gamma distribution that are optimized for dual-frequency radar rainfall retrievals. These observations are composited by reflectivity, and then gamma parameters are fit to the composites. The results show considerable variability in shape parameter between regions and within a region at different reflectivities. Most notable is that oceanic regions exhibit maxima in shape parameter at 13.6-GHz reflectivities between 40 and 50 dBZ, in contrast to continental regions. The shape parameter and slope parameter of all composite DSDs are poorly correlated. Thus, constraints of a constant shape parameter or shape parameter–slope parameter relationship are inadequate to represent the observed variability. However, the shape and slope parameters are highly correlated at a given reflectivity. Constraints of a fixed shape parameter and relationships between a shape parameter m and slope parameter Λ, both of which are given as functions of 13.6-GHz reflectivity, are applied to retrieve rain rate, liquid water content, and mean mass diameter from the composites. The m–Λ relationships perform best at high reflectivity (dBZ13.6 > 35), whereas the fixed shape parameter generally results in lower error at medium and low reflectivities (dBZ13.6 < 35). All calculations have been made under the assumption that the reflectivity measurements have been corrected for attenuation. [ABSTRACT FROM AUTHOR]

Dual-wavelength ratio (DWR) techniques offer the prospect of producing high-resolution mapping of cloud microphysical properties, including retrievals of cloud liquid water content (LWC) from reflectivity measured by millimeter-wavelength radars. Unfortunately, noise and artifacts in the DWR require smoothing to obtain physically realistic values of LWC with a concomitant loss of resolution. Factors that cause inaccuracy in the retrieved LWC include uncertainty in gas and liquid water attenuation coefficients, Mie scattering due to large water droplets or ice particles, corruption of the radar reflectivities by noise and nonatmospheric returns, and artifacts due to mismatched radar illumination volumes. The error analysis presented here consists of both analytic and heuristic arguments; it is illustrated using data from the Mount Washington Icing Sensors Project (MWISP) and from an idealized simulation. In addition to offering insight into design considerations for a DWR system, some results suggest methods that may mitigate some of these sources of error for existing systems and datasets. [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 source of clear-air reflectivity from operational and research meteorological radars has been a subject of much debate and study over the entire history of radar meteorology. Recent studies have suggested that bird migrations routinely contaminate wind profiles obtained at night, while historical studies have suggested insects as the main source of such nocturnal clear-air echoes. This study analyzes two cases of nocturnal clear-air return using data from operational Weather Surveillance Radar-1988 Doppler (WSR-88D) and X- and W-band research radars. The research radars have sufficient resolution to resolve the echo as point targets in some cases. By examining the radar cross section of the resolved point targets, and by determining the target density, it is found for both cases of nocturnal clear-air echoes that the targets are almost certainly insects. The analysis of the dependence of the echo strength on radar wavelength also supports this conclusion. [ABSTRACT FROM AUTHOR]

A skill analysis of the Multiple Signal Characterization (MUSIC) algorithm used in compact-antenna-style HF radar ocean current radial velocity/bearing determination is performed using simulation. The simulation is based upon three collocated antennas (two cross loops and a monopole with ideal gain patterns) in a geometry similar to the 25-MHz SeaSonde HF radar commercially available from Coastal Ocean Dynamics Applications Radar (CODAR) Ocean Sensors, Palo Alto, California. The simulations consider wind wave/current scenarios of varying complexity to provide insight to the accuracy of surface current retrievals and the inherent limitations of the technique, with a focus on the capabilities of the MUSIC algorithm itself. The influence of second-order scatter, interference, and stationary target scatter are not considered. Simple error reduction techniques are explored and their impacts quantified to aid in operational system configuration and encourage areas of further research. Increases in skill between 55% and 100% using spatial averaging, and between 14% and 33% using temporal averaging, are realized, highlighting the utility of these techniques. When these error-flagging and averaging techniques are employed, individual range cell skill metrics are found to be as high as 0.94 for simple currents at a high signal-to-noise ratio (SNR), while more complex currents achieve a maximum skill metric of 0.72 for the same SNR. These simulations, conducted under ideal conditions, provide insight to understanding the variables, which influence the accuracy of surface currents retrieved using MUSIC. [ABSTRACT FROM AUTHOR]

To assess the spatial structures and temporal evolutions of distinct physical processes on the West Florida Shelf, patterns of ocean current variability are extracted from a joint HF radar and ADCP dataset acquired from August to September 2003 using Self-Organizing Map (SOM) analyses. Three separate ocean–atmosphere frequency bands are considered: semidiurnal, diurnal, and subtidal. The currents in the semidiurnal band are relatively homogeneous in space, barotropic, clockwise polarized, and have a neap-spring modulation consistent with semidiurnal tides. The currents in the diurnal band are less homogeneous, more baroclinic, and clockwise polarized, consistent with a combination of diurnal tides and near-inertial oscillations. The currents in the subtidal frequency band are stronger and with more complex patterns consistent with wind and buoyancy forcing. The SOM is shown to be a useful technique for extracting ocean current patterns with dynamically distinctive spatial and temporal structures sampled by HF radar and supporting in situ measurements. [ABSTRACT FROM AUTHOR]

A polarimetric method is devised to correct for attenuation effects at C band on reflectivity ZH and differential reflectivity ZDR measurements. An operational cross-correlation analysis is used to derive advection vectors and to displace echoes over a 5-min time step. These advected echoes are then compared with observations valid at the same time. The method assumes that the mean change in the intrinsic ZH and ZDR over a 5-min period when considering 1–2 h of observations over the entire radar umbrella is approximately zero. Correction coefficients are retrieved through the minimization of a cost function that links observed decreases in ZH and ZDR due to attenuation effects with increases in differential phase shift (ΦDP). The retrieved coefficients are consistent with published values for the typical ranges of temperatures and drop sizes encountered at midlatitudes, even when Mie scattering effects are present. Measurements of ZH and ZDR corrected using retrieved coefficients are compared with raw measurements and to measurements adjusted by mean coefficients found in the literature. The empirical retrieval method shows improvement over using mean correction coefficients based on comparisons of ZH from neighboring, unattenuated radars, disdrometer measurements, and analysis of ZH and ZDR as a function of ΦDP. [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]

Because echoes caused by nonmeteorological targets significantly affect radar scans, contaminated bins must be identified and eliminated before precipitation can be quantitatively estimated from radar measurements. Under mean propagation conditions, clutter echoes (mainly caused by targets such as mountains or large buildings) can be found in almost fixed locations. However, in anomalous propagation conditions, new clutter echoes may appear (sometimes over the sea), and they may be difficult to distinguish from precipitation returns. Therefore, an automatic algorithm is needed to identify clutter on radar scans, especially for operational uses of radar information (such as real-time hydrology). In this study, a new algorithm is presented based on fuzzy logic, using volumetric data. It uses some statistics to highlight clutter characteristics (namely, shallow vertical extent, high spatial variability, and low radial velocities) to output a value that quantifies the possibility of each bin being affected by clutter (in order to remove those in which this factor exceeds a certain threshold). The performance of this algorithm was compared against that of simply removing mean clutter echoes. Satisfactory results were obtained from an exhaustive evaluation of this algorithm, especially in those cases in which anomalous propagation played an important role. [ABSTRACT FROM AUTHOR]