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  • Author or Editor: Peter T. May x
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Acacia S. Pepler and Peter T. May

Abstract

Rainfall estimation using polarimetric radar involves the combination of a number of estimators with differing error characteristics to optimize rainfall estimates at all rain rates. In Part I of this paper, a new technique for such combinations was proposed that weights algorithms by the inverse of their theoretical errors. In this paper, the derived algorithms are validated using the “CP2” polarimetric radar in Queensland, Australia, and a collocated rain gauge network for two heavy-rain events during November 2008 and a larger statistical analysis that is based on data from between 2007 and 2009. Use of a weighted combination of polarimetric algorithms offers some improvement over composite methods that are based on decision-tree logic, particularly at moderate to high rain rates and during severe-thunderstorm events.

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Peter T. May and Thomas D. Keenan

Abstract

Polarimetric radar data have been used to produce microphysical classifications. This kind of analysis is run in a real-time mode from several research radars, including the C-band polarimetric (C-Pol) radar in Darwin, Australia. However, these classifications have had very little systematic evaluation with independent data. Using surface data is often difficult because of sampling issues, particularly for hail. The approach taken here is to use a combination of 50- and 920-MHz wind profiler estimates of rain and hail to provide validation data for the radar pixels over the profiler. The profilers also observe signals associated with lightning, and some comparisons are made between lightning occurrence and the radar measurements of graupel. The retrievals of hail–rain mixtures are remarkably robust; there are some issues regarding other microphysical classes, however, including difficulties in detecting melting snow layers in stratiform rain. These difficulties are largely due to the resampling of the radar volume data onto a grid and to poor separation of the snow classes.

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Acacia S. Pepler, Peter T. May, and Merhala Thurai

Abstract

The algorithms used to estimate rainfall from polarimetric radar variables show significant variance in error characteristics over the range of naturally occurring rain rates. As a consequence, to improve rainfall estimation accuracy using polarimetric radar, it is necessary to optimally combine a number of different algorithms. In this study, a new composite method is proposed that weights the algorithms by the inverse of their theoretical error. A number of approaches are discussed and are investigated using simulated radar data calculated from disdrometer measurements. The resultant algorithms show modest improvement over composite methods based on decision-tree logic—in particular, at rain rates above 20 mm h−1.

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Peter T. May, Kenneth P. Moran, and Richard G. Strauch

Abstract

Temperature measurements obtained using radiosondes and Radio Acoustic Sounding Systems (RASS) are compared to assess the utility of the RASS technique for meteorological studies. The agreement is generally excellent; rms temperature differences are about 1.0°C for comparisons during a variety of meteorological conditions. Observations taken under ideal circumstances indicate that a precision of about 0.2°C is achievable with the RASS technique. A processor being designed for RASS should allow routine temperature measurements approaching this precision.

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Scott Collis, Alain Protat, Peter T. May, and Christopher Williams

Abstract

Comparisons between direct measurements and modeled values of vertical air motions in precipitating systems are complicated by differences in temporal and spatial scales. On one hand, vertically profiling radars more directly measure the vertical air motion but do not adequately capture full storm dynamics. On the other hand, vertical air motions retrieved from two or more scanning Doppler radars capture the full storm dynamics but require model constraints that may not capture all updraft features because of inadequate sampling, resolution, numerical constraints, and the fact that the storm is evolving as it is scanned by the radars. To investigate the veracity of radar-based retrievals, which can be used to verify numerically modeled vertical air motions, this article presents several case studies from storm events around Darwin, Northern Territory, Australia, in which measurements from a dual-frequency radar profiler system and volumetric radar-based wind retrievals are compared. While a direct comparison was not possible because of instrumentation location, an indirect comparison shows promising results, with volume retrievals comparing well to those obtained from the profiling system. This prompted a statistical analysis of an extended period of an active monsoon period during the Tropical Warm Pool International Cloud Experiment (TWP-ICE). Results show less vigorous deep convective cores with maximum updraft velocities occurring at lower heights than some cloud-resolving modeling studies suggest.

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Peter T. May, A. R. Jameson, Thomas D. Keenan, and Paul E. Johnston

Abstract

This paper describes the results of an experiment that combines the data from a 5-cm-wavelength polarimetric radar and multiple-frequency wind profilers to examine the polarimetric signatures associated with the microphysical structure of several relatively shallow thunderstorms and also to examine quantitative rainfall measurements made with the polarimetric radar. These shallow storms produce considerable amounts of centimeter-sized hail. The presence and size of this hail are deduced from the wind profiler data. The melting hail particles produce a distinctive polarimetric signature with large values of differential reflectivity Z DR and suppressed values of the correlation coefficient between the signals at horizontal and vertical polarization. Comparisons between the mass-weighted mean drop diameter and differential reflectivity have been performed and show reasonable agreement with theoretical expectations, although the observed Z DR are somewhat smaller than expected. This may be associated with the theoretical assumption of the Pruppacher–Beard oblateness relationship even though there is evidence to suggest that real raindrops may be less oblate on average in convective rain. Quantitative polarimetric rainfall estimators have been compared with rainfall rates derived from the profiler drop size distribution retrievals and show reasonably good agreement when reflectivity values are matched.

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Justin R. Peter, Michael J. Manton, Rodney J. Potts, Peter T. May, Scott M. Collis, and Louise Wilson

Abstract

The aim of this study is to examine the statistics of convective storms and their concomitant changes with thermodynamic variability. The thermodynamic variability is analyzed by performing a cluster analysis on variables derived from radiosonde releases at Brisbane Airport in Australia. Three objectively defined regimes are found: a dry, stable regime with mainly westerly surface winds, a moist northerly regime, and a moist trade wind regime. S-band radar data are analyzed and storms are identified using objective tracking software [Thunderstorm Identification, Tracking, Analysis, and Nowcasting (TITAN)]. Storm statistics are then investigated, stratified by the regime subperiods. Convective storms are found to form and maintain along elevated topography. Probability distributions of convective storm size and rain rate are found to follow lognormal distributions with differing mean and variance among the regimes. There was some evidence of trimodal storm-top heights, located at the trade inversion (1.5–2 km), freezing level (3.6–4 km), and near 6 km, but it was dependent on the presence of the trade inversion. On average, storm volume and height are smallest in the trade regime and rain rate is largest in the westerly regime. However, westerly regime storms occur less frequently and have shorter lifetimes, which were attributed to the enhanced stability and decreased humidity profiles. Furthermore, time series of diurnal rain rate exhibited early morning and midafternoon maxima for the northerly and trade regimes but were absent for the westerly regime. The observations indicate that westerly regime storms are primarily driven by large-scale forcing, whereas northerly and trade wind regime storms are more responsive to surface characteristics.

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Vickal V. Kumar, Alain Protat, Christian Jakob, Christopher R. Williams, Surendra Rauniyar, Graeme L. Stephens, and Peter T. May

Abstract

Cumulus parameterizations in general circulation models (GCMs) frequently apply mass-flux schemes in their description of tropical convection. Mass flux constitutes the product of the fractional area covered by cumulus clouds in a model grid box and the vertical velocity within the cumulus clouds. The cumulus area fraction profiles can be derived from precipitating radar reflectivity volumes. However, the vertical velocities are difficult to observe, making the evaluation of mass-flux schemes difficult. In this paper, the authors develop and evaluate a parameterization of vertical velocity in convective (cumulus) clouds using only radar reflectivities collected by a C-band polarimetric research radar (CPOL), operating at Darwin, Australia. The parameterization is trained using vertical velocity retrievals from a dual-frequency wind profiler pair located within the field of view of CPOL. The parametric model uses two inputs derived from CPOL reflectivities: the 0-dBZ echo-top height (0-dBZ ETH) and a height-weighted column reflectivity index (Z HWT). The 0-dBZ ETH determines the shape of the vertical velocity profile, while Z HWT determines its strength. The evaluation of these parameterized vertical velocities using (i) the training dataset, (ii) an independent wind-profiler-based dataset, and (iii) 1 month of dual-Doppler vertical velocity retrievals indicates that the statistical representation of vertical velocity is reasonably accurate up to the 75th percentile. However, the parametric model underestimates the extreme velocities. The method allows for the derivation of cumulus mass flux and its variability on current GCM scales based only on reflectivities from precipitating radar, which could be valuable to modelers.

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