A New Technique to Categorize and Retrieve the Microphysical Properties of Ice Particles above the Melting Layer Using Radar Dual-Polarization Spectral Analysis

Spek, A; Unal, C.M.H.; Moisseev, Dmitri; Russchenberg, H.W.J.; Chandrasekar, V.; Dufournet, Y.

doi:10.1175/2007jtecha944.1

Cited by 35 publications

(46 citation statements)

References 30 publications

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“…Aggregates of these crystals can easily exceed 2 cm, which is beyond our model's maximum diameter. However, simulated snowflake D MIN and D 0 values agree well with observations (Locatelli and Hobbs 1974;Lo and Passarelli 1982;Barthazy et al 1988;Herzegh and Jameson 1992;Vivekanandan et al 1994;Spek et al 2008). Our simulations attempted to account for aggregation or consumption of many smaller-sized crystals into larger ones, which produces flatter aggregate PSDs compared to that of their pristine component crystals (Spek et al 2008;Lo and Passarelli 1982;Kennedy and Rutledge 2011).…”

Section: ) Dry Aggregatessupporting

confidence: 70%

“…The particle size distribution (PSD), D MIN , D MAX , diameter interval (DD), number concentration (N 0 or N W ), slope (l), and functional shape (m) are parameterized, from which we calculate D 0 (median diameter of the PSD). To represent the natural variability of precipitation in turbulent background flow, all hydrometeors are assumed to have a Gaussian distribution of canting angles about a mean (u m ) of zero (Hendry et al 1976;Beard and Jameson 1983;Spek et al 2008). Then a certain standard deviation of the canting angle (s) from zero is implemented to represent fluttering or tumbling.…”

Section: Electromagnetic Scattering Simulation Methodology a T-matrimentioning

confidence: 99%

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A Dual-Polarization Radar Hydrometeor Classification Algorithm for Winter Precipitation

Thompson

Rutledge

Dolan

et al. 2014

Journal of Atmospheric and Oceanic Technology

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101

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The purpose of this study is to demonstrate the use of polarimetric observations in a radar-based winter hydrometeor classification algorithm. This is accomplished by deriving bulk electromagnetic scattering properties of stratiform, cold-season rain, freezing rain, sleet, dry aggregated snowflakes, dendritic snow crystals, and platelike snow crystals at X-, C-, and S-band wavelengths based on microphysical theory and previous observational studies. These results are then used to define the expected value ranges, or membership beta functions, of a simple fuzzy-logic hydrometeor classification algorithm. To test the algorithm's validity and robustness, polarimetric radar data and algorithm output from four unique winter storms are investigated alongside surface observations and thermodynamic soundings. This analysis supports that the algorithm is able to realistically discern regions dominated by wet snow, aggregates, plates, dendrites, and other small ice crystals based solely on polarimetric data, with guidance from a melting-level detection algorithm but without external temperature information. Temperature is still used to distinguish rain from freezing rain or sleet below the radar-detected melting level. After appropriate data quality control, little modification of the algorithm was required to produce physically reasonable results on four different radar platforms at X, C, and S bands. However, classification seemed more robust at shorter wavelengths because the specific differential phase is heavily weighted in ice crystal classification decisions. It is suggested that parts, or all, of this algorithm could be applicable in both operational and research settings.

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Section: ) Dry Aggregatessupporting

confidence: 70%

Section: Electromagnetic Scattering Simulation Methodology a T-matrimentioning

confidence: 99%

A Dual-Polarization Radar Hydrometeor Classification Algorithm for Winter Precipitation

Thompson

Rutledge

Dolan

et al. 2014

Journal of Atmospheric and Oceanic Technology

Self Cite

101

View full text Add to dashboard Cite

show abstract

“…Advantages of such a representation have been shown for weather radar applications (Spek et al, 2008). Before the calculation of polarimetric parameters the elements of the coherency matrix B(ω k ) were corrected for the effect of differential amplification in the horizontal and vertical channels.…”

Section: Correction Of the Coherency Matrix For Differences Of Channelsmentioning

confidence: 99%

Cloud radar with hybrid mode towards estimation of shape and orientation of ice crystals

et al. 2016

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Abstract. This paper is devoted to the experimental quantitative characterization of the shape and orientation distribution of ice particles in clouds. The characterization is based on measured and modeled elevation dependencies of the polarimetric parameters differential reflectivity and correlation coefficient. The polarimetric data are obtained using a newly developed 35 GHz cloud radar MIRA-35 with hybrid polarimetric configuration and scanning capabilities. The full procedure chain of the technical implementation and the realization of the setup of the hybrid-mode cloud radar for the shape determination are presented. This includes the description of phase adjustments in the transmitting paths, the introduction of the general data processing scheme, correction of the data for the differences of amplifications and electrical path lengths in the transmitting and receiving channels, the rotation of the polarization basis by 45 • , the correction of antenna effects on polarimetric measurements, the determination of spectral polarimetric variables, and the formulation of a scheme to increase the signal-to-noise ratio. Modeling of the polarimetric variables is based on existing backscattering models assuming the spheroidal representation of cloud scatterers. The parameters retrieved from the model are polarizability ratio and degree of orientation, which can be assigned to certain particle orientations and shapes. The developed algorithm is applied to a measurement of the hybridmode cloud radar taken on 20 October 2014 in Cabauw, the Netherlands, in the framework of the ACCEPT (Analysis of the Composition of Clouds with Extended Polarization Techniques) campaign. The case study shows the retrieved polarizability ratio and degree of orientation of ice particles for a cloud system of three cloud layers at different heights. Retrieved polarizability ratios are 0.43, 0.85, and 1.5 which correspond to oblate, quasi-spherical, and columnar ice particles, respectively. It is shown that the polarizability ratio is useful for the detection of aggregation/riming processes. The orientation of oblate and prolate particles is estimated to be close to horizontal while quasi-spherical particles were found to be more randomly oriented.

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“…New retrieval techniques, which are using the measurement of this spectral polarimetric parameter in the case of slant profiling, have been recently proposed. The possibility to retrieve two particle size distributions (plates and aggregates) from monomodal Doppler spectra above the melting layer is investigated in Spek et al (2008). The raindrop size distribution is obtained without assumption on its shape after deconvolution of the Doppler spectrum in Moisseev and Chandrasekar (2007).…”

Section: Clutter-suppression Technique Based On the Spectral Differenmentioning

confidence: 99%

“…The Doppler velocity is negative when the targets approach the radar. High Doppler resolution spectral polarimetric measurements are necessary for cloud microphysical retrievals (Spek et al 2008). In that case, the ground clutter Doppler spectrum may consist of 13 Doppler bins with a Doppler resolution of 3 cm s…”

Section: A Comparison Of Ground Cluttermentioning

confidence: 99%

Spectral Polarimetric Radar Clutter Suppression to Enhance Atmospheric Echoes

Unal

2009

Journal of Atmospheric and Oceanic Technology

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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 (08-908). 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).

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A New Technique to Categorize and Retrieve the Microphysical Properties of Ice Particles above the Melting Layer Using Radar Dual-Polarization Spectral Analysis

Cited by 35 publications

References 30 publications

A Dual-Polarization Radar Hydrometeor Classification Algorithm for Winter Precipitation

A Dual-Polarization Radar Hydrometeor Classification Algorithm for Winter Precipitation

Cloud radar with hybrid mode towards estimation of shape and orientation of ice crystals

Spectral Polarimetric Radar Clutter Suppression to Enhance Atmospheric Echoes

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