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  • Author or Editor: Liang Liao x
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Liang Liao
and
Robert Meneghini

Abstract

An important objective for the dual-wavelength Ku-/Ka-band precipitation radar (DPR) that will be on board the Global Precipitation Measurement (GPM) core satellite is to identify the phase state of hydrometeors along the range direction. To assess this, radar signatures are simulated in snow and rain to explore the relation between the differential frequency ratio (DFR), defined as the difference of radar reflectivity factors between Ku and Ka bands, and the radar reflectivity factor at Ku band Z Ku for different hydrometeor types. Model simulations indicate that there is clear separation between snow and rain in the Z Ku–DFR plane assuming that the snow follows the Gunn–Marshall size distribution and rain follows the Marshall–Palmer size distribution. In an effort to verify the simulated results, the data collected by the Airborne Second-Generation Precipitation Radar (APR-2) in the Wakasa Bay Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) campaign are employed. Using the signatures of linear depolarization ratio at Ku band, the APR-2 data can be easily divided into the regions of snow, mixed phase, and rain for stratiform storms. These results are then superimposed onto the theoretical curves computed from the model in the Z Ku–DFR plane. For over 90% of the observations from a cold-season stratiform precipitation event, snow and rain can be distinguished if the Ku-band radar reflectivity exceeds 18 dBZ (the minimum detectable level of the GPM DPR at Ku band). This is also the case for snow and mixed-phase hydrometeors. Although snow can be easily distinguished from rain and melting hydrometeors by using Ku- and Ka-band radar, the rain and mixed-phase particles are not always separable. It is concluded that Ku- and Ka-band dual-wavelength radar might provide a potential means to identify the phase state of hydrometeors.

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Liang Liao
and
Robert Meneghini

Abstract

The validity of the effective dielectric constant ɛ eff for nonspherical mixed-phase particles is tested by comparing the scattering parameters of ice–water mixtures for oblate and prolate spheroids obtained from the conjugate-gradient and fast Fourier transform (CGFFT) numerical scheme with those computed from the T matrix for a homogeneous particle with the derived ɛ eff with the same size, shape, and orientation as that of the mixed-phase particle. The accuracy of the effective dielectric constant is evaluated by examining whether the scattering parameters of interest can reproduce those of the direct computations, that is, the CGFFT results. Computations have been run over a range of prolate and oblate spheroids of different axial ratios up to size parameters of 4. It is found that the effective dielectric constant, obtained from realizations of small particles, can be applied to a class of particle types if the fractional water content remains the same. Analysis of the results indicates that the effective dielectric constant approach is useful in computing radar and radiometer polarimetric scattering parameters of nonspherical mixed-phase particles.

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Liang Liao
and
Robert Meneghini

Abstract

A procedure to accurately resample spaceborne and ground-based radar data is described and then is applied to the measurements taken from the Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) and the ground-based Weather Surveillance Radar-1988 Doppler (WSR-88D or WSR) for the validation of the PR measurements and estimates. Through comparisons with the well-calibrated, nonattenuated WSR at Melbourne, Florida, for the period 1998–2007, the calibration of the PR aboard the TRMM satellite is checked using measurements near the storm top. Analysis of the results indicates that the PR, after taking into account differences in radar reflectivity factors between the PR and WSR, has a small positive bias of 0.8 dB relative to the WSR, implying a soundness of the PR calibration in view of the uncertainties involved in the comparisons. Comparisons between the PR and WSR reflectivities are also made near the surface for evaluation of the attenuation-correction procedures used in the PR algorithms. It is found that the PR attenuation is accurately corrected in stratiform rain but is underestimated in convective rain, particularly in heavy rain. Tests of the PR estimates of rainfall rate are conducted through comparisons in the overlap area between the TRMM overpass and WSR scan. Analyses of the data are made both on a conditional basis, in which the instantaneous rain rates are compared only at those pixels at which both the PR and WSR detect rain, and an unconditional basis, in which the area-averaged rain rates are estimated independently for the PR and WSR. Results of the conditional rain comparisons show that the PR-derived rain is about 9% greater and 19% less than the WSR estimates for stratiform and convective storms, respectively. Overall, the PR tends to underestimate the conditional mean rain rate by 8% for all rain categories, a finding that conforms to the results of the area-averaged rain (unconditional) comparisons.

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Kenneth Sassen
and
Liang Liao

Abstract

W-band (3.2-mm) radars are seeing increasing utilization as a result of improving microwave technologies and the increased research emphasis being given to nonprecipitating clouds. This niche is exemplified by the study of the radiatively important stratus and cirrus clouds, which essentially require the application of Rayleigh and nonspherical scattering solutions, respectively. To increase the utility of such studies, the authors provide the following relations derived from empirical and model-derived particle size distributions that rely on a combination of Rayleigh and conjugate gradient-fast Fourier transform scattering theory approaches to relate (equivalent) radar reflectivity factors (Ze ) Z (mm6 m−3) to liquid water content (LWC, g m−3) and ice water content (IWC, mg m−3): Z = (3.6/Nd )LWC1.8 for stratus clouds, where Nd (cm−3) is the droplet concentration, and IWC = 21.7 Ze 0.83 for cirrus clouds using the dielectric constant appropriate for ice, which is valid over a IWC range of 3–100 mg m−3. Sources of 95-GHz attenuation are also discussed.

In addition, radar estimates of the lidar volume extinction coefficient σ l (m−1) are derived using the exponential ice particle size distributions, yielding σ l = 6.5 × 10−4 Ze 0.86 for solid ice particles, or 9.65 × 10−4 Ze 0.81 if an ice density of 0.5 g cm−3 is used to approximate the effects of hollow ice crystals in cirrus clouds.

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Liang Liao
and
Robert Meneghini

Abstract

To overcome a deficiency in the standard Ku- and Ka-band dual-wavelength radar technique, a modified version of the method is introduced. The deficiency arises from ambiguities in the estimate of the mass-weighted diameter D m of the raindrop size distribution (DSD) derived from the differential frequency ratio (DFR), defined as the difference between the radar reflectivity factors (dB) at Ku and Ka band Z KuZ Ka. In particular, for DFR values less than zero, there are two possible solutions of D m , leading to ambiguities in the retrieved DSD parameters. It is shown that the double solutions to D m are effectively eliminated if the DFR is modified from Z KuZ Ka to Z KuγZ Ka (dB), where γ is a constant with a value less than 0.8. An optimal radar algorithm that uses the modified DFR for the retrieval of rain and D m profiles is described. The validity and accuracy of the algorithm are tested by applying it to radar profiles that are generated from measured DSD data. Comparisons of the rain rates and D m estimated from the modified DFR algorithm to the same hydrometeor quantities computed directly from the DSD spectra (or the truth) indicate that the modified DFR-based profiling retrievals perform fairly well and are superior in accuracy and robustness to retrievals using the standard DFR.

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Liang Liao
,
Robert Meneghini
, and
Ali Tokay

Abstract

A framework based on measured raindrop size distribution (DSD) data has been developed to assess uncertainties in DSD models employed in Ku- and Ka-band dual-wavelength radar retrievals. In this study, the rain rates and attenuation coefficients from DSD parameters derived by dual-wavelength algorithms are compared with those directly obtained from measured DSD spectra. The impact of the DSD gamma parameterizations on rain estimation from the Global Precipitation Measurement mission (GPM) Dual-Frequency Precipitation Radar (DPR) is examined for the cases of a fixed shape factor μ as well as for a constrained μ—that is, a μ–Λ relation (a relationship between the shape parameter and slope parameter Λ of the gamma DSD)—by using 11 Particle Size and Velocity (Parsivel) disdrometer measurements with a total number of about 50 000 one-minute spectra that were collected during the Iowa Flood Studies (IFloodS) experiment. It is found that the DPR-like dual-wavelength techniques provide fairly accurate estimates of rain rate and attenuation if a fixed-μ gamma DSD model is used, with the value of μ ranging from 3 to 6. Comparison of the results reveals that the retrieval errors from the μ–Λ relations are generally small, with biases of less than ±10%, and are comparable to the results from a fixed-μ gamma model with μ equal to 3 and 6. The DSD evaluation procedure is also applied to retrievals in which a lognormal DSD model is used.

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Liang Liao
,
Robert Meneghini
,
Lin Tian
, and
Gerald M. Heymsfield

Abstract

Simulated radar signatures within the melting layer in stratiform rain—namely, the radar bright band—are checked by means of comparisons with simultaneous measurements of the bright band made by the ER-2 Doppler radar (EDOP; X band) and Cloud Radar System (CRS; W band) airborne Doppler radars during the Cirrus Regional Study of Tropical Anvils and Cirrus Layers–Florida-Area Cirrus Experiment (CRYSTAL-FACE) campaign in 2002. A stratified-sphere model, allowing the fractional water content to vary along the radius of the particle, is used to compute the scattering properties of individual melting snowflakes. Using the effective dielectric constants computed by the conjugate gradient–fast Fourier transform numerical method for X and W bands and expressing the fractional water content of a melting particle as an exponential function in particle radius, it is found that at X band the simulated radar brightband profiles are in an excellent agreement with the measured profiles. It is also found that the simulated W-band profiles usually resemble the shapes of the measured brightband profiles even though persistent offsets between them are present. These offsets, however, can be explained by the attenuation caused by cloud water and water vapor at W band. This is confirmed by comparisons of the radar profiles made in the rain regions where the unattenuated W-band reflectivity profiles can be estimated through the X- and W-band Doppler velocity measurements. The brightband model described in this paper has the potential to be used effectively for both radar and radiometer algorithms relevant to the satellite-based Tropical Rainfall Measuring Mission and Global Precipitation Measuring Mission.

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Liang Liao
,
Robert Meneghini
,
Ali Tokay
, and
Larry F. Bliven

Abstract

The focus of this study is on the estimation of snow microphysical properties and the associated bulk parameters such as snow water content and water equivalent snowfall rate for Ku- and Ka-band dual-frequency radar. This is done by exploring a suitable scattering model and the proper particle size distribution (PSD) assumption that accurately represent, in the electromagnetic domain, the micro-/macrophysical properties of snow. The scattering databases computed from simulated aggregates for small-to-moderate particle sizes are combined with a simple scattering model for large particle sizes to characterize snow-scattering properties over the full range of particle sizes. With use of the single-scattering results, the snow retrieval lookup tables can be formed in a way that directly links the Ku- and Ka-band radar reflectivities to snow water content and equivalent snowfall rate without use of the derived PSD parameters. A sensitivity study of the retrieval results to the PSD and scattering models is performed to better understand the dual-wavelength retrieval uncertainties. To aid in the development of the Ku- and Ka-band dual-wavelength radar technique and to further evaluate its performance, self-consistency tests are conducted using measurements of the snow PSD and fall velocity acquired from the Snow Video Imager/Particle Image Probe (SVI/PIP) during the winter of 2014 at the NASA Wallops Flight Facility site in Wallops Island, Virginia.

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Robert Meneghini
,
Toshio Iguchi
,
Toshiaki Kozu
,
Liang Liao
,
Ken’ichi Okamoto
,
Jeffrey A. Jones
, and
John Kwiatkowski

Abstract

Estimates of rain rate from the precipitation radar (PR) aboard the Tropical Rainfall Measuring Mission (TRMM) satellite require a means by which the radar signal attenuation can be corrected. One of the methods available is the surface reference technique in which the radar surface return in rain-free areas is used as a reference against which the path-integrated attenuation is obtained. Despite the simplicity of the basic concept, an assessment of the reliability of the technique is difficult because the statistical properties of the surface return depend not only on surface type (land/ocean) and incidence angle, but on the detailed nature of the surface scattering. In this paper, a formulation of the technique and a description of several surface reference datasets that are used in the operational algorithm are presented. Applications of the method to measurements from the PR suggest that it performs relatively well over the ocean in moderate to heavy rains. An indication of the reliability of the results can be gained by comparing the estimates derived from different reference datasets.

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William S. Olson
,
Peter Bauer
,
Nicolas F. Viltard
,
Daniel E. Johnson
,
Wei-Kuo Tao
,
Robert Meneghini
, and
Liang Liao

Abstract

In this study, a 1D steady-state microphysical model that describes the vertical distribution of melting precipitation particles is developed. The model is driven by the ice-phase precipitation distributions just above the freezing level at applicable grid points of “parent” 3D cloud-resolving model (CRM) simulations. It extends these simulations by providing the number density and meltwater fraction of each particle in finely separated size categories through the melting layer. The depth of the modeled melting layer is primarily determined by the initial material density of the ice-phase precipitation. The radiative properties of melting precipitation at microwave frequencies are calculated based upon different methods for describing the dielectric properties of mixed-phase particles. Particle absorption and scattering efficiencies at the Tropical Rainfall Measuring Mission Microwave Imager frequencies (10.65–85.5 GHz) are enhanced greatly for relatively small (∼0.1) meltwater fractions. The relatively large number of partially melted particles just below the freezing level in stratiform regions leads to significant microwave absorption, well exceeding the absorption by rain at the base of the melting layer. Calculated precipitation backscatter efficiencies at the precipitation radar frequency (13.8 GHz) increase with particle meltwater fraction, leading to a “bright band” of enhanced radar reflectivities in agreement with previous studies. The radiative properties of the melting layer are determined by the choice of dielectric models and the initial water contents and material densities of the “seeding” ice-phase precipitation particles. Simulated melting-layer profiles based upon snow described by the Fabry–Szyrmer core-shell dielectric model and graupel described by the Maxwell-Garnett water matrix dielectric model lead to reasonable agreement with radar-derived melting-layer optical depth distributions. Moreover, control profiles that do not contain mixed-phase precipitation particles yield optical depths that are systematically lower than those observed. Therefore, the use of the melting-layer model to extend 3D CRM simulations is likely justified, at least until more-realistic spectral methods for describing melting precipitation in high-resolution, 3D CRMs are implemented.

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