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The Precipitation Occurrence Sensor System (POSS) is a small X-band Doppler radar that measures the Doppler velocity spectra from precipitation falling in a small volume near the sensor. The sensor records a 2D frequency of occurrence matrix of the velocity and power at the mode of each spectrum measured over 1 min. The centroid of the distribution of these modes, along with other spectral parameters, defines a data vector input to a multiple discriminant analysis (MDA) for classification of the precipitation type. This requires the a priori determination of a training set for different types, particle size distributions (PSDs), and wind speed conditions. A software model combines POSS system parameters, a particle scattering cross section, and terminal velocity models, to simulate the real-time Doppler signal measured by the system for different PSDs and wind speeds. This is processed in the same manner as the system hardware to produce bootstrap samples of the modal centroid distributions for the MDA training set. MDA results are compared to images from the Multi-Angle Snowflake Camera (MASC) at the MASCRAD site near Easton, Colorado, and to the CSU–CHILL X-band radar observations from Greeley, Colorado. In the four case studies presented, POSS successfully identified precipitation transitions through a range of types (rain, graupel, rimed dendrites, aggregates, unrimed dendrites). Also two separate events of hail were reported and confirmed by the images.

Commonly used disdrometers tend not to accurately measure concentrations of very small drops in the raindrop size distribution (DSD), either through truncation of the DSD at the small-drop end or because of large uncertainties on these measurements. Recent studies have shown that, as a result of these inaccuracies, many if not most ground-based disdrometers do not capture the “drizzle mode” of precipitation, which consists of large concentrations of small drops and is often separated from the main part of the DSD by a shoulder region. We present a technique for reconstructing the drizzle mode of the DSD from “incomplete” measurements in which the drizzle mode is not present. Two statistical moments of the DSD that are well measured by standard disdrometers are identified and used with a double-moment normalized DSD function that describes the DSD shape. A model representing the double-moment normalized DSD is trained using measurements of DSD spectra that contain the drizzle mode obtained using collocated Meteorological Particle Spectrometer and 2D video disdrometer instruments. The best-fitting model is shown to depend on temporal resolution. The result is a method to estimate, from truncated or uncertain measurements of the DSD, a more complete DSD that includes the drizzle mode. The technique reduces bias on low-order moments of the DSD that influence important bulk variables such as the total drop concentration and mass-weighted mean drop diameter. The reconstruction is flexible and often produces better rain-rate estimations than a previous DSD correction routine, particularly for light rain.

Two-dimensional video disdrometer (2DVD) data from a line convection rain event are analyzed using the method of moments surface integral equation (MoM-SIE) via drop-by-drop polarimetric scattering calculations at C band that are compared with radar measurements. Drop geometry of asymmetric drop shapes is reconstructed from 2DVD measurements, and the MoM-SIE model is created by meshing the surface of the drop. The differential reflectivity Zdr calculations for an example asymmetric drop are validated against an industry standard code solution at C band, and the azimuthal dependence of results is documented. Using the MoM-SIE analysis on 2DVD drop-by-drop data (also referred to as simply MoM-SIE), the radar variables [Zh, Zdr, Kdp, ρhv] are computed as a function of time (with 1-min resolution) and compared to C-band radar measurements. The importance of shape variability of asymmetric drops is demonstrated by comparing with the traditional (or “bulk”) method, which uses 1-min averaged drop size distributions and equilibrium oblate shapes. This was especially pronounced for ρhv, where the MoM-SIE method showed lowered values (dip) during the passage of the line convection consistent with radar measurements, unlike the bulk method. The MoM-SIE calculations of [Zh, Zdr, Kdp] agree very well with the radar measurements, whereas linear depolarization ratio (LDR) calculations from the drop-by-drop method are found to be larger than the values from the bulk method, which is consistent with the dip in simulated and radar-measured ρhv. Our calculations show the importance of the variance of shapes resulting from asymmetric drops in the calculation of ρhv and LDR.

We report on measurements of drop size distributions (DSD) using collocated instruments (a Droplet Measurement Technologies, Inc., Meteorological Particle Spectrometer and a 2D-video disdrometer) from two locations with different rainfall climates (Greeley, Colorado, and Huntsville, Alabama, with measurements from the latter that include the outer rainbands of Hurricane Irma). The combination of the two instruments gives what we term as the “full” DSD spectra, the shape of which generally cannot be represented by the standard gamma model, but instead requires the additional flexibility of the generalized gamma model, which includes two shape parameters (μ and c). The double-moment normalization of DSDs using the third and fourth moments is used to arrive at the intrinsic shapes of the DSD with two shape parameters that are shown to capture simultaneously the drizzle mode as well as the precipitation mode, together with a “plateau” region between the two. The estimation of μ and c is done with a global search using nonlinear least squares, and the error residuals are examined to check the sensitivity of the parameters to a preselected, allowed tolerance around the minimum error in the μ, c plane. This leads to a range of plausible fits for a given normalized DSD mainly governed by the c parameter. The stability or invariance of the shape of the normalized DSDs from the two sites is examined, and on average the shapes are similar with some variability at the large normalized diameter end that is explained by the aforementioned range of plausible fits. Heuristic goodness-of-fit methods are described that demonstrate that the generalized gamma model outperforms the standard gamma model with only one shape parameter (μ).

Dual-polarization radar rainfall estimation relationships have been extensively tested in continental and subtropical coastal rain regimes, with little testing over tropical oceans where the majority of rain on Earth occurs. A 1.5-yr Indo-Pacific warm pool disdrometer dataset was used to quantify the impacts of tropical oceanic drop-size distribution (DSD) variability on dual-polarization radar variables and their resulting utility for rainfall estimation. Variables that were analyzed include differential reflectivity Zdr; specific differential phase Kdp; reflectivity Zh; and specific attenuation Ah. When compared with continental or coastal convection, tropical oceanic Zdr and Kdp values were more often of low magnitude (−1) and Zdr was lower for a given Kdp or Zh, consistent with observations of tropical oceanic DSDs being dominated by numerous, small, less-oblate drops. New X-, C-, and S-band R estimators were derived: R(Kdp), R(Ah), R(Kdp, ζdr), R(z, ζdr), and R(Ah, ζdr), which use linear versions of Zdr and Zh, namely ζdr and z. Except for R(Kdp), convective/stratiform partitioning was unnecessary for these estimators. All dual-polarization estimators outperformed updated R(z) estimators derived from the same dataset. The best-performing estimator was R(Kdp, ζdr), followed by R(Ah, ζdr) and R(z, ζdr). The R error was further reduced in an updated blended algorithm choosing between R(z), R(z, ζdr), R(Kdp), and R(Kdp, ζdr) depending on Zdr > 0.25 dB and Kdp > 0.3° km−1 thresholds. Because of these thresholds and the lack of hail, R(Kdp) was never used. At all wavelengths, R(z) was still needed 43% of the time during light rain (R < 5 mm h−1, Zdr < 0.25 dB), composing 7% of the total rain volume. As wavelength decreased, R(Kdp, ζdr) was used more often, R(z, ζdr) was used less often, and the blended algorithm became increasingly more accurate than R(z).

Analysis of drop size distributions (DSD) measured by collocated Meteorological Particle Spectrometer (MPS) and a third-generation, low-profile, 2D-video disdrometer (2DVD) are presented. Two events from two different regions (Greeley, Colorado, and Huntsville, Alabama) are analyzed. While the MPS, with its 50-μm resolution, enabled measurements of small drops, typically for drop diameters below about 1.1 mm, the 2DVD provided accurate measurements for drop diameters above 0.7 mm. Drop concentrations in the 0.7–1.1-mm overlap region were found to be in excellent agreement between the two instruments. Examination of the combined spectra clearly reveals a drizzle mode and a precipitation mode. The combined spectra were analyzed in terms of the DSD parameters, namely, the normalized intercept parameter NW, the mass-weighted mean diameter Dm, and the standard deviation of mass spectrum σM. The inclusion of small drops significantly affected the NW and the ratio σM/Dm toward higher values relative to using the 2DVD-based spectra alone. For each of the two events, polarimetric radar data were used to characterize the variation of radar-measured reflectivity Zh and differential reflectivity Zdr with Dm from the combined spectra. In the Greeley event, this variation at S band was well captured for small values of Dm (Zdr tended to 0 dB but Zh showed a noticeable decrease with decreasing Dm. For the Huntsville event, an overpass of the Global Precipitation Measurement mission Core Observatory satellite enabled comparison of satellite-based dual-frequency radar retrievals of Dm with ground-based DSD measurements. Small differences were found between the satellite-based radar retrievals and disdrometers.

Data analyses for the mobile Iowa X-band polarimetric (XPOL) radar from a long-duration rain event that occurred during the NASA Iowa Flood Studies (IFloodS) field campaign are presented. A network of six 2D video disdrometers (2DVDs) is used to derive four rain-rate estimators for the XPOL-5 radar. The rain accumulation validations with a collocated network of twin and triple tipping-bucket rain gauges have highlighted the need for combined algorithms because no single estimator was found to be sufficient for all cases considered. A combined version of weighted and composite algorithms is introduced, including a new R(Ah, Zdr) rainfall estimator for X band, where Ah is the specific attenuation for horizontal polarization and Zdr is the differential reflectivity. Based on measurement and algorithm errors, the weights are derived to be as piecewise constant functions over reflectivity values. The weights are later turned into continuous functions using smoothing splines. A methodology to derive the weights in near–real time is proposed for the composite-weighted algorithm. Comparisons of 2-h accumulations and 8-h event totals obtained from the XPOL-5 with 12 rain gauges have shown 10%–40% improvement in normalized bias over individual rainfall estimators. The analyses have enabled the development of rain-rate estimators for the Iowa XPOL.

Comprehensive analysis of an unusual graupel-shower event recorded by an S-band polarimetric radar and two optical-imaging surface instruments is presented. The primary radar characteristic was negative differential reflectivity Zdr values along a vertical column. During the afternoon hours of 16 February 2015, a sequence of three showers that were composed primarily of small (8–15-mm diameter) graupel affected the ground instrumentation site that was established for the Multi-Angle Snowflake Camera and Radar (MASCRAD) experiment in the high plains of Colorado. While these showers passed the instrumentation site, the CSU–CHILL radar conducted high-time-resolution (~2.5-min cycle time) range–height indicator (RHI) scans from a range of 13 km. The RHI data show that the negative Zdr values extended vertically through much of the reflectivity cores, implying that the reflectivity-weighted mean axis ratios of the graupel particles in this event remained somewhat prolate throughout their lifetime. To be specific, the cores of the convective showers only extended to heights of ~3.5 km AGL and had fractionally negative (from ~−0.3 to −0.7 dB) Zdr levels in those cores. Particle-image data obtained by the MASC system and by a collocated 2D video disdrometer measured the diameters, shapes, and fall speeds of the graupel particles as they reached the surface. The graupel particles were found to be primarily of the lump type with a slightly prolate mean shape (especially for the larger-diameter particles). Microwave backscatter calculations confirm that the graupel-particle shape and orientation characteristics are consistent with the observed slightly, but consistently, negative Zdr values.

Two-dimensional video disdrometer (2DVD) data were analyzed from two equatorial Indian (Gan) and west Pacific Ocean (Manus) islands where precipitation is primarily organized by the intertropical convergence zone and the Madden–Julian oscillation (MJO). The 18 (3.5) months of 2DVD data from Manus (Gan) Island show that 1) the two sites have similar drop size distribution (DSD) spectra of liquid water content, median diameter, rain rate R, radar reflectivity z, normalized gamma number concentration Nw, and other integral rain parameters; 2) there is a robust Nw-based separation between convective (C) and stratiform (S) DSDs at both sites that produces consistent separation in other parameter spaces. The 2DVD data indicate an equatorial, maritime average C/S rainfall accumulation fraction (frequency) of 81/19 (41/59) at these locations. It is hypothesized that convective fraction and frequency estimates are slightly higher than previous radar-based studies, because the ubiquitous weak, shallow convection (

Polarimetric radar data obtained at high spatial and temporal resolutions offer a distinct advantage in estimating the spatial correlation function of drop size distribution (DSD) parameters and rain rate compared with a fixed gauge–disdrometer network. On two days during the 2011 Midlatitude Continental Convective Clouds Experiment (MC3E) campaign in Oklahoma, NASA’s S-band polarimetric radar (NPOL) performed repeated PPI scans every 40 s over six 2D video disdrometer (2DVD) sites, located 20–30 km from the radar. The two cases were 1) a rapidly evolving multicell rain event (with large drops) and 2) a long-duration stratiform rain event. From the time series at each polar pixel, the Pearson correlation coefficient is computed as a function of distance along each radial in the PPI scan. Azimuthal dependence is found, especially for the highly convective event. A pseudo-1D spatial correlation is computed that is fitted to a modified-exponential function with two parameters (decorrelation distance R0 and shape F). The first event showed significantly higher spatial variability in rain rate (shorter decorrelation distance R0 = 3.4 km) compared with the second event with R0 = 10.2 km. Further, for the second event, the spatial correlation of the DSD parameters and rain rate from radar showed good agreement with 2DVD-based spatial correlations over distances ranging from 1.5 to 7 km. The NPOL also performed repeated RHI scans every 40 s along one azimuth centered over the 2DVD network. Vertical correlations of the DSD parameters as well as the rainwater content were determined below the melting level, with the first event showing more variability compared with the second event.

A dataset containing 9637 h of two-dimensional video disdrometer observations consisting of more than 240 million raindrops measured at diverse climatological locations was compiled to help characterize underlying drop size distribution (DSD) assumptions that are essential to make precise retrievals of rainfall using remote sensing platforms. This study concentrates on the tail of the DSD, which largely impacts rainfall retrieval algorithms that utilize radar reflectivity. The maximum raindrop diameter was a median factor of 1.8 larger than the mass-weighted mean diameter and increased with rainfall rate. Only 0.4% of the 1-min DSD spectra were found to contain large raindrops exceeding 5 mm in diameter. Large raindrops were most abundant at the tropical locations, especially in Puerto Rico, and were largely concentrated during the spring, especially at subtropical locations. Giant raindrops exceeding 8 mm in diameter occurred at tropical, subtropical, and high-latitude continental locations. The greatest numbers of giant raindrops were found in the subtropical locations, with the largest being a 9.7-mm raindrop that occurred in northern Oklahoma during the passage of a hail-producing thunderstorm. These results suggest large raindrops are more likely to fall from clouds that contain hail, especially those raindrops exceeding 8 mm in diameter.

The effect of ship motion on shipborne polarimetric radar measurements is considered at C band. Calculations are carried out by (i) varying the “effective” mean canting angle and (ii) separately examining the elevation dependence. Scattering from a single oblate hydrometeor is considered at first. Equations are derived (i) to convert the measured differential reflectivity for nonzero mean canting angles to those for zero mean canting angle and (ii) to do the corresponding corrections for nonzero elevation angles. Scattering calculations are also performed using the T-matrix method with measured drop size distributions as input. Dependence on mean volume diameter is examined as well as variations of the four main polarimetric parameters. The results show that as long as the ship movement is limited to a roll of less than about 10°–15°, the effects are tolerable. Furthermore, the results from the scattering simulations have been used to provide equations for correction factors that can be applied to compensate for the “apparent” nonzero canting angles and nonzero elevation angles, so that drop size distribution parameters and rainfall rates can be estimated without any bias.

A new 10-category, polarimetric-based hydrometeor identification algorithm (HID) for C band is developed from theoretical scattering simulations including wet snow, hail, and big drops/melting hail. The HID is applied to data from seven wet seasons in Darwin, Australia, using the polarimetric C-band (C-POL) radar, to investigate microphysical differences between monsoon and break periods. Scattering simulations reveal significant Mie effects with large hail (diameter > 1.5 cm), with reduced reflectivity and enhanced differential reflectivity Zdr and specific differential phase Kdp relative to those associated with S band. Wet snow is found to be associated with greatly depreciated correlation coefficient ρhv and moderate values of Zdr. It is noted that large oblate liquid drops can produce the same electromagnetic signatures at C band as melting hail falling quasi stably, resulting in some ambiguity in the HID retrievals. Application of the new HID to seven seasons of C-POL data reveals that hail and big drops/melting hail occur much more frequently during break periods than during monsoon periods. Break periods have a high frequency of vertically aligned ice above 12 km, suggesting the presence of strong electric fields. Reflectivity and mean drop diameter D0 statistics demonstrate that convective areas in both monsoon and break periods may have robust coalescence or melting precipitation ice processes, leading to enhanced reflectivity and broader distributions of D0. Conversely, for stratiform regions in both regimes, mean reflectivity decreases below the melting level, indicative of evaporative processes. Break periods also have larger ice water path fractions, indicating substantial mixed-phase precipitation generation as compared with monsoonal periods. In monsoon periods, a larger percentage of precipitation is produced through warm-rain processes.

The accuracy of retrieving the two drop size distribution (DSD) parameters, median volume diameter (D0), and normalized intercept parameter (NW), as well as rain rate (R), from polarimetric C-band radar data obtained during a cool-season, long-duration precipitation event in Huntsville, Alabama, is examined. The radar was operated in a special “near-dwelling” mode over two video disdrometers (2DVD) located 15 km away. The polarimetric radar–based retrieval algorithms for the DSD parameters and rain rate were obtained from simulations using the 2DVD measurements of the DSD. A unique feature of this paper is the radar-based estimation of the spatial correlation functions of the two DSD parameters and rain rate that are used to estimate the “point-to-area” variance. A detailed error variance separation is performed, including the aforementioned point-to-area variance, along with variance components due to the retrieval algorithm error, radar measurement error, and disdrometer sampling error. The spatial decorrelation distance was found to be smallest for the R (4.5 km) and largest for D0 (8.24 km). For log10(NW), it was 7.22 km. The proportion of the variance of the difference between radar-based estimates and 2DVD measurements that could be explained by the aforementioned errors was 100%, 57%, and 73% for D0, log10(NW), and R, respectively. The overall accuracy of the radar-based retrievals for the particular precipitation event quantified in terms of the fractional standard deviation were estimated to be 6.8%, 6%, and 21% for D0, log10(NW), and R, respectively. The normalized bias was

As a response to extreme water shortages in southeast Queensland, Australia, brought about by reduced rainfall and increasing population, the Queensland government decided to explore the potential for cloud seeding to enhance rainfall. The Queensland Cloud Seeding Research Program (QCSRP) was conducted in the southeast Queensland region near Brisbane during the 2008/09 wet seasons. In addition to conducting an initial exploratory, randomized (statistical) cloud seeding study, multiparameter radar measurements and in situ aircraft microphysical data were collected. This comprehensive set of observational platforms was designed to improve the physical understanding of the effects of both ambient aerosols and seeding material on precipitation formation in southeast Queensland clouds. This focus on gaining physical understanding, along with the unique combination of modern observational platforms utilized in the program, set it apart from previous cloud seeding research programs. The overarching goals of the ...

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.

Rain drop size distributions retrieved from polarimetric radar measurements over regularly occurring thunderstorms over the islands north of Darwin, Australia, are used to test if aerosol contributions to the probability distributions of the drop size distribution parameters (median volume diameter and normalized intercept parameter) are detectable. The observations reported herein are such that differences in cloud properties arising from thermodynamic differences are minimized but even so may be a factor. However, there is a clear signature that high aerosol concentrations are correlated with smaller number concentrations and larger drops. This may be associated with enhanced ice multiplication processes for low aerosol concentration storms or other processes such as invigoration of the updrafts.

This note builds on prior technique development related to the classification of rain types utilizing C-band polarimetric (CPOL) radar measurements. While the prior work was preliminary and limited in scope, the authors elaborate here on the basis of the drop size distribution (DSD)-based indexing technique for rain-type classification (convective/stratiform/mixed), and place it on firmer footing by testing the methodology against texture- and disdrometer-based methods as applied to Darwin datasets. A microphysical-based methodology is attractive as it links more directly to the underlying rainfall physical processes. Statistics of the DSD parameters, namely, histograms of log10(Nw) and D0, for convective and stratiform rain types across the premonsoon buildup and monsoon regimes were derived and further separated for over land and over ocean regions. The maximum value for mean D0 (1.64 mm) and the largest histogram standard deviation (0.32 mm) occurred for convective rain over land during the buildup regime. The largest differences in D0 and NW histograms were found to be for convective rain between the buildup and monsoon regimes (independent of land or ocean areas). Stratiform rain histograms were found to be very similar during the buildup regime with little land–ocean differences. However, somewhat larger land–ocean differences were found for the monsoon stratiform rain. The main histogram characteristics of the “mixed” or “uncertain” rain type were closer to the convective rain type than to stratiform, across both regimes and land–ocean areas. Additionally, the Nw versus D0 cluster of points (mean ±1σ) for convective rain agrees very well with the previously published range of values for maritime convective (equilibrium-like) DSDs.

Comparisons are made between the reflectivity Z, median volume diameter D0, and rain rate R from a dual-frequency profiler and the C-band polarimetric radar (C-POL), which are both located near Darwin, Australia. Examples from the premonsoon “buildup” regime and the monsoon (oceanic) regime are used to illustrate the excellent agreement between the dual-profiler retrievals and the polarimetric radar-based retrievals. This work builds on similar works that were limited in scope to shallow tropical showers and predominantly stratiform rain events. The dual-frequency profiler retrievals of D0 and R herein are based on ensemble statistics, whereas the polarimetric radar retrievals are based on algorithms derived by using one season of disdrometer data from Darwin along with scattering simulations. The latest drop shape versus D relation is used as well as the canting angle distribution results obtained from the 80-m fall bridge experiment in the scattering simulations. The scatterplot of D0 from dual-frequency profiler versus Zdr measurements from C-POL is shown to be consistent not only with the theoretical simulations and prior data but also within prior predicted error bars for both stratiform rain as well as convective rain. Based on dual-frequency profiler–retrieved gamma drop size distribution parameters, a new smoothly varying “separator” indexing scheme has been developed that classifies between stratiform and convective rain types, including a continuous “transition” region between the two. This indexing technique has been applied on a number of low-elevation-angle plan position indicator (PPI) sweeps with the C-POL from the two regime examples, to construct “unconditioned” histograms of D0 in stratiform and convective rain (to within the sensitivity of the radar). With reference to the latter, it is demonstrated that the distribution of D0 is different in the buildup example than in the monsoon example, because of the differences in both the microphysical and kinematic features between the two regimes. In particular, (i) the mean D0 is significantly larger in the buildup example than in the monsoon example, irrespective of rain type; (ii) the histogram width (or standard deviation) is much larger for the buildup example than the monsoon example, irrespective of rain type; and (iii) the histogram skewness is negative for the monsoon regime example because of a lack of larger D0 values, whereas the buildup histogram is positively skewed irrespective of rain type.

Comparisons of drop shapes between measurements made using 2D video disdrometer (2DVD) and wind-tunnel experiments are presented. Comparisons are made in terms of the mean drop shapes and the axis ratio distributions. Very close agreement of the mean shapes is seen between the two sets of measurements; the same applies to the mean axis ratio versus drop diameter. Also, in both sets of measurements, an increase in the oscillation amplitudes with increasing drop diameter is observed. In the case of the 2DVD, a small increase in the skewness was also detected. Given that the two sets of measurements were conducted in very different conditions, the agreement between the two sets of data implies a certain “robustness” in the mean shape of oscillating drops that may be extended to natural raindrop oscillations, at least in steady rainfall and above the surface layer.

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.

This note reports on the use of a 2D video disdrometer to estimate the orientation of drops (>2 mm) that were generated artificially and allowed to fall 80 m from a bridge with no obstruction and under calm conditions. This experimental setup enabled a large number of drops to be generated, up to 10 mm in horizontal dimension. The distribution of the canting angles for all drops >2 mm was found to be nearly symmetric about 0° with standard deviation between 7° and 8°. From the canting angle distributions derived from the two orthogonal camera view planes, the distributions of the polar (θ) and azimuth (ϕ) angles were deduced; these two angles describe the 2D orientation of the symmetry axis. The azimuthal angle distribution was found to be nearly uniform in the range (0, 2π), whereas the distribution of pΩ(θ) = p(θ) sinθ was similar in shape to a special form of the Fisher distribution that is valid for describing the statistics on a spherical surface. The standard deviation of pΩ(θ) showed that larger drops are more stably oriented than smaller ones. This is in agreement with previous radar-based results of standard deviation of the canting angle decreasing with increasing Zdr.

Drop shapes derived from a previously conducted artificial rain experiment using a two-dimensional video disdrometer (2DVD) are presented. The experiment involved drops falling over a distance of 80 m to achieve their terminal velocities as well as steady-state oscillations. The previous study analyzed the measured axis ratios (i.e., ratio of maximum vertical to maximum horizontal chord) as a function of equivolumetric spherical drop diameter (Deq) for over 115 000 drops ranging from 1.5 to 9 mm. In this paper, the actual contoured shapes of the drops are reported, taking into account the finite quantization limits of the instrument. The shapes were derived from the fast line-scanning cameras of the 2DVD. The drops were categorized into Deq intervals of 0.25-mm width and the smoothed contours for each drop category were superimposed on each other to obtain their most probable shapes and their variations due to drop oscillations. The most probable shapes show deviation from oblate spheroids for Deq > 4 mm, the larger drops having a more flattened base, in good agreement with the equilibrium (nonoblate) shape model of Beard and Chuang. Deviations were noted from the Beard and Chuang model shapes for diameters larger than 6 mm. However, the 2DVD measurements of the most probable contour shapes are the first to validate the Beard and Chuang model shapes for large drops, and further to demonstrate the differences from the equivalent oblate shapes. The purpose of this paper is to document the differences in radar polarization parameters and the range of error incurred when using the equivalent oblate shapes versus the most probable contoured shapes measured with the 2DVD especially for drop size distributions (DSDs) with large median volume diameters (>2 mm). The measured contours for Deq > 1.5 mm were fitted to a modified conical equation, and scattering calculations were performed to derive the complex scattering amplitudes for forward and backscatter for H and V polarizations primarily at 5.34 GHz (C band) but also at 3 GHz (S band) and 9 GHz (X band). Calculations were also made to derive the relevant dual-polarization radar parameters for measured as well as model-based drop size distributions. When comparing calculations using the contoured shapes against the equivalent oblate spheroid shapes, good agreement was obtained for cases with median volume diameter (D0) less than around 2 mm. Small systematic differences in the differential reflectivity (Zdr) values of up to 0.3 dB were seen for the larger D0 values when using the oblate shapes, which can be primarily attributed to the shape differences in the resonance region, which occurs in the 5.5–7-mm-diameter range at C band. Lesser systematic differences were present in the resonance region at X band (3–4 mm). At S band, the impact of shape differences in the polarimetric parameters were relatively minor for D0 up to 2.5 mm. Unusual DSDs with very large D0 values (>3 mm) (e.g., as can occur along the leading edge of severe convective storms or aloft due localized “big drop” zones) can accentuate the Zdr difference between the contoured shape and the oblate spheroid equivalent, especially at C band. For attenuation-correction schemes based on differential propagation phase, it appears that the equivalent oblate shape approximation is sufficient using a fit to the axis ratios from the 80-m fall experiment given in this paper. For high accuracy in developing algorithms for predicting D0 from Zdr, it is recommended that the fit to the most probable contoured shapes as given in this paper be used especially at C band.

Results from an experiment to measure the drop shapes using a 2D video disdrometer (2DVD) are reported. Under calm conditions, drops were generated from a hose located on a bridge 80 m above ground, this height being sufficient to allow drop oscillations to reach a steady state. The disdrometer data had to be carefully processed so as to eliminate the drops mismatched by the instrument and to remove the system spreading function. The total number of drops analyzed was around 115 000. Their axis ratio distributions were obtained for diameters ranging from 1.5 to 9 mm. The mean axis ratio decreases with increasing drop diameter, in agreement with the upper bound of the Beard and Chuang equilibrium shape model. The inferred mode of oscillation appears to be dominated by the oblate–prolate axisymmetric mode for the diameter range of 1.5 to 9 mm. The mean axis ratio agrees well with two empirically fitted formulas reported in earlier studies. In addition, a linear fit was applied to the data for radar applications relating to rain retrievals from dual-polarization measurements. The 2DVD data taken in moderate stratiform rain were also analyzed in a similar way and the results agree with the artificially generated drop experiment, at least up to 4 mm. No data for larger diameters were available for stratiform precipitation. Finally, the fall velocity was examined in terms of drop diameter. The results closely follow an empirical formula fitted to the Gunn and Kinzer data as well as the Beard and Pruppacher data including a slight decrease in the terminal velocity with a diameter beyond 7 mm.

This article presents the data collected and analyzed using the University of Iowa’s X-band polarimetric (XPOL) radars that were part of the spring 2013 hydrology-oriented Iowa Flood Studies (IFloodS) field campaign, sponsored by NASA’s Global Precipitation Measurement (GPM) Ground Validation (GV) program. The four mobile radars have full scanning capabilities that provide quantitative estimation of the rainfall at high temporal and spatial resolutions over experimental watersheds. IFloodS was the first extensive test of the XPOL radars, and the XPOL radars demonstrated their field worthiness during this campaign with 46 days of nearly uninterrupted, remotely monitored, and controlled operations. This paper presents detailed postcampaign analyses of the high-resolution, research-quality data that the XPOL radars collected. The XPOL dual-polarimetric products and rainfall are compared with data from other instruments for selected diverse meteorological events at high spatiotemporal resolutions from unprecedentedly unique and vast data generated during IFloodS operations. The XPOL data exhibit a detailed, complex structure of precipitation viewed at multiple range resolutions (75 and 30 m). The inter-XPOL comparisons within an overlapping scanned domain demonstrate consistency across different XPOL units. The XPOLs employed a series of heterogeneous scans and obtained estimates of the meteorological echoes up to a range oversampling of 7.5 m. A finer-resolution (30 m) algorithm is described to correct the polarimetric estimates for attenuation at the X band and obtain agreement of attenuation-corrected products with disdrometers and NASA S-band polarimetric (NPOL) radar. The paper includes hardware characterization of Iowa XPOL radars conducted prior to the deployment in IFloodS following the GPM calibration protocol.