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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.

Advantages of using the generalized gamma (GG) model to represent raindrop size distribution (DSD) are discussed, especially when near-complete DSD spectra are considered. Measurements from three climatically different locations in the United States are used. The central approach is the use of double-moment normalization of the measured DSDs using two reference moments, together with an underlying or intrinsic shape, h(x), based on two shape parameters. Stability of h(x) is examined and illustrative examples are presented. It is shown that the modal GG-fitted h(x) representing semiarid and subtropical regimes (combined) provides equally good fits to those from outer rain bands (after landfall) of a Hurricane, a tropical storm, and a tropical depression event. We also show similarities with some recent studies which had used GG model and address the goodness-of-fit aspects of the model, especially when compared with the (much) more widely used standard gamma model. Finally, some applications of the modal GG-fitted h(x) in remote sensing and numerical modeling of microphysical processes are briefly considered.

Data from an S-band polarimetric radar located at a mid-latitude, coastal location are used to compare two different methods for identifying stratiform and convective rain regions. The first method entails the retrievals of two (main) parameters of the rain drop size distributions using the radar reflectivity and the differential reflectivity. The second technique is a well-known texture-based method which utilizes the radar reflectivity and its spatial variability. A widespread event with embedded line convection was used as a test case. The two methods were compared using 500 m by 500 m pixel resolution gridded data constructed from the radar volume scans. Only 12% of the pixels showed disagreement between the two methods.

The Global Precipitation Measurement mission is a major U.S.–Japan joint mission to understand the physics of the Earth’s global precipitation as a key component of its weather, climate, and hydrological systems. The core satellite carries a dual-precipitation radar and an advanced microwave imager which provide measurements to retrieve the drop size distribution (DSD) and rain rates using a Combined Radar-Radiometer Algorithm (CORRA). Our objective is to validate key assumptions and parameterizations in CORRA and enable improved estimation of precipitation products, especially in the middle-to-higher latitudes in both hemispheres. The DSD parameters and statistical relationships between DSD parameters and radar measurements are a central part of the rainfall retrieval algorithm, which is complicated by regimes where DSD measurements are abysmally sparse (over the open ocean). In view of this, we have assembled optical disdrometer datasets gathered by research vessels, ground stations, and aircrafts to simulate radar observables and validate the scattering lookup tables used in CORRA. The joint use of all DSD datasets spans a large range of drop concentrations and characteristic drop diameters. The scaling normalization of DSDs defines an intercept parameter NW, which normalizes the concentrations, and a scaling diameter Dm, which compresses or stretches the diameter coordinate axis. A major finding of this study is that a single relationship between NW and Dm, on average, unifies all datasets included, from stratocumulus to heavier rainfall regimes. A comparison with the NW–Dm relation used as a constraint in versions 6 and 7 of CORRA highlights the scope for improvement of rainfall retrievals for small drops (Dm < 1 mm) and large drops (Dm > 2 mm). The normalized specific attenuation–reflectivity relationships used in the combined algorithm are also found to match well the equivalent relationships derived using DSDs from the three datasets, suggesting that the currently assumed lookup tables are not a major source of uncertainty in the combined algorithm rainfall estimates.

Raindrop shapes and fall velocities measured by 2-dimensional video disdrometer are presented for 2 high-wind/turbulent events. The shapes were reconstructed using a relatively new technique. 10 m height wind sensor data are used to derive proxy-indicators for turbulent intensities. Our results show strong gusts, directional wind shifts (i.e. shear) and/or inferred high turbulence intensity are correlated with reduced fall speeds, reaching values ∼25 %–30 % less than the expected values, i.e. sub-terminal fall speeds. Significant percentage (20 %–35 %) of asymmetric drops (> 2 mm) deviating from the most probable axisymmetric shapes were also detected for some events with high turbulent intensities.

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.

Laboratory measurements of drop fall speeds by Gunn–Kinzer under still air conditions with pressure corrections of Beard are accepted as the “gold standard”. We present measured fall speeds of 2 and 3 mm raindrops falling in turbulent flow with 2D-video disdrometer (2DVD) and simultaneous measurements of wind velocity fluctuations using a 3D-sonic anemometer. The findings based on six rain events are, (i) the mean fall speed decreases (from the Gunn–Kinzer terminal velocity) with increasing turbulent intensity, and (ii) the standard deviation increases with increase in the rms of the air velocity fluctuations. These findings are compared with other observations reported in the literature.

On 9 September 2019, rain-bands of category-1 Hurricane Dorian passed over a ground instrumentation site in Delmarva peninsula, USA. Drop shapes derived from 2D Video Disdrometer measurements at this site were used to compute the S-band radar cross sections (RCS) for horizontal and vertical polarizations for each drop with equi-volume diameter > 2 mm. These are combined with RCS for the smaller drops assuming equilibrium shapes. Radar reflectivity (Z H ) and differential reflectivity (Z DR ) are calculated for each of the 3 minutes throughout the event which lasted for more than 8 hours. These are compared with simultaneous observations from an S-band polarimetric radar 38 km away. The comparisons highlight the impact of large amplitude drop oscillations on Z DR .

Stratiform and convective rain are associated with different microphysical processes and generally produce drop size distributions (DSDs) with different characteristics. Identification of these two rain types is also important for estimating rainfall rates from ground-based polarimetric radars as well as spaceborne radars. Previous studies have investigated DSD characteristics using disdrometer data along with radar observations and/or vertically pointing Doppler radar observations. One such study, using data from Darwin, Australia (a tropical coastal location), found that the two rain types could be separated in the NW – Dm space, where Dm is the mass-weighted mean diameter and NW is the normalized intercept parameter. Since then, the separation method has been tested using data and observations from Greeley, Colorado, a mid-latitude continental location with semi-arid climate, and Huntsville, Alabama, a sub-tropical continental location. In this paper, we investigate the same separation technique using data and observations from a mid-latitude coastal region, situated in the Delmarva peninsula in Virginia at NASA Wallops Flight Facility (WFF). Two different types of disdrometers were used to construct the full DSD spectra and the NW versus Dm based classification is compared with simultaneous observations from a S-band polarimetric radar 38 km away from the disdrometer site. Three-minute DSDs were used for the classification and RHI (range-height indicator) radar scans over the disdrometer were used for validation. Events which occurred on 14 and 16 October 2019 were chosen. Results show, surprisingly, that there was no need to modify the separation criteria from those used in Darwin, AU. Also considered were the outer rain bands of Hurricane Dorian (as Category-1) which occurred on 06 September 2019. However, in this case, it was largely stratiform rain during the major part of the storm affecting WFF. Scattering (T-matrix) calculations using the 3-minute DSD spectra were used to derive retrieval equations for NW and Dm for the S-band radar data. These were applied to the radar scans to identify convective and stratiform rain regions as well as mixed or transition regions. Chosen RHI scans from two events (14 October 2019 and 06 September 2019) will be used as illustrative examples. Vertical profiles of reflectivity, differential reflectivity and copolar correlation coefficient over the disdrometer site will be extracted to establish whether or not the melting layer can be clearly distinguished. Specific times will be chosen from the two events and compared against the disdrometer data based classification as well for those corresponding times.

The availability of high quality surface observations of precipitation and volume observations by polarimetric operational radars make it possible to constrain, evaluate, and validate numerical models with a wide variety of microphysical schemes. In this article, a novel particle-based Monte-Carlo microphysical model (called McSnow) is used to simulate the outer rain bands of Hurricane Dorian which traversed the densely instrumented precipitation research facility operated by NASA at Wallops Island, Virginia. The rain bands showed steady stratiform vertical profiles with radar signature of dendritic growth layers near &minus, 15 &deg, C and peak reflectivity in the bright band of 55 dBZ along with polarimetric signatures of wet snow with sizes inferred to exceed 15 mm. A 2D-video disdrometer measured frequent occurrences of large drops &gt, 5 mm and combined with an optical array probe the drop size distribution was well-documented in spite of uncertainty for drops &lt, 0.5 mm due to high wind gusts and turbulence. The 1D McSnow control run and four numerical experiments were conducted and compared with observations. One of the main findings is that even at the moderate rain rate of 10 mm/h collisional breakup is essential for the shape of the drop size distribution.

Hurricane rainbands are very efficient rain producers, but details on drop size distributions are still lacking. This study focuses on the rainbands of hurricane Dorian as they traversed the densely instrumented NASA precipitation-research facility at Wallops Island, VA, over a period of 8 h. Drop size distribution (DSD) was measured using a high-resolution meteorological particle spectrometer (MPS) and 2D video disdrometer, both located inside a double-fence wind shield. The shape of the DSD was examined using double-moment normalization, and compared with similar shapes from semiarid and subtropical sites. Dorian rainbands had a superexponential shape at small normalized diameter values similar to those of the other sites. NASA&rsquo, s S-band polarimetric radar performed range height-indicator (RHI) scans over the disdrometer site, showing some remarkable signatures in the melting layer (bright-band reflectivity peaks of 55 dBZ, a dip in the copolar correlation to 0.85 indicative of 12&ndash, 15 mm wet snow, and a staggering reflectivity gradient above the 0 &deg, C level of &ndash, 10 dB/km, indicative of heavy aggregation). In the rain layer at heights &lt, 2.5 km, polarimetric signatures indicated drop break-up as the dominant process, but drops as large as 5 mm were detected during the intense bright-band period.

Tropical storm Nate, which was a powerful hurricane prior to landfall along the US Gulf coast, traversed north and weakened considerably to a tropical depression as it moved near an instrumented site in Hunstville, AL. The outer rain bands lasted 18 h (03:00 to 21:00 UTC on 08 October 2017) and a 2D-video disdrometer (2DVD) captured the event which was shallow at times and indicative of pure warm rain processes. The 2DVD measurements are used for 3D reconstruction of drop shapes (including the rotationally asymmetric drops) and the drop-by-drop scattering matrix has been computed using Computer Simulation Technology integral equation solver for drop sizes &gt, 2.5 mm. From the scattering matrix elements, the polarimetric radar observables are simulated by integrating over 1 min consecutive segments of the event. These simulated values are compared with dual-polarized C-band radar data located at 15 km range from the 2DVD site to evaluate the contribution of the asymmetric drop shapes, specifically to differential reflectivity. The drop fall velocities and drop horizontal velocities in terms of magnitude and direction, all being derived from each drop image from two orthogonal cameras of the 2DVD, are also considered.

The lower-order moments of the drop size distribution (DSD) have generally been considered difficult to retrieve accurately from polarimetric radar data because these data are related to higher-order moments. For example, the 4.6th moment is associated with a specific differential phase and the 6th moment with reflectivity and ratio of high-order moments with differential reflectivity. Thus, conventionally, the emphasis has been to estimate rain rate (3.67th moment) or parameters of the exponential or gamma distribution for the DSD. Many double-moment “bulk” microphysical schemes predict the total number concentration (the 0th moment of the DSD, or M0) and the mixing ratio (or equivalently, the 3rd moment M3). Thus, it is difficult to compare the model outputs directly with polarimetric radar observations or, given the model outputs, forward model the radar observables. This article describes the use of double-moment normalization of DSDs and the resulting stable intrinsic shape that can be fitted by the generalized gamma (G-G) distribution. The two reference moments are M3 and M6, which are shown to be retrievable using the X-band radar reflectivity, differential reflectivity, and specific attenuation (from the iterative correction of measured reflectivity Zh using the total Φdp constraint, i.e., the iterative ZPHI method). Along with the climatological shape parameters of the G-G fit to the scaled/normalized DSDs, the lower-order moments are then retrieved more accurately than possible hitherto. The importance of measuring the complete DSD from 0.1 mm onwards is emphasized using, in our case, an optical array probe with 50 µm resolution collocated with a two-dimensional video disdrometer with about 170 µm resolution. This avoids small drop truncation and hence the accurate calculation of lower-order moments. A case study of a complex multi-cell storm which traversed an instrumented site near the CSU-CHILL radar is described for which the moments were retrieved from radar and compared with directly computed moments from the complete spectrum measurements using the aforementioned two disdrometers. Our detailed validation analysis of the radar-retrieved moments showed relative bias of the moments M0 through M2 was  % in magnitude, with Pearson’s correlation coefficient >0.9. Both radar measurement and parameterization errors were estimated rigorously. We show that the temporal variation of the radar-retrieved mass-weighted mean diameter with M0 resulted in coherent “time tracks” that can potentially lead to studies of precipitation evolution that have not been possible so far.

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).

We report on fall speed measurements of raindrops in light-to-heavy rain events from two climatically different regimes (Greeley, Colorado, and Huntsville, Alabama) using the high-resolution (50 µm) Meteorological Particle Spectrometer (MPS) and a third-generation (170 µm resolution) 2-D video disdrometer (2DVD). To mitigate wind effects, especially for the small drops, both instruments were installed within a 2∕3-scale Double Fence Intercomparison Reference (DFIR) enclosure. Two cases involved light-to-moderate wind speeds/gusts while the third case was a tornadic supercell and several squall lines that passed over the site with high wind speeds/gusts. As a proxy for turbulent intensity, maximum wind speeds from 10 m height at the instrumented site recorded every 3 s were differenced with the 5 min average wind speeds and then squared. The fall speeds vs. size from 0.1 to 2 and >0.7 mm were derived from the MPS and the 2DVD, respectively. Consistency of fall speeds from the two instruments in the overlap region (0.7–2 mm) gave confidence in the data quality and processing methodologies. Our results indicate that under low turbulence, the mean fall speeds agree well with fits to the terminal velocity measured in the laboratory by Gunn and Kinzer from 100 µm up to precipitation sizes. The histograms of fall speeds for 0.5, 0.7, 1 and 1.5 mm sizes were examined in detail under the same conditions. The histogram shapes for the 1 and 1.5 mm sizes were symmetric and in good agreement between the two instruments with no evidence of skewness or of sub- or super-terminal fall speeds. The histograms of the smaller 0.5 and 0.7 mm drops from MPS, while generally symmetric, showed that occasional occurrences of sub- and super-terminal fall speeds could not be ruled out. In the supercell case, the very strong gusts and inferred high turbulence intensity caused a significant broadening of the fall speed distributions with negative skewness (for drops of 1.3, 2 and 3 mm). The mean fall speeds were also found to decrease nearly linearly with increasing turbulent intensity attaining values about 25–30 % less than the terminal velocity of Gunn–Kinzer, i.e., sub-terminal fall speeds.

Precipitation plays a vital role within the Earth system [...]

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.

Tropical storm Nate, which was a powerful hurricane prior to landfall along the Alabama coast, traversed north towards our instrumented site in Hunstville, AL. The rain bands lasted 18 h and the 2D-video disdrometer (2DVD) captured the event which was shallow and indicative of pure warm rain processes. Measurements of raindrop size, shape and velocity distributions are quite rare in pure warm rain and are expected to differ from cold rain processes. In particular, asymmetric shapes due to drop oscillations and their impact on polarimetric radar signatures in warm rain have not been studied so far. Recently, the 2DVD data has been used for 3D reconstruction of asymmetric raindrop shapes but their fraction (relative to the more common oblate shapes) in warm rain has yet to be ascertained. Here we compute the scattering matrix drop-by-drop using Computer Simulation Technology integral equation solver for drop sizes>2.5 mm. From the scattering matrix elements, the polarimetric radar observables are simulated by integrating over 1 minute consecutive segments of the event. These simulated values are compared with dual-polarized C-band radar data located at 15 km range from the 2DVD site to evaluate the contribution of the asymmetric drop shapes.

A technique for separating stratiform and convective rain types using the characteristics of two of the main drop size distribution (DSD) parameters is presented. The method was originally developed based on observations from dual-frequency profiler and dual-polarization radar observations in Darwin, Australia. In this paper, we will present the testing of the method using data from 2D video disdrometers (2DVD) from two very different locations, namely, Ontario, Canada, and Huntsville, Alabama, USA. One-minute DSDs from 2DVD are used as input to a gamma-fitting procedure and our separation technique uses the fitted values of log 10 ( N W ) and D 0 (where N W is the scaling parameter and D 0 is the median volume diameter) and an “index” to quantify where the points lie in the log 10 ( N W ) versus D 0 domain. For the Ontario location, the output of the classification is compared with simultaneous observations from a collocated, vertically pointing, X-band Doppler radar. A “bright-band” detection algorithm is used to classify each height profile as either stratiform or convective, depending on whether or not a clearly defined melting layer is present at an expected height. If present, the maximum reflectivity within the melting layer and the corresponding height are determined. Similar testing is carried out for two events in Huntsville and compared with observations from a collocated UHF profiler (with Doppler capability). Additional case studies are required, but these results indicate our separation technique seems to be applicable to many different locations and climatologies based on previously published data.

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 (

Measurements using the 2-D video disdrometer (2DVD) taken during a heavy rainfall event in Huntsville, Alabama, are analysed. The 2DVD images were processed to derive the rain microstructure parameters for each individual drop, which in turn were used as input to the T-matrix method to compute the forward and back scatter amplitudes of each drop at C-band. The polarimetric radar variables were then calculated from the individual drop contribution over a finite time period, e.g., 1 min. The calculated co-polar reflectivity, differential reflectivity, specific differential propagation phase and the co-polar correlation coefficient were compared with measurements from a C-band polarimetric radar located 15 km away. An attenuation-correction method based on the specific differential propagation phase was applied to the co-polar and differential reflectivity data from the C-band radar, after ensuring accurate radar calibration. Time series comparisons of the parameters derived from the 2DVD and C-band radar data show very good agreement for all four quantities, the agreement being sometimes better than the computations using the 1-min drop size distribution and bulk assumptions on rain microstructure (such as mean shapes and model-based assumptions for drop orientation). The agreement is particularly improved in the case of co-polar correlation coefficient since this parameter is very sensitive to variation of shapes as well as orientation angles. The calculations mark the first attempt at utilizing experimentally derived "drop- by-drop" rain microstructure information to compute the radar polarimetric parameters and to demonstrate the value of utilizing the 2-D video disdrometer for studying rain microstructure under various precipitation conditions. Histograms of drop orientation angles as well as the most probable drop shapes and the corresponding variations were also derived and compared with prior results from the 80 m fall "artificial rain" experiment.

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.