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The raindrop size distribution (DSD) is vital for applications such as quantitative precipitation estimation, understanding microphysical processes, and validation/improvement of two-moment bulk microphysical schemes. We trace the history of the DSD representation and its linkage to polarimetric radar observables from functional forms (exponential, gamma, and generalized gamma models) and its normalization (un-normalized, single/double-moment scaling normalized). The four-parameter generalized gamma model is a good candidate for the optimal representation of the DSD variability. A radar-based disdrometer was found to describe the five archetypical shapes (from Montreal, Canada) consisting of drizzle, the larger precipitation drops and the ‘S’-shaped curvature that occurs frequently in between the drizzle and the larger-sized precipitation. Similar ‘S’-shaped DSDs were reproduced by combining the disdrometric measurements of small-sized drops from an optical array probe and large-sized drops from 2DVD. A unified theory based on the double-moment scaling normalization is described. The theory assumes the multiple power law among moments and DSDs are scaling normalized by the two characteristic parameters which are expressed as a combination of any two moments. The normalized DSDs are remarkably stable. Thus, the mean underlying shape is fitted to the generalized gamma model from which the ‘optimized’ two shape parameters are obtained. The other moments of the distribution are obtained as the product of power laws of the reference moments M3 and M6 along with the two shape parameters. These reference moments can be from dual-polarimetric measurements: M6 from the attenuation-corrected reflectivity and M3 from attenuation-corrected differential reflectivity and the specific differential propagation phase. Thus, all the moments of the distribution can be calculated, and the microphysical evolution of the DSD can be inferred. This is one of the major findings of this article. 

Recent studies revealed that scattering calculations at weather radar frequencies using individual drop shapes result in better agreement between simulated and measured polarimetric weather radar parameters, than if established rotational symmetric shape models are used. In the present work, thousands of individual rain drops that were detected with a 2D Video Disdrometer during a tropical storm, were reconstructed and their individual radar cross sections (RCS) were calculated by automatizing a commercial EM solver software. The calculations were carried out at the common weather radar frequencies at 2.8 GHz and 5.625 GHz, both for horizontal and vertical polarization. It is evaluated to what extend the RCS can differ for drops with an equal volume, it is discussed how the scattering parameters of individual drops scale within S- and C-band frequencies, and it is shown for one sample drop what effect the modelling granularity has on determined radar cross section values. 

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 (Zh ) and differential reflectivity (Zdr ) 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 Zdr 

Abstract 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. 

Abstract. 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. 

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 >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. 

Abstract. 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 <15 % 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. 

The modern era of polarimetric radar begins with radiowave propagation research starting in the early 1970s with applications to measurement and modeling of wave attenuation in rain and depolarization due to ice particles along satellite–earth links. While there is a rich history of radar in meteorology afterWorldWar II, the impetus provided by radiowave propagation requirements led to high-quality antennas and feeds. Our journey starts by describing the key institutions and personnel responsible for development of weather radar polarimetry. The early period was dominated by circularly polarized radars for propagation research and at S band (frequency near 3 GHz) for hail detection. By the mid to late 70s, a paradigm shift occurred which led to the dominance of linear polarizations with applications to slant path attenuation prediction as well as estimation of rain rates and inferences of precipitation physics. The period from the early 1980s to 1995 can be considered as the “golden” period of rapid research that brought in meteorologists, cloud physicists, and hydrologists. This article describes the evolution of this technology from the vantage point of the authors. Their personal reflections and “behind the scenes” descriptions oer a glimpse into the inner workings at several key institutions which cannot be found elsewhere. 

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. 10m 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.