Drop Size Distribution Retrieval Research Articles

An Inverse Method for Drop Size Distribution Retrieval from Polarimetric Radar at Attenuating Frequency

A method that formulates the retrieval of drop size distribution (DSD) parameters from polarimetric radar variables at attenuating frequency as the solution of an inverse problem is presented. The DSD in each radar bin is represented by a normalized Gamma distribution defined by three parameters (Dm,N0*,μ). The direct problem that describes polarimetric radar observables—scattering and propagation terms—and their dependency on DSD parameters is analyzed based on T-matrix scattering simulations. The inverse algorithm and its application to the DSD retrieval are then presented. The inverse method is applied to an African Monsoon Multidisciplinary Analysis (AMMA) field campaign that deployed an X-band dual-polarization Doppler radar and optical disdrometers in Benin, West Africa, in 2006 and 2007. The dataset is composed of X-band polarimetric radar PPIs and disdrometer data for 15 organized convective systems observed in 2006. A priori information on DSD parameters (benchmark method) is derived from the polarimetric radar observables by applying power law relationships. The proposed retrieval method of DSD parameters leads to the following results as compared to the benchmark: (i) we found a better spatial consistency of the retrieved parameters, (ii) the reconstructed polarimetric radar observables are closer to the observations, (iii) The validation with disdrometer data confirms an improved estimation of the DSD parameters.

Classification of Rainfall Types Using Parsivel Disdrometer and S-Band Polarimetric Radar in Central Korea

Tools to identify and classify stratiform and convective rains at various times of the 12 days from June 2015 to March 2016 in Jincheon, Korea, were developed by using a Parsivel disdrometer and S-band polarimetric (S-POL) radar data. Stratiform and convective rains were identified using three different methods (vertical profile of reflectivity (VPR), the method proposed by Bringi et al. (BR03), and a combination of the two (BR03-VPR)) by using a Parsivel disdrometer for its applications to radar as a reference. BR03-VPR exhibits a better classification scheme than the VPR and BR03 methods. The rain types were compared using the drop size distribution (DSD) retrieved from polarimetric variables and reflectivity only. By using the DSD variables, a new convective/stratiform classification line of the log-normalized droplet number concentration ( log 10 N w ) − median volume diameter ( D 0 ) was derived for this area to classify the rainfall types using DSD variables retrieved from the polarimetric radar. For the radar variables, the method by Steiner et al. (SHY95) was found to be the best method, with 0.00% misclassification of the stratiform rains. For the convective rains, the DSD retrieval method performed better. However, for both stratiform and convective rains, the fuzzy method performed better than the SHY95 and DSD retrieval methods.

Dual-Polarization Radar Retrievals of Coastal Pacific Northwest Raindrop Size Distribution Parameters Using Random Forest Regression

AbstractRadar retrievals of drop size distribution (DSD) parameters are developed and evaluated over the mountainous Olympic Peninsula of Washington State. The observations used to develop retrievals were collected during the 2015/16 Olympic Mountain Experiment (OLYMPEX) and included the NASA S-band dual-polarimetric (NPOL) radar and a collection of second-generation Particle Size and Velocity (PARSIVEL2) disdrometers over the windward slopes of the barrier. Nonlinear and random forest regressions are applied to the PARSIVEL2 data to develop retrievals for median volume diameter, liquid water content, and rain rate. Improvement in DSD retrieval accuracy, defined by the mean error of the retrieval relative to PARSIVEL2 observations, was achieved when using the random forest model when compared with nonlinear regression. Evaluation of disdrometer observations and the retrievals from NPOL indicate that the radar retrievals can accurately reproduce observed DSDs in this region, including the common wintertime regime of small but numerous raindrops that is important there. NPOL retrievals during the OLYMPEX period are further evaluated using two-dimensional video disdrometers (2DVD) and vertically pointing Micro Rain Radars. Results indicate that radar retrievals using random forests may be skillful in capturing DSD characteristics in the lowest portions of the atmosphere.

Applications of QC and Merged Doppler Spectral Density Data from Ka-Band Cloud Radar to Microphysics Retrieval and Comparison with Airplane in Situ Observation

The new Chinese Ka-band solid-state transmitter cloud radar (CR) uses four operational modes with different pulse widths and coherent integration and non-coherent integration numbers to meet long-term cloud measurement requirements. The CR and an instrument-equipped aircraft were used to observe clouds and precipitation on the east side of Taihang Mountain in Hebei Province in 2018. To resolve the data quality problems caused by attenuation in the precipitation area; we focused on developing an algorithm for attenuation correction based on rain drop size distribution (DSD) retrieved from the merged Doppler spectral density data of the four operational modes following data quality control (QC). After dealiasing Doppler velocity and removal of range sidelobe artifacts; we merged the four types of Doppler spectral density data. Vertical air speed and DSD are retrieved from the merged Doppler spectral density data. Finally, we conducted attenuation correction of Doppler spectral density data and recalculated Doppler moments such as reflectivity; radial velocity; and spectral width. We evaluated the consistencies of reflectivity spectra from the four operational modes and DSD retrieval performance using airborne in situ observation. We drew three conclusions: First, the four operational modes observed similar reflectivity and velocity for clouds and low-velocity solid hydrometeors; however; three times of coherent integration underestimated Doppler reflectivity spectra for velocities greater than 2 m s−1. Reflectivity spectra were also underestimated for low signal-to-noise ratios in the low-sensitivity operational mode. Second, QC successfully dealiased Doppler velocity and removed range sidelobe artifacts; and merging of the reflectivity spectra mitigated the effects of coherent integration and pulse compression on radar data. Lastly, the CR observed similar DSD and liquid water content vertical profiles to airborne in situ observations. Comparing CR and aircraft data yielded uncertainty due to differences in observation space and temporal and spatial resolutions of the data.

Seasonal Variations of Observed Raindrop Size Distribution in East China

Seasonal variations of rainfall microphysics in East China are investigated using data from the observations of a two-dimensional video disdrometer and a vertically pointing micro rain radar. The precipitation and rain drop size distribution (DSD) characteristics are revealed for different rain types and seasons. Summer rainfall is dominated by convective rain, while during the other seasons the contribution of stratiform rain to rainfall amount is equal to or even larger than that of convective rain. The mean mass-weighted diameter versus the generalized intercept parameter pairs of convective rain are plotted roughly around the “maritime” cluster, indicating a maritime nature of convective precipitation throughout the year in East China. The localized rainfall estimators, i.e., rainfall kinetic energy–rain rate, shape–slope, and radar reflectivity–rain rate relations are further derived. DSD variability is believed to be a major source of diversity of the aforementioned derived estimators. These newly derived relations would certainly improve the accuracy of rainfall kinetic energy estimation, DSD retrieval, and quantitative precipitation estimation in this specific region.

Convective–stratiform separation using video disdrometer observations in central Oklahoma – the Bayesian approach

Application of 2-Dimensional Video Disdrometer (2DVD) data, collected in central Oklahoma, to the problem of convective-stratiform rain separation is presented. The partition into convective (CO) and stratiform (ST) periods is achieved by applying a multi-variable Bayesian classification algorithm to the 2DVD dataset. It turns out that the CO-ST separation methods developed for measurements with one type of disdrometer may not work optimally on measurements with a different type of disdrometer. Similarly, single/dual parameter, or simple threshold separation methods may not be able to adequately separate CO and ST rain types. The corresponding shape-slope (μ-Λ) relations of the constrained gamma distribution are derived for these two rain classes. These constrained gamma relations are then used for rain drop size distribution (DSD) retrievals, and the results are compared with those obtained from the exponential distribution and the unified μ-Λ constraint previously proposed. It is demonstrated that the results based on the convective-stratiform separation yield more accurate DSD retrievals with respect to the exponential distribution and moderate improvements in comparison to unified μ-Λ constraint.

Microphysical retrievals from simultaneous polarimetric and profiling radar observations

Abstract. The character of precipitation detected at the surface is the final product of many microphysical interactions in the cloud above, the combined effects of which may be characterized by the observed drop size distribution (DSD). This necessitates accurate retrieval of the DSD from remote sensing data, especially radar as it offers large areal coverage, high spatial resolution, and rigorous quality control and testing. Combined instrument observations with a UHF wind profiler, an S-band polarimetric weather radar, and a video disdrometer are analyzed for two squall line events occuring during the calendar year 2007. UHF profiler Doppler velocity spectra are used to estimate the DSD aloft, and are complemented by DSDs retrieved from an exponential model applied to polarimetric data. Ground truth is provided by the disdrometer. A complicating factor in the retrieval from UHF profiler spectra is the presence of ambient air motion, which can be corrected using the method proposed by Teshiba et al. (2009), in which a comparison between idealized Doppler spectra calculated from the DSDs retrieved from KOUN and those retrieved from contaminated wind profiler spectra is performed. It is found that DSDs measured using the distrometer at the surface and estimated using the wind profiler and polarimetric weather radar generally showed good agreement. The DSD retrievals using the wind profiler were improved when the estimates of the vertical wind were included into the analysis, thus supporting the method of Teshiba et al. (2009). Furthermore, the the study presents a method of investigating the time and height structure of DSDs.

An Analysis of Errors in Drop Size Distribution Retrievals and Rain Bulk Parameters with a UHF Wind Profiling Radar and a Two-Dimensional Video Disdrometer

Abstract Vertically pointed wind profiling radars can be used to obtain measurements of the underlying drop size distribution (DSD) for a rain event by means of the Doppler velocity spectrum. Precipitation parameters such as rainfall rate, radar reflectivity factor, liquid water content, mass-weighted mean drop diameter, and median volume drop diameter can then be calculated from the retrieved DSD. The DSD retrieval process is complicated by the presence of atmospheric turbulence, vertical ambient air motion, selection of fall speed relationships, and velocity thresholding. In this note, error analysis is presented to quantify the effect of each of those factors on rainfall rate. The error analysis results are then applied to two precipitation events to better interpret the rainfall-rate retrievals. It was found that a large source of error in rain rate is due to unaccounted-for vertical air motion. For example, in stratiform rain with a rainfall rate of R = 10 mm h−1, a mesoscale downdraft of 0.6 m s−1 can result in a 34% underestimation of the estimated value of R. The fall speed relationship selection and source of air density information both caused negligible errors. Errors due to velocity thresholding become more important in the presence of significant contamination near 0 m s−1, such as ground clutter. If particles having an equivalent volume diameter of 0.8 mm and smaller are rejected, rainfall rate errors from −4% to −10% are possible, although these estimates depend on DSD and rainfall rate.

Comparison of Two Raindrop Size Distribution Retrieval Algorithms for X-Band Dual Polarization Observations

Abstract In this study the authors evaluate two algorithms, the so-called beta (β) and constrained methods, proposed for retrieving the governing parameters of the “normalized” gamma drop size distribution (DSD) from dual-polarization radar measurements. The β method treats the drop axis ratio as a variable and computes drop shape and DSD parameters from radar reflectivity (ZH), differential reflectivity (ZDR), and specific differential phase shift (KDP). The constrained method assumes that the axis-ratio relation is fixed and computes DSD parameters from ZH, ZDR, and an empirical relation between the DSD slope and shape parameters. The two techniques are evaluated for polarimetric X-band radar observations by comparing retrieved DSD parameters with disdrometer observations and examining simulated radar parameters for consistency. Error effects on the β method and constrained method retrievals are analyzed. The β approach is found to be sensitive to errors in KDP and to be less consistent with observations. Large retrieved β values are found to be associated with large retrieved DSD shape parameters and small median drop diameters. The constrained method provides reasonable rain DSD retrievals that agree better with disdrometer observations.

Comparison of Raindrop Size Distribution Estimates From X-Band and S-Band Polarimetric Observations

This letter evaluates the consistency of rainfall drop size distribution (DSD) parameters that were estimated from attenuation-corrected X-band dual-polarization (XPOL) radar measurements with estimates from a colocated S-band dual-polarization radar (S-Pol). The DSD retrieval technique uses reflectivity and differential reflectivity, and a constrained relationship to estimate the three parameters of a ldquonormalizedrdquo gamma distribution model. The more definitive S-Pol DSD parameter estimates are used as a reference to assess the performance of the corresponding XPOL estimates for different rain-path attenuation values. Results show that XPOL attenuation-corrected profiles can provide rainfall DSD estimations that are consistent to an S-band dual-polarization radar, even in cases of moderate to high rain-path attenuation.

Drop Size Distribution Retrieval with Polarimetric Radar: Model and Application

Polarimetric radar measurements are used to retrieve properties of raindrop distributions. The procedure assumes that drops are represented by a gamma distribution and retrieves the governing parameters from an empirical relation between the distribution shape and slope parameters and measurements of radar reflectivity and differential reflectivity. Retrieved physical characteristics of the drop size distribution (DSD) were generally well matched with disdrometer observations. The method is applied to select storms to demonstrate utility. Broad DSDs were determined for the core (high reflectivity) regions of thunderstorms. Largest drop median volume diameters were at the leading edge of the storm core and were displaced slightly downwind from updrafts. Rainy downdrafts exhibited what are believed to be equilibrium DSDs in which breakup and accretion are roughly in balance. DSDs for stratiform precipitation were dominated by relatively large drops. Median volume diameters at the ground were closely related to the intensity of an overlying bright band. The radar measurements suggest that, although DSDs in stratiform rain were also broad and nearly constant in the rain layer, they were not at equilibrium but were merely steady. DSD invariance is attributed to small total drop numbers, which result in few collisions.

Comparison of Precipitation Estimation Using Single- and Dual-Frequency Wind Profilers: Simulations and Experimental Results

Abstract The advantages and disadvantages of single-frequency (50 MHz) and dual-frequency (50 and 915 MHz) wind profiler drop size distribution retrievals are discussed by comparing retrievals of median volume drop diameter and rain rates. Simulated data, as well as observational data, show that the median volume diameter estimated from the single-frequency technique is biased higher than what is retrieved using the dual-frequency technique. This result is due to the strong 50-MHz Bragg scatter signal that masks the small drop (low fall velocity) part of the precipitation spectrum. The error in the estimation of the median volume diameter increases markedly with increasing vertical air motion spectral width. The error in the estimation of the median volume diameter is minimum for median volume diameters ranging from 0.5 to about 2.5 mm for the dual-frequency technique and 1.2 to about 2.5 mm for the single-frequency technique. The comparison of retrieved rain rates with rain gauge data shows a very good a...