scholarly journals An Inverse Model for Raindrop Size Distribution Retrieval with Polarimetric Variables

2018 ◽  
Vol 10 (8) ◽  
pp. 1179 ◽  
Author(s):  
Guang Wen ◽  
Haonan Chen ◽  
Guifu Zhang ◽  
Jiming Sun

This paper proposes an inverse model for raindrop size distribution (DSD) retrieval with polarimetric radar variables. In this method, a forward operator is first developed based on the simulations of monodisperse raindrops using a T-matrix method, and then approximated with a polynomial function to generate a pseudo training dataset by considering the maximum drop diameter in a truncated Gamma model for DSD. With the pseudo training data, a nearest-neighborhood method is optimized in terms of mass-weighted diameter and liquid water content. Finally, the inverse model is evaluated with simulated and real radar data, both of which yield better agreement with disdrometer observations compared to the existing Bayesian approach. In addition, the rainfall rate derived from the DSD by the inverse model is also improved when compared to the methods using the power-law relations.

2017 ◽  
Vol 10 (7) ◽  
pp. 2573-2594 ◽  
Author(s):  
Timothy H. Raupach ◽  
Alexis Berne

Abstract. A new technique for estimating the raindrop size distribution (DSD) from polarimetric radar data is proposed. Two statistical moments of the DSD are estimated from polarimetric variables, and the DSD is reconstructed using a double-moment normalisation. The technique takes advantage of the relative invariance of the double-moment normalised DSD. The method was tested using X-band radar data and networks of disdrometers in three different climatic regions. Radar-derived estimates of the DSD compare reasonably well to observations. In the three tested domains, in terms of DSD moments, rain rate, and characteristic drop diameter, the proposed method performs similarly to and often better than a state-of-the-art DSD-retrieval technique. The approach is flexible because no specific DSD model is prescribed. In addition, a method is proposed to treat noisy radar data to improve DSD-retrieval performance with radar measurements.


2017 ◽  
Vol 18 (5) ◽  
pp. 1285-1303 ◽  
Author(s):  
Firat Y. Testik ◽  
Bin Pei

Abstract The wind effects on the shape of drop size distribution (DSD) and the driving microphysical processes for the DSD shape evolution were investigated using the dataset from the Midlatitude Continental Convective Clouds Experiment (MC3E). The quality-controlled DSD spectra from MC3E were grouped for each of the rainfall events by considering the precipitation type (stratiform vs convective) and liquid water content for the analysis. The DSD parameters (e.g., mass-weighted mean diameter) and the fitted DSD slopes for these grouped spectra showed statistically significant trends with varying wind speed. Increasing wind speeds were observed to modify the DSD shapes by increasing the number of small drops and decreasing the number of large drops, indicating that the raindrop breakup process governs the DSD shape evolution. Both spontaneous and collisional raindrop breakup modes were analyzed to elucidate the process responsible for the DSD shape evolution with varying wind speed. The analysis revealed that the collisional breakup process controls the wind-induced DSD shape. The findings of this study are of importance in DSD parameterizations that are essential to a wide variety of applications such as radar rainfall retrievals and hydrologic models.


2012 ◽  
Vol 51 (4) ◽  
pp. 780-785 ◽  
Author(s):  
Joël Jaffrain ◽  
Alexis Berne

AbstractThis work aims at quantifying the variability of the parameters of the power laws used for rain-rate estimation from radar data, on the basis of raindrop size distribution measurements over a typical weather radar pixel. Power laws between the rain rate and the reflectivity or the specific differential phase shift are fitted to the measured values, and the variability of the parameters is analyzed. At the point scale, the variability within this radar pixel cannot be solely explained by the sampling uncertainty associated with disdrometer measurements. When parameters derived from point measurements are applied at the radar pixel scale, the resulting error in the rain amount varies between −2% and +15%.


2016 ◽  
Author(s):  
Timothy H. Raupach ◽  
Alexis Berne

Abstract. A new technique for estimating the raindrop size distribution (DSD) from polarimetric radar data is proposed. Two statistical moments of the DSD are estimated from polarimetric variables, and the DSD is reconstructed. The technique takes advantage of the relative invariance of the double-moment normalised DSD. The method was tested using X-band radar data and networks of disdrometers in three different climatic regions. Radar-derived estimates of the DSD compare reasonably well to observations. In the three tested domains, the proposed method performs similarly to and often better than a state-of-the-art DSD-retrieval technique. The approach is flexible because no specific double-normalised DSD model is prescribed. In addition, a method is proposed to treat noisy radar data to improve DSD-retrieval performance with radar measurements.


Author(s):  
Sung–Ho Suh ◽  
Hyeon–Joon Kim ◽  
Dong–In Lee ◽  
Tae–Hoon Kim

AbstractThis study analyzed the regional characteristics of raindrop size distribution (DSD) in the southern coastal area of South Korea. Data from March 2016 to February 2017 were recorded by four PARSIVEL disdrometers installed at intervals of ~20 km from the coastline to inland. Within 20 km from the coastline, multiple local maxima in the probability density function (PDF) were observed at Dm (mass-weighted drop diameter) = 0.6 mm and logNw (normalized intercept parameter) = 5.2 for stratiform rainfall, but these features were not observed more than 20 km from the coastline. Based on mean Dm–logNw values, stratiform rainfall clearly differed between coastal and inland areas. For convective precipitation, there was a linear relationship between Dm and Nw with the distance from the coastline. PDF analyses of diurnal variation in DSD confirmed that in spring and autumn the multiple local maxima appear in the daytime. The multiple local maxima in Dm (logNw) values were lower (higher) at nighttime (NT) than DT in the spring and summer season. These features were highly dependent on the prevailing wind. There was a pattern of increasing A and decreasing b in the radar reflectivity–rainfall rate (Z–R) relationship (Z = ARb) with distance from the coastline, and these features were more pronounced in convective precipitation. These diurnal variabilities were regular in stratiform rainfall, and there were large differences in quantitative precipitation estimation depending on the land–sea breeze in the coastal area.


2016 ◽  
Vol 17 (7) ◽  
pp. 2077-2104 ◽  
Author(s):  
Timothy H. Raupach ◽  
Alexis Berne

Abstract The drop size distribution (DSD) describes the microstructure of liquid precipitation. The high variability of the DSD reflects the variety of microphysical processes controlling raindrop properties and affects the retrieval of rainfall. An analysis of the effects of DSD subgrid variability on areal estimation of precipitation is presented. Data used were recorded with a network of disdrometers in Ardèche, France. DSD variability was studied over two typical scales: 5 km × 5 km, similar to the ground footprint size of the Global Precipitation Measurement (GPM) spaceborne weather radar, and 2.8 km × 2.8 km, an operational pixel size of the Consortium for Small-Scale Modeling (COSMO) numerical weather model. Stochastic simulation was used to generate high-resolution grids of DSD estimates over the regions of interest, constrained by experimental DSDs measured by disdrometers. From these grids, areal DSD estimates were derived. The error introduced by assuming a point measurement to be representative of the areal DSD was quantitatively characterized and was shown to increase with the size of the considered area and with drop size and to decrease with the integration time. The controlled framework allowed for the accuracy of retrieval algorithms to be investigated. Rainfall variables derived by idealized simulations of GPM- and COSMO-style algorithms were compared to subgrid distributions of the same variables. While rain rate and radar reflectivity were well represented, the estimated drop concentration and mass-weighted mean drop diameter were often less representative of subgrid values.


2020 ◽  
Vol 37 (2) ◽  
pp. 229-242 ◽  
Author(s):  
Robert Conrick ◽  
Joseph P. Zagrodnik ◽  
Clifford F. Mass

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.


2012 ◽  
Vol 51 (11) ◽  
pp. 1960-1970 ◽  
Author(s):  
Ricardo Sarmento Tenório ◽  
Marcia Cristina da Silva Moraes ◽  
Henri Sauvageot

AbstractA dataset on raindrop size distribution (DSD) gathered in a coastal site of the Alagoas state in northeastern Brazil is used to analyze some differences between continental and maritime rainfall parameters. The dataset is divided into two subsets. One is composed of rainfall systems coming from the continent and moving eastward (i.e., offshore), representing the continental subset. The other is composed of rainfall systems that developed over the sea and are moving westward (i.e., inshore), representing the maritime subset. The mean conditional rain rate (i.e., for rain rate R > 0) is found to be higher for maritime (4.6 mm h−1) than for continental (3.2 mm h−1) conditions. The coefficient of variation of the conditional rain rate is lower for the maritime (1.75) than for the continental (2.25) subset. The continental and maritime DSDs display significant differences. For drop diameter D smaller than about 2 mm, the number of drops is higher for maritime rain than for continental rain. This reverses for D > 2 mm, in such a way that radar reflectivity factor Z for the maritime case is lower than for the continental case at the same rain rate. These results show that, to estimate precipitation by radar in the coastal area of northeastern Brazil, coefficients of the Z–R relation need to be adapted to the direction of motion of the rain-bearing system, inshore or offshore.


2019 ◽  
Vol 58 (1) ◽  
pp. 145-164 ◽  
Author(s):  
Timothy H. Raupach ◽  
Merhala Thurai ◽  
V. N. Bringi ◽  
Alexis Berne

AbstractCommonly 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.


2008 ◽  
Vol 136 (5) ◽  
pp. 1669-1685 ◽  
Author(s):  
Ali Tokay ◽  
Paul G. Bashor ◽  
Emad Habib ◽  
Takis Kasparis

Abstract Characteristics of the raindrop size distribution in seven tropical cyclones have been studied through impact-type disdrometer measurements at three different sites during the 2004–06 Atlantic hurricane seasons. One of the cyclones has been observed at two different sites. High concentrations of small and/or midsize drops were observed in the presence or absence of large drops. Even in the presence of large drops, the maximum drop diameter rarely exceeded 4 mm. These characteristics of raindrop size distribution were observed in all stages of tropical cyclones, unless the storm was in the extratropical stage where the tropical cyclone and a midlatitude frontal system had merged. The presence of relatively high concentrations of large drops in extratropical cyclones resembled the size distribution in continental thunderstorms. The integral rain parameters of drop concentration, liquid water content, and rain rate at fixed reflectivity were therefore lower in extratropical cyclones than in tropical cyclones. In tropical cyclones, at a disdrometer-calculated reflectivity of 40 dBZ, the number concentration was 700 ± 100 drops m−3, while the liquid water content and rain rate were 0.90 ± 0.05 g m−3 and 18.5 ± 0.5 mm h−1, respectively. The mean mass diameter, on the other hand, was 1.67 ± 0.3 mm. The comparison of raindrop size distributions between Atlantic tropical cyclones and storms that occurred in the central tropical Pacific island of Roi-Namur revealed that the number density is slightly shifted toward smaller drops, resulting in higher-integral rain parameters and lower mean mass and maximum drop diameters at the latter site. Considering parameterization of the raindrop size distribution in tropical cyclones, characteristics of the normalized gamma distribution parameters were examined with respect to reflectivity. The mean mass diameter increased rapidly with reflectivity, while the normalized intercept parameter had an increasing trend with reflectivity. The shape parameter, on the other hand, decreased in a reflectivity range from 10 to 20 dBZ and remained steady at higher reflectivities. Considering the repeatability of the characteristics of the raindrop size distribution, a second impact disdrometer that was located 5.3 km away from the primary site in Wallops Island, Virginia, had similar size spectra in selected tropical cyclones.


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