scholarly journals A Field Study of Footprint-Scale Variability of Raindrop Size Distribution

2017 ◽  
Vol 18 (12) ◽  
pp. 3165-3179 ◽  
Author(s):  
Ali Tokay ◽  
Leo Pio D’Adderio ◽  
Federico Porcù ◽  
David B. Wolff ◽  
Walter A. Petersen
Keyword(s):  
Spatial Variability ◽  
Size Distribution ◽  
Dual Frequency ◽  
Weighting Method ◽  
Convective Clouds ◽  
Raindrop Size Distribution ◽  
Precipitation Measurement ◽  
Raindrop Size ◽  
Global Precipitation Measurement ◽  
Global Precipitation

Abstract A network of seven two-dimensional video disdrometers (2DVD), which were operated during the Midlatitude Continental Convective Clouds Experiment (MC3E) in northern Oklahoma, are employed to investigate the spatial variability of raindrop size distribution (DSD) within the footprint of the dual-frequency precipitation radar (DPR) on board the National Aeronautics and Space Administration’s Global Precipitation Measurement (GPM) mission core satellite. One-minute 2DVD DSD observations were interpolated uniformly to 13 points distributed within a nearly circular DPR footprint through an inverse distance weighting method. The presence of deep continental showers was a unique feature of the dataset resulting in a higher mean rain rate R with respect to previous studies. As a measure of spatial variability for the interpolated data, a three-parameter exponential function was applied to paired correlations of three parameters of normalized gamma DSD, R, reflectivity, and attenuation at Ka- and Ku-band frequencies of DPR (Z_Ka, Z_Ku, k_Ka, and k_Ku, respectively). The symmetry of the interpolated sites allowed quantifying the directional differences in correlations at the same distance. The correlation distances d0 of R, k_Ka, and k_Ku were approximately 10 km and were not sensitive to the choice of four rain thresholds used in this study. The d0 of Z_Ku, on the other hand, ranged from 29 to 20 km between different rain thresholds. The coefficient of variation (CV) remained less than 0.5 for most of the samples for a given physical parameter, but a CV of greater than 1.0 was also observed in noticeable samples, especially for the shape parameter and Z_Ku.

scholarly journals Validation of GPM Precipitation Products by Comparison with Ground-Based Parsivel Disdrometers over Jianghuai Region

Water ◽  
2019 ◽  
Vol 11 (6) ◽  
pp. 1260 ◽  
Author(s):  
Zuhang Wu ◽  
Yun Zhang ◽  
Lifeng Zhang ◽  
Xiaolong Hao ◽  
Hengchi Lei ◽  
...  
Keyword(s):  
Shape Parameter ◽  
Rain Rate ◽  
Dual Frequency ◽  
Raindrop Size Distribution ◽  
Precipitation Measurement ◽  
Retrieval Algorithms ◽  
Raindrop Size ◽  
Global Precipitation Measurement ◽  
Global Precipitation ◽  
Rain Retrieval

In this study, we evaluated the performance of rain-retrieval algorithms for the Version 6 Global Precipitation Measurement Dual-frequency Precipitation Radar (GPM DPR) products, against disdrometer observations and improved their retrieval algorithms by using a revised shape parameter µ derived from long-term Particle Size Velocity (Parsivel) disdrometer observations in Jianghuai region from 2014 to 2018. To obtain the optimized shape parameter, raindrop size distribution (DSD) characteristics of summer and winter seasons over Jianghuai region are analyzed, in terms of six rain rate classes and two rain categories (convective and stratiform). The results suggest that the GPM DPR may have better performance for winter rain than summer rain over Jianghuai region with biases of 40% (80%) in winter (summer). The retrieval errors of rain category-based µ (3–5%) were proved to be the smallest in comparison with rain rate-based µ (11–13%) or a constant µ (20–22%) in rain-retrieval algorithms, with a possible application to rainfall estimations over Jianghuai region. Empirical Dm–Ze and Nw–Dm relationships were also derived preliminarily to improve the GPM rainfall estimates over Jianghuai region.

scholarly journals Development and Evaluation of the Raindrop Size Distribution Parameters for the NASA Global Precipitation Measurement Mission Ground Validation Program

2020 ◽  
Vol 37 (1) ◽  
pp. 115-128 ◽  
Author(s):  
Ali Tokay ◽  
Leo Pio D’Adderio ◽  
David B. Wolff ◽  
Walter A. Petersen
Keyword(s):  
Size Distribution ◽  
Drop Diameter ◽  
Empirical Relationships ◽  
Tropical Ocean ◽  
Raindrop Size Distribution ◽  
Precipitation Measurement ◽  
Ground Validation ◽  
Raindrop Size ◽  
Global Precipitation Measurement ◽  
Global Precipitation

AbstractThe National Aeronautics and Space Administration Global Precipitation Measurement (GPM) mission ground validation program uses dual-polarization radar moments to estimate raindrop size distribution (DSD) parameters, the mass-weighted mean drop diameter Dmass, and normalized intercept parameter NW, to validate the GPM Core Observatory–derived DSD parameters. The disdrometer-based Dmass and NW are derived through empirical relationships between Dmass and differential reflectivity ZDR, and between NW, reflectivity ZH, and Dmass. This study employs large datasets collected from two-dimensional video disdrometers (2DVD) during six different field studies to derive the requisite empirical relationships. The uncertainty of the derived Dmass(ZDR) relationship is evaluated through comparisons of 2DVD-calculated and ZDR-estimated Dmass, where ZDR is calculated directly from 2DVD observations. Similarly, the uncertainty of the NW(ZH, Dmass) relationship is evaluated through 2DVD-calculated and Dmass and ZH-estimated NW, where Dmass and ZH are directly calculated from 2DVD observations. This study also presents the sensitivity of Dmass(ZDR) relationships to climate regime and to disdrometer type after developing three additional Dmass(ZDR) relationships from second-generation Particle Size Velocity (PARSIVEL2) disdrometer (P2) observations collected in the Pacific Northwest, in Iowa, and at Kwajalein Atoll in the tropical Pacific Ocean. The application of P2-derived Dmass(ZDR) relationship based on precipitation in the northwestern United States to P2 observations collected over the tropical ocean resulted in the highest error among comparisons of the three datasets.

Microphysical features indicated by GPM DPR product “flagHeavyIcePrecip” – Case studies on lightning activity

2020 ◽  
Author(s):  
Kenji Suzuki ◽  
Rimpei Kamamoto ◽  
Tetsuya Kawano ◽  
Katsuhiro Nakagawa ◽  
Yuki Kaneko
Keyword(s):  
Heavy Rain ◽  
Lightning Activity ◽  
Dual Frequency ◽  
Convective Clouds ◽  
Precipitation Measurement ◽  
X Band ◽  
Precipitation Type ◽  
Global Precipitation Measurement ◽  
Global Precipitation

<p>Two products from the Global Precipitation Measurement (GPM) Dual-frequency Precipitation Radar (DPR) algorithms, a flag of intense solid precipitation above the –10°C height (“flagHeavyIcePrecip”), and a classification of precipitation type (“typePrecip”) were validated quantitatively from the viewpoint of microphysics using ground-based in-situ hydrometeor measurements and X-band multi-parameter (X-MP) radar observations of snow clouds that occurred on 4 February 2018. The distribution of the “flagHeavyIcePrecip” footprints was in good agreement with that of the graupel-dominant pixels classified by the X-MP radar hydrometeor classification. In addition, the vertical profiles of X-MP radar reflectivity exhibited significant differences between footprints flagged and unflagged by “flagHeavyPrecip”. We confirmed the effectiveness of “flagHeavyIcePrecip”, which is built into “typePrecip” algorithm, for detecting intense ice precipitation and concluded that "flagHeavyIcePrecip" is appropriate to useful for determining convective clouds.</p><p>It is well known that the lightning activity is closely related to the convection. We examined the lightning activity using GPM DPR product flagHeavyIcePrecip that indicates the existence of graupel in the upper cloud. On 20 June 2016, we experienced heavy rain with active lightning during Baiu monsoon rainy season, while the GPM DPR passed over Kyushu region in Japan. The distribution of “flagHeavyIcePrecip” obtained from the GPM DPR well corresponded to the CG/IC lightning concentration. On 4 September 2019, isolated thunder clouds observed by the GPM DPR was also similar to the “flagHeavyIcePrecip” distribution. However, partially there was IC lightning without “flagHeavyIcePrecip”, which was positive lightning. It was suggested to have been produced in the upper clouds in which positive ice crystals were dominant.</p>

Uncertainties of GPM DPR Rain Estimates Caused by DSD Parameterizations

2014 ◽  
Vol 53 (11) ◽  
pp. 2524-2537 ◽  
Author(s):  
Liang Liao ◽  
Robert Meneghini ◽  
Ali Tokay
Keyword(s):  
Dual Wavelength ◽  
Evaluation Procedure ◽  
Dual Frequency ◽  
Raindrop Size Distribution ◽  
Precipitation Measurement ◽  
Raindrop Size ◽  
Comparison Of The Results ◽  
Rain Rates ◽  
Global Precipitation ◽  
The Impact

AbstractA framework based on measured raindrop size distribution (DSD) data has been developed to assess uncertainties in DSD models employed in Ku- and Ka-band dual-wavelength radar retrievals. In this study, the rain rates and attenuation coefficients from DSD parameters derived by dual-wavelength algorithms are compared with those directly obtained from measured DSD spectra. The impact of the DSD gamma parameterizations on rain estimation from the Global Precipitation Measurement mission (GPM) Dual-Frequency Precipitation Radar (DPR) is examined for the cases of a fixed shape factor μ as well as for a constrained μ—that is, a μ–Λ relation (a relationship between the shape parameter and slope parameter Λ of the gamma DSD)—by using 11 Particle Size and Velocity (Parsivel) disdrometer measurements with a total number of about 50 000 one-minute spectra that were collected during the Iowa Flood Studies (IFloodS) experiment. It is found that the DPR-like dual-wavelength techniques provide fairly accurate estimates of rain rate and attenuation if a fixed-μ gamma DSD model is used, with the value of μ ranging from 3 to 6. Comparison of the results reveals that the retrieval errors from the μ–Λ relations are generally small, with biases of less than ±10%, and are comparable to the results from a fixed-μ gamma model with μ equal to 3 and 6. The DSD evaluation procedure is also applied to retrievals in which a lognormal DSD model is used.

scholarly journals Measurements and Modeling of the Full Rain Drop Size Distribution

Atmosphere ◽  
2019 ◽  
Vol 10 (1) ◽  
pp. 39 ◽  
Author(s):  
Merhala Thurai ◽  
Viswanathan Bringi ◽  
Patrick Gatlin ◽  
Walter Petersen ◽  
Matthew Wingo
Keyword(s):  
Size Distribution ◽  
Small Drop ◽  
Dual Frequency ◽  
Raindrop Size Distribution ◽  
Precipitation Estimation ◽  
Rain Drop ◽  
Double Moment ◽  
Raindrop Size ◽  
Microphysical Processes ◽  
Global Precipitation

The raindrop size distribution (DSD) is fundamental for quantitative precipitation estimation (QPE) and in numerical modeling of microphysical processes. Conventional disdrometers cannot capture the small drop end, in particular the drizzle mode which controls collisional processes as well as evaporation. To overcome this limitation, the DSD measurements were made using (i) a high-resolution (50 microns) meteorological particle spectrometer to capture the small drop end, and (ii) a 2D video disdrometer for larger drops. Measurements were made in two climatically different regions, namely Greeley, Colorado, and Huntsville, Alabama. To model the DSDs, a formulation based on (a) double-moment normalization and (b) the generalized gamma (GG) model to describe the generic shape with two shape parameters was used. A total of 4550 three-minute DSDs were used to assess the size-resolved fidelity of this model by direct comparison with the measurements demonstrating the suitability of the GG distribution. The shape stability of the normalized DSD was demonstrated across different rain types and intensities. Finally, for a tropical storm case, the co-variabilities of the two main DSD parameters (normalized intercept and mass-weighted mean diameter) were compared with those derived from the dual-frequency precipitation radar onboard the global precipitation mission satellite.

scholarly journals Physical Evaluation of GPM DPR Single- and Dual-Wavelength Algorithms

2019 ◽  
Vol 36 (5) ◽  
pp. 883-902 ◽  
Author(s):  
Liang Liao ◽  
Robert Meneghini
Keyword(s):  
Path Integral ◽  
Dual Wavelength ◽  
Dual Frequency ◽  
Error Sources ◽  
Algorithm Performance ◽  
Physical Evaluation ◽  
Precipitation Measurement ◽  
Raindrop Size ◽  
Global Precipitation Measurement ◽  
Global Precipitation

AbstractA physical evaluation of the rain profiling retrieval algorithms for the Dual-Frequency Precipitation Radar (DPR) on board the Global Precipitation Measurement (GPM) Core Observatory satellite is carried out by applying them to the hydrometeor profiles generated from measured raindrop size distributions (DSD). The DSD-simulated radar profiles are used as input to the algorithms, and their estimates of hydrometeors’ parameters are compared with the same quantities derived directly from the DSD data (or truth). The retrieval accuracy is assessed by the degree to which the estimates agree with the truth. To check the validity and robustness of the retrievals, the profiles are constructed for cases ranging from fully correlated (or uniform) to totally uncorrelated DSDs along the columns. Investigation into the sensitivity of the retrieval results to the model assumptions is made to characterize retrieval uncertainties and identify error sources. Comparisons between the single- and dual-wavelength algorithm performance are carried out with either a single- or dual-wavelength constraint of the path integral or differential path integral attenuation. The results suggest that the DPR dual-wavelength algorithm generally provides accurate range-profiled estimates of rainfall rate and mass-weighted diameter with the dual-wavelength estimates superior in accuracy to those from the single-wavelength retrievals.

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