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Ali Tokay and David A. Short

Abstract

An analysis of temporal variations in gamma parameters of raindrop spectra is presented utilizing surface-based observations from the Tropical Ocean Global Atmosphere Couple Ocean-Atmosphere Experiment. An observed dramatic change in the N 0 parameter, found to occur during rainfall events with little change in rainfall rate, is suggestive of a transition from rain of convective origin to rain originating from the stratiform portion of tropical systems. An empirical stratiform-convective classification method based on N 0 and R (rainfall rate) is presented. Properties of the drop size spectra from the stratiform classification are consistent with micro-physical processes occurring within an aggregation/melting layer aloft, which produces more large raindrops and fewer small to medium size raindrops than rain from the convective classification, at the same rainfall rate. The occurrence of precipitation was found to be 74% (stratiform) and 26% (convective), but total rainfall, on the other hand, was 32% and 68%, respectively. Case studies of the tropical systems studied here indicate that heavy convective showers are generally followed by longer intervals of lighter rain from the stratiform portion of the cloud systems. Differences in the shapes of the frequency distributions of the integral rainfall parameters (i.e., liquid water content, rainfall rate, and radar reflectivity) suggest that the lognormal distribution applies to some, but not all cases. The analysis shows that almost all the precipitation with a radar reflectivity above 40 dBZ falls within the convective classification. Regarding radar reflectivity versus rainfall rate relationships, the exponent is lower and the intercept is higher in the tropical stratiform classification than in the tropical convective classification. Collision and evaporation rates, which are important for cloud-modeling studies, indicate substantial variation at different rainfall rates and between the two types.

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Jackson Tan, Walter A. Petersen, and Ali Tokay

Abstract

The comparison of satellite and high-quality, ground-based estimates of precipitation is an important means to assess the confidence in satellite-based algorithms and to provide a benchmark for their continued development and future improvement. To these ends, it is beneficial to identify sources of estimation uncertainty, thereby facilitating a precise understanding of the origins of the problem. This is especially true for new datasets such as the Integrated Multisatellite Retrievals for GPM (IMERG) product, which provides global precipitation gridded at a high resolution using measurements from different sources and techniques. Here, IMERG is evaluated against a dense network of gauges in the mid-Atlantic region of the United States. A novel approach is presented, leveraging ancillary variables in IMERG to attribute the errors to the individual instruments or techniques within the algorithm. As a whole, IMERG exhibits some misses and false alarms for rain detection, while its rain-rate estimates tend to overestimate drizzle and underestimate heavy rain with considerable random error. Tracing the errors to their sources, the most reliable IMERG estimates come from passive microwave satellites, which in turn exhibit a hierarchy of performance. The morphing technique has comparable proficiency with the less skillful satellites, but infrared estimations perform poorly. The approach here demonstrated that, underlying the overall reasonable performance of IMERG, different sources have different reliability, thus enabling both IMERG users and developers to better recognize the uncertainty in the estimate. Future validation efforts are urged to adopt such a categorization to bridge between gridded rainfall and instantaneous satellite estimates.

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Ali Tokay, Walter A. Petersen, Patrick Gatlin, and Matthew Wingo

Abstract

An impact-type Joss–Waldvogel disdrometer (JWD), a two-dimensional video disdrometer (2DVD), and a laser optical OTT Particle Size and Velocity (PARSIVEL) disdrometer (PD) were used to measure the raindrop size distribution (DSD) over a 6-month period in Huntsville, Alabama. Comparisons indicate event rain totals for all three disdrometers that were in reasonable agreement with a reference rain gauge. In a relative sense, hourly composite DSDs revealed that the JWD was more sensitive to small drops (<1 mm), while the PD appeared to severely underestimate small drops less than 0.76 mm in diameter. The JWD and 2DVD measured comparable number concentrations of midsize drops (1–3 mm) and large drops (3–5 mm), while the PD tended to measure relatively higher drop concentrations at sizes larger than 2.44 mm in diameter. This concentration disparity tended to occur when hourly rain rates and drop counts exceeded 2.5 mm h−1 and 400 min−1, respectively. Based on interactions with the PD manufacturer, the partially inhomogeneous laser beam is considered the cause of the PD drop count overestimation. PD drop fall speeds followed the expected terminal fall speed relationship quite well, while the 2DVD occasionally measured slower drops for diameters larger than 2.4 mm, coinciding with events where wind speeds were greater than 4 m s−1. The underestimation of small drops by the PD had a pronounced effect on the intercept and shape of parameters of gamma-fitted DSDs, while the overestimation of midsize and larger drops resulted in higher mean values for PD integral rain parameters.

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Ali Tokay, David B. Wolff, and Walter A. Petersen

Abstract

A comparative study of raindrop size distribution measurements has been conducted at NASA’s Goddard Space Flight Center where the focus was to evaluate the performance of the upgraded laser-optical OTT Particle Size Velocity (Parsivel2; P2) disdrometer. The experimental setup included a collocated pair of tipping-bucket rain gauges, OTT Parsivel (P1) and P2 disdrometers, and Joss–Waldvogel (JW) disdrometers. Excellent agreement between the two collocated rain gauges enabled their use as a relative reference for event rain totals. A comparison of event total showed that the P2 had a 6% absolute bias with respect to the reference gauges, considerably lower than the P1 and JW disdrometers. Good agreement was also evident between the JW and P2 in hourly raindrop spectra for drop diameters between 0.5 and 4 mm. The P2 drop concentrations mostly increased toward small sizes, and the peak concentrations were mostly observed in the first three measurable size bins. The P1, on the other hand, underestimated small drops and overestimated the large drops, particularly in heavy rain rates. From the analysis performed, it appears that the P2 is an improvement over the P1 model for both drop size and rainfall measurements. P2 mean fall velocities follow accepted terminal fall speed relationships at drop sizes less than 1 mm. As a caveat, the P2 had approximately 1 m s−1 slower mean fall speed with respect to the terminal fall speed near 1 mm, and the difference between the mean measured and terminal fall speeds reduced with increasing drop size. This caveat was recognized as a software bug by the manufacturer and is currently being investigated.

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David B. Wolff, Walter A. Petersen, Ali Tokay, David A. Marks, and Jason L. Pippitt

Abstract

Hurricane Harvey hit the Texas Gulf Coast as a major hurricane on 25 August 2017 before exiting the state as a tropical storm on 29 August 2017. Left in its wake was historic flooding, with some locations measuring more than 60 in. (150 cm) of rain over a 5-day period. The WSR-88D radar (KHGX) maintained operations for the entirety of the event. Rain gauge data from the Harris County Flood Warning System (HCFWS) was used for validation with the full radar dataset to retrieve daily and event-total precipitation estimates for the period 25–29 August 2017. The KHGX precipitation estimates were then compared with the HCFWS gauges. Three different hybrid polarimetric rainfall retrievals were used, along with attenuation-based retrieval that employs the radar-observed differential propagation. An advantage of using a attenuation-based retrieval is its immunity to partial beam blockage and calibration errors in reflectivity and differential reflectivity. All of the retrievals are susceptible to changes in the observed drop size distribution (DSD). No in situ DSD data were available over the study area, so changes in the DSD were interpreted by examining the observed radar data. We examined the parameter space of two key values in the attenuation retrieval to test the sensitivity of the rain retrieval. Selecting a value of α = 0.015 and β = 0.600 provided the best overall results, relative to the gauges, but more work needs to be done to develop an automated technique to account for changes in the ambient DSD.

Open access
Ali Tokay, Leo Pio D’Adderio, David B. Wolff, and Walter A. Petersen

Abstract

The spatial variability of parameters of the raindrop size distribution and its derivatives is investigated through a field study where collocated Particle Size and Velocity (Parsivel2) and two-dimensional video disdrometers were operated at six sites at Wallops Flight Facility, Virginia, from December 2013 to March 2014. The three-parameter exponential function was employed to determine the spatial variability across the study domain where the maximum separation distance was 2.3 km. The nugget parameter of the exponential function was set to 0.99 and the correlation distance d 0 and shape parameter s 0 were retrieved by minimizing the root-mean-square error, after fitting it to the correlations of physical parameters. Fits were very good for almost all 15 physical parameters. The retrieved d 0 and s 0 were about 4.5 km and 1.1, respectively, for rain rate (RR) when all 12 disdrometers were reporting rainfall with a rain-rate threshold of 0.1 mm h−1 for 1-min averages. The d 0 decreased noticeably when one or more disdrometers were required to report rain. The d 0 was considerably different for a number of parameters (e.g., mass-weighted diameter) but was about the same for the other parameters (e.g., RR) when rainfall threshold was reset to 12 and 18 dBZ for Ka- and Ku-band reflectivity, respectively, following the expected Global Precipitation Measurement mission’s spaceborne radar minimum detectable signals. The reduction of the database through elimination of a site did not alter d 0 as long as the fit was adequate. The correlations of 5-min rain accumulations were lower when disdrometer observations were simulated for a rain gauge at different bucket sizes.

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Ali Tokay, Leo Pio D’Adderio, Federico Porcù, David B. Wolff, and Walter A. Petersen

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 d 0 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 d 0 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.

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David A. Marks, David B. Wolff, David S. Silberstein, Ali Tokay, Jason L. Pippitt, and Jianxin Wang

Abstract

Since the Tropical Rainfall Measuring Mission (TRMM) satellite launch in November 1997, the TRMM Satellite Validation Office (TSVO) at NASA Goddard Space Flight Center (GSFC) has been performing quality control and estimating rainfall from the KPOL S-band radar at Kwajalein, Republic of the Marshall Islands. Over this period, KPOL has incurred many episodes of calibration and antenna pointing angle uncertainty. To address these issues, the TSVO has applied the relative calibration adjustment (RCA) technique to eight years of KPOL radar data to produce Ground Validation (GV) version 7 products. This application has significantly improved stability in KPOL reflectivity distributions needed for probability matching method (PMM) rain-rate estimation and for comparisons to the TRMM precipitation radar (PR). In years with significant calibration and angle corrections, the statistical improvement in PMM distributions is dramatic. The intent of this paper is to show improved stability in corrected KPOL reflectivity distributions by using the PR as a stable reference. Intermonth fluctuations in mean reflectivity differences between the PR and corrected KPOL are on the order of ±1–2 dB, and interyear mean reflectivity differences fluctuate by approximately ±1 dB. This represents a marked improvement in stability with confidence comparable to the established calibration and uncertainty boundaries of the PR. The practical application of the RCA method has salvaged eight years of radar data that would have otherwise been unusable and has made possible a high-quality database of tropical ocean–based reflectivity measurements and precipitation estimates for the research community.

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Sergey Y. Matrosov, Kurt A. Clark, Brooks E. Martner, and Ali Tokay

Abstract

A combined polarimetric estimator for rainfall rate (R) retrievals from polarimetric radar measurements at X band is proposed. This estimator uses the horizontal polarization radar reflectivity Z e, differential reflectivity Z DR, and specific differential phase shift K DP, and it intrinsically accounts for changes in how drop oblateness increases with size. Because this estimator uses power measurements (i.e., Z e and Z DR), a procedure for correcting these measurements for effects of partial attenuation and differential attenuation using the differential phase measurement is suggested. An altitude correction for estimates of rainfall rates is also suggested. The proposed combined polarimetric estimator that uses K DP, Z DR, and Z e, an estimator that uses K DP alone for equilibrium drop shapes, and different Z eR relations were applied to the 15 rain events observed with the NOAA X-band transportable polarimetric radar during the eight-week field campaign at the NASA Wallops Island facility in Virginia. The observed rains ranged from very light stratiform events to very heavy convective ones with cells producing rainfall rates in excess of 100 mm h−1. The three different ground validation sites were equipped with high-resolution (0.01 in.) tipping-bucket rain gauges. One of these sites also was equipped with disdrometers. In terms of the relative standard deviation, the combined polarimetric estimator provided the best overall agreement with gauge data (22%), closely followed by a case-tuned Z eR relation (23%) that was determined for each observational case from drop size distributions (DSD) measured in situ by a disdrometer and was available only a posteriori. The use of the K DP-only estimator and a mean Z eR relation resulted in 30% and 32% relative standard deviations, correspondingly. The combined polarimetric estimator, the K DP-only estimator, and the case-tuned Z eR relation estimator provided about a 6%–9% negative bias in comparison with the gauge data; the mean Z eR relation estimator provided a larger negative bias (18%).

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Ali Tokay, Leo Pio D’Adderio, David B. Wolff, and Walter A. Petersen

Abstract

The 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 D mass, and normalized intercept parameter N W, to validate the GPM Core Observatory–derived DSD parameters. The disdrometer-based D mass and N W are derived through empirical relationships between D mass and differential reflectivity Z DR, and between N W, reflectivity Z H, and D mass. 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 D mass(Z DR) relationship is evaluated through comparisons of 2DVD-calculated and Z DR-estimated D mass, where Z DR is calculated directly from 2DVD observations. Similarly, the uncertainty of the N W(Z H, D mass) relationship is evaluated through 2DVD-calculated and D mass and Z H-estimated N W, where D mass and Z H are directly calculated from 2DVD observations. This study also presents the sensitivity of D mass(Z DR) relationships to climate regime and to disdrometer type after developing three additional D mass(Z DR) 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 D mass(Z DR) 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.

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