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V. N. Bringi, Gwo-Jong Huang, V. Chandrasekar, and E. Gorgucci

Abstract

A methodology is proposed for estimating the parameters of a gamma raindrop size distribution model from radar measurements of Z h, Z dr, and K dp at S band. Previously developed algorithms by Gorgucci et al. are extended to cover low rain-rate events where both Z dr and K dp are noisy. Polarimetric data from the S-band Dual-Polarization Doppler Radar (S-Pol) during the Tropical Rainfall Measuring Mission (TRMM)/Brazil campaign are analyzed; specifically, the gamma parameters are retrieved for samples of convective and trailing stratiform rain during the 15 February 1999 squall-line event. Histograms of N w and D o are retrieved from radar for each rain type and compared with related statistics reported in the literature. The functional behavior of N w and D o versus rain rate retrieved from radar is compared against samples of 2D-video and RD-69 disdrometer data obtained during the campaign. The time variation of N w, D o, and μ averaged over a 5 km × 5 km area (within which a network of gauges and a profiler were situated) is shown to illustrate temporal changes associated with the gamma parameters as the squall line passed over the network. The gauge-derived areal rainfall over the network is compared against radar using the areal Φdp method, and the concept of an effective slope of a linear axis ratio versus diameter model is shown to significantly reduce the bias in radar-derived rainfall accumulation.

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Gwo-Jong Huang, V. N. Bringi, and M. Thurai

Abstract

This note reports on the use of a 2D video disdrometer to estimate the orientation of drops (>2 mm) that were generated artificially and allowed to fall 80 m from a bridge with no obstruction and under calm conditions. This experimental setup enabled a large number of drops to be generated, up to 10 mm in horizontal dimension.

The distribution of the canting angles for all drops >2 mm was found to be nearly symmetric about 0° with standard deviation between 7° and 8°. From the canting angle distributions derived from the two orthogonal camera view planes, the distributions of the polar (θ) and azimuth (ϕ) angles were deduced; these two angles describe the 2D orientation of the symmetry axis. The azimuthal angle distribution was found to be nearly uniform in the range (0, 2π), whereas the distribution of p Ω(θ) = p(θ) sinθ was similar in shape to a special form of the Fisher distribution that is valid for describing the statistics on a spherical surface. The standard deviation of p Ω(θ) showed that larger drops are more stably oriented than smaller ones. This is in agreement with previous radar-based results of standard deviation of the canting angle decreasing with increasing Z dr.

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Gwo-Jong Huang, V. N. Bringi, Robert Cifelli, David Hudak, and W. A. Petersen

Abstract

The objective of this work is to derive equivalent radar reflectivity factor–liquid equivalent snow rate (Ze–SR) power-law relations for snowfall using the C-band King City operational weather radar and a 2D video disdrometer (2DVD). The 2DVD provides two orthogonal views of each snow particle that falls through its 10 cm × 10 cm virtual sensor area. The “size” parameter used here for describing the size distribution is based on the “apparent” volume computed from the two images, and an equivolume spherical diameter D app is defined. The determination of fall speed is based on matching two images corresponding to the same particle as it falls through two light planes separated by a precalibrated separation distance. A new “rematching” algorithm was developed to improve the quality of the fall speed versus D app as compared with the original matching algorithm provided by the manufacturer.

The snow density is parameterized in the conventional power-law form , where α and β are assumed to be variable. To account for strong horizontal winds that tend to decrease the measured concentrations from the 2DVD, a third parameter γ is introduced. The methodology estimates the three parameters (α, β, and γ) by minimizing the difference between the radar-measured reflectivity and the equivalent reflectivity computed from the 2DVD in a least squares sense. The optimally determined values of α, β, and γ are used to estimate the SR and the coefficient and exponent of the Ze = a(SR)b relation. For validation, the accumulation from the SR is compared with the manually recorded accumulations from the double-fence international reference (DFIR) gauge. The data were collected during the Canadian Cloudsat Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) Validation Project (C3VP) conducted in Ontario, Canada, during the 2006/07 winter season. A total of seven snow days were analyzed and the accumulation intercomparisons gave a fractional standard deviation of 26% and normalized bias 2.1%. The range of the a and b values for the seven days appear reasonable and similar to conventional ZeR relations.

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V. N. Bringi, Gwo-Jong Huang, V. Chandrasekar, and T. D. Keenan

Abstract

An areal rainfall estimator based on differential propagation phase is proposed and evaluated using the Bureau of Meteorology Research Centre (BMRC) C-POL radar and a dense gauge network located near Darwin, Northern Territory, Australia. Twelve storm events during the summer rainy season (December 1998–March 1999) are analyzed and radar–gauge comparisons are evaluated in terms of normalized error and normalized bias. The areal rainfall algorithm proposed herein results in normalized error of 14% and normalized bias of 5.6% for storm total accumulation over an area of around 100 km2. Both radar measurement error and gauge sampling error are minimized substantially in the areal accumulation comparisons. The high accuracy of the radar-based method appears to validate the physical assumptions about the rain model used in the algorithm, primarily a gamma form of the drop size distribution model, an axis ratio model that accounts for transverse oscillations for D ≤ 4 mm and equilibrium shapes for D > 4 mm, and a Gaussian canting angle distribution model with zero mean and standard deviation 10°. These assumptions appear to be valid for tropical rainfall.

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V. N. Bringi, Gwo-Jong Huang, S. Joseph Munchak, Christian D. Kummerow, David A. Marks, and David B. Wolff

Abstract

The estimation of the drop size distribution parameter [median volume diameter (D 0)] and rain rate (R) from the Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) as well as from combined PR–TRMM Microwave Imager (TMI) algorithms are considered in this study for two TRMM satellite overpasses near the Kwajalein Atoll. An operational dual-polarized S-band radar (KPOL) located in Kwajalein is central as the only TRMM ground validation site for measurement of precipitation over the open ocean. The accuracy of the TRMM PR in retrieving D 0 and R is better for precipitation over the ocean based on a more stable surface reference technique for estimating the path-integrated attenuation. Also, combined PR–TMI methods are more accurate over the open ocean because of better knowledge of the surface microwave emissivity. Using Zh (horizontal polarized radar reflectivity) and Z dr (differential reflectivity) data for the two TRMM overpass events over Kwajalein, D 0 and R from KPOL are retrieved. Herein, the main objective is to see if the D 0 retrieved from either PR or the combined PR–TMI algorithms are in agreement with KPOL-derived values. Also, the variation of D 0 versus R is compared for convective rain pixels from KPOL, PR, and PR–TMI. It is shown that the PR–TMI optimal estimation scheme does indeed adjust the D 0 in the “correct” direction, on average, from the a priori state if the KPOL data are considered to be the ground truth. This correct adjustment may be considered as evidence of the value added by the TMI brightness temperatures in the combined PR–TMI variational scheme, at least for the two overpass events considered herein.

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Gail Skofronick-Jackson, David Hudak, Walter Petersen, Stephen W. Nesbitt, V. Chandrasekar, Stephen Durden, Kirstin J. Gleicher, Gwo-Jong Huang, Paul Joe, Pavlos Kollias, Kimberly A. Reed, Mathew R. Schwaller, Ronald Stewart, Simone Tanelli, Ali Tokay, James R. Wang, and Mengistu Wolde

Abstract

As a component of Earth’s hydrologic cycle, and especially at higher latitudes, falling snow creates snowpack accumulation that in turn provides a large proportion of the freshwater resources required by many communities throughout the world. To assess the relationships between remotely sensed snow measurements with in situ measurements, a winter field project, termed the Global Precipitation Measurement (GPM) Cold Season Precipitation Experiment (GCPEx), was carried out in the winter of 2011/12 in Ontario, Canada. Its goal was to provide information on the precipitation microphysics and processes associated with cold season precipitation to support GPM snowfall retrieval algorithms that make use of a dual-frequency precipitation radar and a passive microwave imager on board the GPM core satellite and radiometers on constellation member satellites. Multiparameter methods are required to be able to relate changes in the microphysical character of the snow to measureable parameters from which precipitation detection and estimation can be based. The data collection strategy was coordinated, stacked, high-altitude, and in situ cloud aircraft missions with three research aircraft sampling within a broader surface network of five ground sites that in turn were taking in situ and volumetric observations. During the field campaign 25 events were identified and classified according to their varied precipitation type, synoptic context, and precipitation amount. Herein, the GCPEx field campaign is described and three illustrative cases detailed.

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