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A. R. Jameson and A. J. Heymsfield

Abstract

It appears that most hail signals less than zero measured by the National Center for Atmospheric Research CP-2 radar during the National Hail Research Experiment were produced by differences between the two beam patterns. Positive hail signals, however, were not significantly affected by these differences. It is concluded that the CP-2 radar did detect and delineate regions of large hail.

Assuming Rayleigh scattering, Rinehart and Tuttle proposed that dual-wavelength data be reprocessed, to account for possible differences between the two beams. In the presence of hail, however, there will be sidelobe effects even if the two beam patterns are well measured and well matched. The use of the estimated erroneous hail signals as proposed by Rinehart and Tuttle, therefore, leads to substantial and ambiguous errors, and the technique should not be used.

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A. R. Jameson and A. J. Heymsfield

Abstract

Extensive comparisons of dual-wavelength (10 and 3 cm) radar data with observations at the ground and penetration aircraft (T-28) measurements of hail in a Colorado storm show that positive hail signals (10 cm reflectivity factor exceeds that at 3 cm) are well correlated with the presence of hail ≳ 1 cm diameter. Widespread areas of negative hail signals (3 cm reflectivity factor exceeds that at 10 cm) found above the melting level are correlated with the presence of subcentimeter graupel. It is possible, therefore, to discriminate two sizes of particles based on dual-wavelength radar measurements. This finding is exploited in Part II of this work to investigate the evolution of graupel into hail.

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A. R. Jameson and A. J. Heymsfield

Abstract

This study addresses the issue of how to upscale cloud-sized in situ measurements of ice to yield realistic simulations of ice clouds for a variety of modeling studies. Aircraft measurements of ice particle counts along a 79-km zigzag path were collected in a Costa Rican cloud formed in the upper-level outflow from convection. These are then used to explore the applicability of Bayesian statistics to the problems of upscaling and downscaling. Using the 10-m particle counts, the analyses using Bayesian statistics provide estimates of the probability distribution function of all possible mean values corresponding to these counts. The statistical method of copulas is used to produce an extensive ensemble of estimates of these mean values, which are then combined to derive the probability density function (pdf) of mean values at 1-km resolution. These are found to compare very well to the observed 1-km particle counts when spatial correlation is included. The profiles of the observed and simulated mean counts along the flight path show similar features and have very similar statistical characteristics. However, because the observed and the simulated counts are both the results of stochastic processes, there is no way to upscale exactly to the observed profile. Each simulation is a unique realization of the stochastic processes, as are the observations themselves. These different realizations over all the different sizes can then be used to upscale particle size distributions over large areas.

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R. M. Rasmussen and A. J. Heymsfield

Abstract

A simple parameterization is presented which allows calculation of surface averaged radial impact velocities for droplets colliding with spheres as a function of the Reynolds and Stokes numbers. These impact velocities are averaged over the collector particle surface, assuming that the incoming droplets are uniformly distributed in space. The results extend the experimental graupel density measurements of Pflaum and Pruppacher to a wide range of graupel masses, sizes, and fallspeeds.

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A. J. Heymsfield and R. G. Knollenberg

Abstract

Particle size spectra were measured during 20 hr of sampling in cirrus generating cells (uncinus, stratus, spissatus, thunderstorm anvil) and the particle concentration, mean crystal length, ice water content, reflectivity factor, and precipitation rate were calculated from these spectra. Average values of the physical properties in the generating cells were:

  1. Ice crystal concentration: 10,000–25,000m−3

  2. Mean crystal length: 0.6–1.0 mm

  3. Particle habit: bullet, rosette, column (75%)-plate (25%)

  4. Ice crystal density. 0.6–0.9 gm m−3

  5. Ice water content. 0.15–0.25 gm −3

  6. Reflectivity factor: 5.0–20.0 mm6−3

  7. Precipitation rate. 0.5–0.7 mm hr−1

Growth was found to be downward, reaching a maximum ice water content just below the base of the generating cell. The maximum ice water contents (not including the thunderstorm anvil) were found in cirrus uncinus. Liquid water was not found throughout the cirrus sampling by measurement with the Johnson-Williams hot wire liquid water meter; however, we believe that liquid water is present as a transient phase.

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C. G. Schmitt and A. J. Heymsfield

Abstract

Ice crystal aggregates imaged by aircraft particle imaging probes often appear to be fractal in nature. As such, their dimensional properties, mass, and projected area can be related using fractal geometry. In cloud microphysics, power-law mass (m)– and area (A)–dimensional (D) relationships (e.g., m = aDb) incorporate different manifestations of the fractal dimension as the exponent (b). In this study a self-consistent technique is derived for determining the mass and projected area properties of ice particles from fractal geometry. A computer program was developed to simulate the crystal aggregation process. The fractal dimension of the simulated aggregates was estimated using the box counting method in three dimensions as well as for two-dimensional projected images of the aggregates. The two- and three-dimensional fractal dimension values were found to be simply related. This relationship enabled the development of mass–dimensional relationships analytically from cloud particle images. This technique was applied to data collected during two field projects. The exponent in the mass–dimensional relationship, the fractal dimension, was found to be between 2.0 and 2.3 with a dependence on temperature noted for both datasets. The coefficient a in the mass–dimensional relationships was derived in a self-consistent manner. Temperature-dependent mass–dimensional relationships have been developed. Cloud ice water content estimated using the temperature-dependent relationship and particle size distributions agreed well with directly measured ice water content values. The results are appropriate for characterizing cloud particle properties in clouds with high concentrations of ice crystal aggregates.

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C. G. Schmitt and A. J. Heymsfield

Abstract

Representations for the surface area of ice particles in terms of the projected area have been developed using two different methods. The first method uses ice particles that are imaged in situ and geometric calculations that are based on the outline of the two-dimensional image of the particle. The second method uses computer-generated ice particle shapes and calculates the total surface area analytically. The results of the second method compare reasonably well with the results of the first method. Surface area estimates for individual particles were combined with particle size distribution and projected area measurements from the Cirrus Regional Study of Tropical Anvils and Cirrus Layers (CRYSTAL)–Florida Area Cirrus Experiment (FACE) field project to give total surface area estimates for observed ice particle populations. Population surface area estimates were also made from balloon-borne replicator data collected during the First International Satellite Cloud Climatology Project (ISCCP) Regional Experiment, phase II (FIRE-II). A relationship between the particle population surface area and projected area (cloud extinction) has been derived. The total particle surface area for particle populations is estimated to be between 8 and 10 times the projected area or between 4 and 5 times the extinction and has a small dependence on the properties of the particle size distribution for particles observed in random orientations.

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C. G. Schmitt and A. J. Heymsfield

Abstract

Cirrus clouds in mid- and high latitudes are frequently composed of bullet rosette– and column-shaped ice crystals, which can have hollow ends. Bullet rosette–shaped ice crystals are composed of a number of bullets radiating from a central point. Research has shown that the light-scattering properties of ice particles with hollow ends are different from the scattering properties of solid ice particles. Knowledge of the frequency of occurrence of hollow particles is important to more accurately calculate the radiative properties of cirrus clouds.

This note presents the results of a survey of cirrus cloud ice crystal replicas imaged from balloon-borne Formvar (polyvinyl formal) replicators. Fifty percent to 80% of the replicated bullet rosette– and column-shaped particles had hollow ends. In bullets longer than 150 μm in length, the length of the hollows of the bullets averaged 88% of the total length of the bullet. The combined length of both hollow portions of column-shaped ice crystals varied from 50% of the length of the column for 30-μm-long columns to 80% of the length of the columns longer than 200 μm. Asymmetry parameter values estimated from cirrus cloud aircraft particle size distributions are higher by 0.014 when hollow crystals are considered. This difference leads to a 2.5 W m−2 increase for hollow crystals at the surface for a 0.5 optical depth cloud, demonstrating the importance of the incorporation of hollow particle scattering characteristics into radiative transfer calculations.

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A. J. Heymsfield and C. D. Westbrook

Abstract

Accurate estimates for the fall speed of natural hydrometeors are vital if their evolution in clouds is to be understood quantitatively. In this study, laboratory measurements of the terminal velocity υt for a variety of ice particle models settling in viscous fluids, along with wind-tunnel and field measurements of ice particles settling in air, have been analyzed and compared to common methods of computing υt from the literature. It is observed that while these methods work well for a number of particle types, they fail for particles with open geometries, specifically those particles for which the area ratio Ar is small (Ar is defined as the area of the particle projected normal to the flow divided by the area of a circumscribing disc). In particular, the fall speeds of stellar and dendritic crystals, needles, open bullet rosettes, and low-density aggregates are all overestimated. These particle types are important in many cloud types: aggregates in particular often dominate snow precipitation at the ground and vertically pointing Doppler radar measurements.

Based on the laboratory data, a simple modification to previous computational methods is proposed, based on the area ratio. This new method collapses the available drag data onto an approximately universal curve, and the resulting errors in the computed fall speeds relative to the tank data are less than 25% in all cases. Comparison with the (much more scattered) measurements of ice particles falling in air show strong support for this new method, with the area ratio bias apparently eliminated.

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C. G. Schmitt and A. J. Heymsfield

Abstract

Ice crystal terminal velocities govern the lifetime of radiatively complex, climatologically important, low-latitude tropopause cirrus clouds. To better understand cloud lifetimes, the terminal velocities of low-latitude tropopause cirrus cloud particles have been estimated using data from aircraft field campaigns. Data used in this study were collected during the Cirrus Regional Study of Tropical Anvils and Cirrus Layers–Florida Area Cirrus Experiment (CRYSTAL-FACE) and the Pre-Aura Validation Experiment (Pre-AVE). Particle properties were measured with the NCAR video ice particle sampler (VIPS) probe, thus providing information about particles in a poorly understood size range. Data used in this study were limited to high-altitude nonconvective thin clouds with temperatures between −56° and −86°C.

Realistic particle terminal velocity estimates require accurate values of particle projected area and mass. Exponential functions were used to predict the dimensional properties of ice particles smaller than 200 microns and were found to predict ice water content measurements well when compared to power-law representations. The shapes of the particle size distributions were found to be monomodal and were well represented by exponential or gamma functions. Incorporating these findings into terminal velocity calculations led to lower values of mass-weighted terminal velocities for particle populations than are currently predicted for low-latitude ice clouds. New parameterizations for individual particle properties as well as particle size distribution properties are presented and compared to commonly used parameterizations. Results from this study are appropriate for use in estimating the properties of low-latitude thin and subvisible cirrus at temperatures lower than −56°C.

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