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- Author or Editor: Thomas J. Greenwald x
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Abstract
The characteristics of shapes and sizes of a sample of 679 hailstones, collected on 22 June 1976 during a hailstorm at Grover, Colorado, were analyzed using a three-parameter formula developed by us previously. These parameters are a, the horizontal dimension, c, the vertical dimension, and λ, the shape parameter. Once these three parameters are specified, both the shape and size of a hailstone are fixed. It is believed that this analysis produces the most complete and quantitative information about the hailstone shape and size distributions reported so far. The dataset of the three parameter also allows the relatively good reconstruction of the sizes and shapes of the original hailstones if desired. The results for this collection of hail show that the distributions of both horizontal and vertical dimensions can be described by gamma distributions, while the shape parameter can be described by an exponential distribution. Since the shape parameter basically describes the vertical asymmetry, it may provide additional information about the physics of particles in clouds and precipitation. The distributions of axial cross-sectional areas, surface areas, and volumes are also presented. They too can be described by gamma distributions. Finally, it was found that the geometrical quantities of the hailstones are best represented by a characteristic dimension rc , defined as the average of the horizontal and vertical dimension.
Abstract
The characteristics of shapes and sizes of a sample of 679 hailstones, collected on 22 June 1976 during a hailstorm at Grover, Colorado, were analyzed using a three-parameter formula developed by us previously. These parameters are a, the horizontal dimension, c, the vertical dimension, and λ, the shape parameter. Once these three parameters are specified, both the shape and size of a hailstone are fixed. It is believed that this analysis produces the most complete and quantitative information about the hailstone shape and size distributions reported so far. The dataset of the three parameter also allows the relatively good reconstruction of the sizes and shapes of the original hailstones if desired. The results for this collection of hail show that the distributions of both horizontal and vertical dimensions can be described by gamma distributions, while the shape parameter can be described by an exponential distribution. Since the shape parameter basically describes the vertical asymmetry, it may provide additional information about the physics of particles in clouds and precipitation. The distributions of axial cross-sectional areas, surface areas, and volumes are also presented. They too can be described by gamma distributions. Finally, it was found that the geometrical quantities of the hailstones are best represented by a characteristic dimension rc , defined as the average of the horizontal and vertical dimension.
Abstract
A combined active/passive modeling system that converts CloudSat observations to simulated microwave brightness temperatures (TB ) is used to assess different ice particle models under precipitating conditions. Simulation results indicate that certain ice models (e.g., low-density spheres) produce excessive scattering and implausibly low simulated TB s for stratiform precipitation events owing to excessive derived ice water paths (IWPs), while other ice models produce unphysical TB depressions due to the combined effects of elevated derived IWP and excessive particle size distribution–averaged extinction. An ensemble of nonspherical ice particle models, however, consistently produces realistic results under most circumstances and adequately captures the radiative properties of frozen hydrometeors associated with precipitation—with the possible exception of very high IWP events. Large derived IWP uncertainties exceeding 60% are also noted and may indicate IWP retrieval accuracy deficiencies using high-frequency passive microwave observations. Simulated TB uncertainties due to the ice particle model ensemble members approach 9 (5) K at 89 (157) GHz for high ice water path conditions associated with snowfall and ∼2–3 (∼1–2) K under typical stratiform rain conditions. These uncertainties, however, display considerable variability owing to ice water path, precipitation type, satellite zenith angle, and frequency. Comparisons between 157-GHz simulations and observations under precipitating conditions produce low biases (<1.5 K) and high correlations, but lower-frequency channels display consistent negative biases of 3–4 K in precipitating regions. Sample error correlations and covariance matrices for select microwave frequencies also show strong functional relationships with ice water path and variability depending on precipitation type.
Abstract
A combined active/passive modeling system that converts CloudSat observations to simulated microwave brightness temperatures (TB ) is used to assess different ice particle models under precipitating conditions. Simulation results indicate that certain ice models (e.g., low-density spheres) produce excessive scattering and implausibly low simulated TB s for stratiform precipitation events owing to excessive derived ice water paths (IWPs), while other ice models produce unphysical TB depressions due to the combined effects of elevated derived IWP and excessive particle size distribution–averaged extinction. An ensemble of nonspherical ice particle models, however, consistently produces realistic results under most circumstances and adequately captures the radiative properties of frozen hydrometeors associated with precipitation—with the possible exception of very high IWP events. Large derived IWP uncertainties exceeding 60% are also noted and may indicate IWP retrieval accuracy deficiencies using high-frequency passive microwave observations. Simulated TB uncertainties due to the ice particle model ensemble members approach 9 (5) K at 89 (157) GHz for high ice water path conditions associated with snowfall and ∼2–3 (∼1–2) K under typical stratiform rain conditions. These uncertainties, however, display considerable variability owing to ice water path, precipitation type, satellite zenith angle, and frequency. Comparisons between 157-GHz simulations and observations under precipitating conditions produce low biases (<1.5 K) and high correlations, but lower-frequency channels display consistent negative biases of 3–4 K in precipitating regions. Sample error correlations and covariance matrices for select microwave frequencies also show strong functional relationships with ice water path and variability depending on precipitation type.
