The Sampling Variations of Hailstone Size Distributions

Wong, Raymond Chi-Wing; Chidambaram, Norman; Cheng, L.; English, Marianne

doi:10.1175/1520-0450(1988)027<0254:tsvohs>2.0.co;2

Cited by 16 publications

(8 citation statements)

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“…2-12). The PSD appear to fit well to gamma functions or exponential functions (e.g., Gunn and Marshall 1958;Wong et al 1988;Heymsfield et al 2002;McFarquhar and Black 2004;McFarquhar et al 2007a;Heymsfield et al 2009Heymsfield et al , 2013Mitchell et al 2010;Muhlbauer et al 2014). The cirrus total ice concentrations generally fall in the range 5-500 L…”

Section: B Cirrus Ice Crystal Concentrations and Size Distributionsmentioning

confidence: 87%

Cirrus Clouds

Heymsfield

Tricht

Lawson

et al. 2017

Meteorological Monographs

148

139

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The goal of this chapter is to synthesize information about what is now known about one of the three main types of clouds, cirrus, and to identify areas where more knowledge is needed. Cirrus clouds, composed of ice particles, form in the upper troposphere, where temperatures are generally below 2308C. Satellite observations show that the maximumoccurrence frequency of cirrus is near the tropics, with a large latitudinal movement seasonally. In situ measurements obtained over a wide range of cirrus types, formation mechanisms, temperatures, and geographical locations indicate that the ice water content and particle size generally decrease with decreasing temperature, whereas the ice particle concentration is nearly constant or increases slightly with decreasing temperature. High ice concentrations, sometimes observed in strong updrafts, result from homogeneous nucleation. The satellite-based and in situ measurements indicate that cirrus ice crystals typically differ from the simple, idealized geometry for smooth hexagonal shapes, indicating complexity and/or surface roughness. Their shapes significantly impact cirrus radiative properties and feedbacks to climate. Cirrus clouds, one of the most uncertain components of general circulation models (GCM), pose one of the greatest challenges in predicting the rate and geographical pattern of climate change. Improved measurements of the properties and size distributions and surface structure of small ice crystals (about 20 mm) and identifying the dominant ice nucleation process (heterogeneous versus homogeneous ice nucleation) under different cloud dynamical forcings will lead to a better representation of their properties in GCM and in modeling their current and future effects on climate.

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Section: B Cirrus Ice Crystal Concentrations and Size Distributionsmentioning

confidence: 87%

Cirrus Clouds

Heymsfield

Tricht

Lawson

et al. 2017

Meteorological Monographs

148

139

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“…The distribution shape is well approximated by a Gamma probability distribution function (PDF) with a mostly absent lower quartile and long upper tail. The gamma PDF was also found to be most suited for major axis length in a number of other case studies studies, including Ziegler et al (1983) for Okalahoma (US), Wong et al (1988) (2014) major/minor axis distributions demonstrates the expected skew towards higher axis ratios in the HailPixel dataset.…”

Section: Resultsmentioning

confidence: 86%

Quantifying Hail Size Distributions from the Sky: Application of Drone Aerial Photogrammetry

Soderholm¹,

Kumjian²,

Gaffney³

et al. 2019

Preprint

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Abstract. A new technique, named "HailPixel," is introduced for measuring the maximum dimension and intermediate dimension of hailstones from aerial imagery. The photogrammetry procedure applies a convolutional neural network for robust detection of hailstones against complex backgrounds and an edge detection method for measuring the shape of identified hailstones. This semi-automated technique is capable of measuring many thousands of hailstones within a single survey, which is several orders of magnitude larger (e.g., 10 000 or more hailstones) than population sizes from existing sensors (e.g., a hail pad). Comparison with a co-located hail pad for an Argentinan hailstorm event during the RELAMPAGO project demonstrates the larger population size of the HailPixel survey significantly improves the shape and tails of the observed hail size distribution. When hailfall is sparse, such as during large and giant hail events, the large survey area of this technique is especially advantageous for resolving the hail size distribution.

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“…The distribution shape is well approximated by a gamma probability distribution function (PDF) with a mostly absent lower quartile and long upper tail. The gamma PDF was also found to be most suited to major-axis length in a number of other case studies, including Ziegler et al (1983) for Oklahoma (US), Wong et al (1988) for Alberta (Canada) and Fraile et al (1992) for León J. S. Soderholm et al: Application of drone aerial photogrammetry (Spain). Impact concentration observed by the hail pad was 141 m −2 , significantly higher than the mean hail concentration observed by the aerial survey (47 m −2 ).…”

Section: Resultsmentioning

confidence: 96%

Quantifying hail size distributions from the sky – application of drone aerial photogrammetry

et al. 2020

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Abstract. A new technique, named “HailPixel”, is introduced for measuring the maximum dimension and intermediate dimension of hailstones from aerial imagery. The photogrammetry procedure applies a convolutional neural network for robust detection of hailstones against complex backgrounds and an edge detection method for measuring the shape of identified hailstones. This semi-automated technique is capable of measuring many thousands of hailstones within a single survey, which is several orders of magnitude larger (e.g. 10 000 or more hailstones) than population sizes from existing sensors (e.g. a hail pad). Comparison with a co-located hail pad for an Argentinian hailstorm event during the RELAMPAGO project demonstrates the larger population size of the HailPixel survey significantly improves the shape and tails of the observed hail size distribution. When hail fall is sparse, such as during large and giant hail events, the large survey area of this technique is especially advantageous for resolving the hail size distribution.

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The Sampling Variations of Hailstone Size Distributions

Cited by 16 publications

References 0 publications

Cirrus Clouds

Cirrus Clouds

Quantifying Hail Size Distributions from the Sky: Application of Drone Aerial Photogrammetry

Quantifying hail size distributions from the sky – application of drone aerial photogrammetry

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