TY - JOUR
T1 - Quantifying hail size distributions from the sky - Application of drone aerial photogrammetry
AU - Soderholm, Joshua S.
AU - Kumjian, Matthew R.
AU - McCarthy, Nicholas
AU - Maldonado, Paula
AU - Wang, Minzheng
N1 - Publisher Copyright:
© 2020 Copernicus GmbH. All rights reserved.
PY - 2020/2/17
Y1 - 2020/2/17
N2 - 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.
AB - 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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U2 - 10.5194/amt-13-747-2020
DO - 10.5194/amt-13-747-2020
M3 - Article
AN - SCOPUS:85081133466
SN - 1867-1381
VL - 13
SP - 747
EP - 754
JO - Atmospheric Measurement Techniques
JF - Atmospheric Measurement Techniques
IS - 2
ER -