Searching for Large Raindrops: A Global Summary of Two-Dimensional Video Disdrometer Observations
A dataset containing 9637 h of two-dimensional video disdrometer observations consisting of more than 240 million raindrops measured at diverse climatological locations was compiled to help characterize underlying drop size distribution (DSD) assumptions that are essential to make precise retrievals...
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Veröffentlicht in: | Journal of applied meteorology and climatology 2015-05, Vol.54 (5), p.1069-1089 |
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Sprache: | eng |
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Zusammenfassung: | A dataset containing 9637 h of two-dimensional video disdrometer observations consisting of more than 240 million raindrops measured at diverse climatological locations was compiled to help characterize underlying drop size distribution (DSD) assumptions that are essential to make precise retrievals of rainfall using remote sensing platforms. This study concentrates on the tail of the DSD, which largely impacts rainfall retrieval algorithms that utilize radar reflectivity. The maximum raindrop diameter was a median factor of 1.8 larger than the mass-weighted mean diameter and increased with rainfall rate. Only 0.4% of the 1-min DSD spectra were found to contain large raindrops exceeding 5mm in diameter. Large raindrops were most abundant at the tropical locations, especially in Puerto Rico, and were largely concentrated during the spring, especially at subtropical locations. Giant raindrops exceeding 8mmin diameter occurred at tropical, subtropical, and high-latitude continental locations. The greatest numbers of giant raindrops were found in the subtropical locations, with the largest being a 9.7-mm raindrop that occurred in northern Oklahoma during the passage of a hail-producing thunderstorm. These results suggest large raindrops are more likely to fall from clouds that contain hail, especially those raindrops exceeding 8mm in diameter. |
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ISSN: | 1558-8424 1558-8432 |
DOI: | 10.1175/jamc-d-14-0089.1 |