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Atmosphere 2018, 9(8), 315; https://doi.org/10.3390/atmos9080315

Identification and Characterization of an Anomaly in Two-Dimensional Video Disdrometer Data

1
Department of Physics and Astronomy, College of Charleston, Charleston, SC 29424, USA
2
Atmospheric Sciences Program, Michigan Technological University, Houghton, MI 49931, USA
3
Digital-Institute for Information and Communication Technologies, Joanneum Research, 8010 Graz, Austria
*
Author to whom correspondence should be addressed.
Received: 20 June 2018 / Revised: 30 July 2018 / Accepted: 8 August 2018 / Published: 13 August 2018
(This article belongs to the Special Issue Precipitation: Measurement and Modeling)
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Abstract

The two-dimensional video distrometer (2DVD) is a well known ground based point-monitoring precipitation gauge, often used as a ground truth instrument to validate radar or satellite rainfall retrieval algorithms. This instrument records a number of variables for each detected hydrometeor, including the detected position within the sample area of the instrument. Careful analyses of real 2DVD data reveal an artifact—there are time periods where hydrometeor detections within parts of the sample area are artificially enhanced or diminished. Here, we (i) illustrate this anomaly with an exemplary 2DVD data set, (ii) describe the origin of this anomaly, (iii) develop and present an algorithm to help flag data potentially partially corrupted by this anomaly, and (iv) explore the prevalence and quantitative impact of this anomaly. Although the anomaly is seen in every major rain event studied and by every 2DVD the authors have examined, the anomaly artificially induces less than 3% of all detected drops and typically alters estimates of rain rates and accumulations by less than 2%. View Full-Text
Keywords: precipitation measurement; two-dimensional video disdrometer; optical disdrometer; ground truth precipitation measurement; two-dimensional video disdrometer; optical disdrometer; ground truth
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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Larsen, M.L.; Schönhuber, M. Identification and Characterization of an Anomaly in Two-Dimensional Video Disdrometer Data. Atmosphere 2018, 9, 315.

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