Document Type
Article
Publication Date
8-1-2020
Department
Department of Physics
Abstract
The 2-Dimensional Video Disdrometer (2DVD) is a commonly used tool for exploring rain microphysics and for validating remotely sensed rain retrievals. Recent work has revealed a persistent anomaly in 2DVD data. Early investigations of this anomaly concluded that the resulting errors in rain measurement were modest, but the methods used to flag anomalous data were not optimized, and related considerations associated with the sample sensing area were not fully investigated. Here, we (i) refine the anomaly-detecting algorithm for increased sensitivity and reliability and (ii) develop a related algorithm for refining the estimate of sample sensing area for all detected drops, including those not directly impacted by the anomaly. Using these algorithms, we explore the corrected data to measure any resulting changes to estimates of bulk rainfall statistics from two separate 2DVDs deployed in South Carolina combining for approximately 10 total years of instrumental uptime. Analysis of this data set consisting of over 200 million drops shows that the error induced in estimated total rain accumulations using the manufacturer-reported area is larger than the error due to considerations related to the anomaly. The algorithms presented here imply that approximately 4.2% of detected drops are spurious and the mean reported effective sample area for drops believed to be correctly detected is overestimated by ~8.5%. Simultaneously accounting for all of these effects suggests that the total accumulated rainfall in the data record is approximately 1.1% larger than the raw data record suggests.
Publication Title
Atmosphere
Recommended Citation
Larsen, M.,
&
Blouin, C.
(2020).
Refinements to data acquired by 2-dimensional video disdrometers.
Atmosphere,
11(8).
http://doi.org/10.3390/ATMOS11080855
Retrieved from: https://digitalcommons.mtu.edu/michigantech-p/2665
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Version
Publisher's PDF
Publisher's Statement
© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). Publisher’s version of record: https://doi.org/10.3390/ATMOS11080855