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Identifying Individual Rain Events with a Dense Disdrometer Network
Joint Authors
Larsen, Michael L.
Teves, Joshua B.
Source
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-04-19
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
The use of point detectors to measure properties of rainfall is ubiquitous in the hydrological sciences.
An early step in most rainfall analysis includes the partitioning of the data record into “rain events.” This work utilizes data from a dense network of optical disdrometers to explore the effects of instrument sampling on this partitioning.
It is shown that sampling variability may result in event identifications that can statistically magnify the differences between two similar data records.
The data presented here suggest that these magnification effects are not equally impactful for all common definitions of a rain event.
American Psychological Association (APA)
Larsen, Michael L.& Teves, Joshua B.. 2015. Identifying Individual Rain Events with a Dense Disdrometer Network. Advances in Meteorology،Vol. 2015, no. 2015, pp.1-12.
https://search.emarefa.net/detail/BIM-1052774
Modern Language Association (MLA)
Larsen, Michael L.& Teves, Joshua B.. Identifying Individual Rain Events with a Dense Disdrometer Network. Advances in Meteorology No. 2015 (2015), pp.1-12.
https://search.emarefa.net/detail/BIM-1052774
American Medical Association (AMA)
Larsen, Michael L.& Teves, Joshua B.. Identifying Individual Rain Events with a Dense Disdrometer Network. Advances in Meteorology. 2015. Vol. 2015, no. 2015, pp.1-12.
https://search.emarefa.net/detail/BIM-1052774
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1052774