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Proceedings Paper

Vertical air motion estimates from the disdrometer flux conservation model and related experimental observations
Author(s): Parvez Ahammad; Christopher R. Williams; Takis Kasparis; John Lane; Francis Merceret; Linwood Jones
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Paper Abstract

The use of meteorological radar reflectivity Z to estimate rainfall rate R is approached using a different perspective from the classical Z-R relation. Simultaneous rain measurements from different sensors are combined to construct a model that estimates the vertical air velocity by minimizing the error in reflectivity between the different sensors. This model is based on the fact that rain rate and reflectivity are both dependent on the integrals of rain drop size distribution (DSD) but only R depends on vertical air velocity. This study attempts to validate the vertical air velocity estimates and quantify their affects on the rainfall rate estimation. Disdrometer Flux Conservation Model (DFC) uses measurements from disdrometers and other sensors such as vertically pointing radar profilers and scanning radars. Disdrometers measure a drop size flux (Phi) (D), defined as the number of drops passing a horizontal surface per unit time, per unit area, per drop size. The flux is equal to the product of the drop size distribution near the ground NG(D) and drop velocity near the ground vG(D). The drop velocity is the difference between the droplet terminal velocity and the vertical component of the wind velocity, which varies with altitude. The estimates derived from the DFC model using two pair wise selected sensors are used to study the change of reflectivity and vertical air velocity with altitude. Sensitivity tests for the DFC model are also discussed and these outcomes are validated by comparison with independent profiler vertical velocity observations.

Paper Details

Date Published: 31 July 2002
PDF: 10 pages
Proc. SPIE 4729, Signal Processing, Sensor Fusion, and Target Recognition XI, (31 July 2002); doi: 10.1117/12.477624
Show Author Affiliations
Parvez Ahammad, Univ. of Central Florida (United States)
Christopher R. Williams, National Oceanic and Atmospheric Administration/CIRES (United States)
Takis Kasparis, Univ. of Central Florida (United States)
John Lane, NASA Kennedy Space Ctr. (United States)
Francis Merceret, Dynacs, Inc. (United States)
Linwood Jones, Univ. of Central Florida (United States)


Published in SPIE Proceedings Vol. 4729:
Signal Processing, Sensor Fusion, and Target Recognition XI
Ivan Kadar, Editor(s)

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