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Objective Identification and Trackin...

Saunders, Patrick Evan.

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Objective Identification and Tracking of ZDR Columns in X-band Radar Observations.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Objective Identification and Tracking of ZDR Columns in X-band Radar Observations./
Author:	Saunders, Patrick Evan.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2018,
Description:	126 p.
Notes:	Source: Masters Abstracts International, Volume: 79-12.
Contained By:	Masters Abstracts International79-12.
Subject:	Meteorology. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10793434
ISBN:	9780438012349

Objective Identification and Tracking of ZDR Columns in X-band Radar Observations.
Saunders, Patrick Evan.

Objective Identification and Tracking of ZDR Columns in X-band Radar Observations. - Ann Arbor : ProQuest Dissertations & Theses, 2018 - 126 p.

Source: Masters Abstracts International, Volume: 79-12.

Thesis (M.S.)--Purdue University, 2018.

This item must not be sold to any third party vendors.

With the advent of rapidly scanning radar systems, it is imperative to automate the detection of features in radar images. We discuss efforts to objectively identify ZDR columns in X-band radar observations using the enhanced watershed algorithm (EWA; Lakshmanan et al. 2009), a method for identifying features in geospatial images. We discuss our choices for EWA parameters, including thresholds. The EWA is applied to ZDR observations of convective storms obtained during the 2016 and 2017 VORTEX-SE field campaign by the University of Massachusetts X-band, polarimetric, mobile Doppler radar (UMass X-Pol). During several intensive observing periods (IOPs), a variety of convective storm modes, including multicellular clusters, supercells and quasi-linear convective systems, were observed. Use of the EWA facilitates fast and objective tracking of the progression and behavior of each individual ZDR column, which is done using the Lakshmanan and Smith algorithm (LSA; Lakshmanan and Smith 2010).

ISBN: 9780438012349Subjects--Topical Terms:

542822
Meteorology.

Objective Identification and Tracking of ZDR Columns in X-band Radar Observations.
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245 1 0 $a Objective Identification and Tracking of ZDR Columns in X-band Radar Observations.
260 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2018
300 $a 126 p.
500 $a Source: Masters Abstracts International, Volume: 79-12.
500 $a Publisher info.: Dissertation/Thesis.
500 $a Advisor: Tanamachi, Robin.
502 $a Thesis (M.S.)--Purdue University, 2018.
506 $a This item must not be sold to any third party vendors.
520 $a With the advent of rapidly scanning radar systems, it is imperative to automate the detection of features in radar images. We discuss efforts to objectively identify ZDR columns in X-band radar observations using the enhanced watershed algorithm (EWA; Lakshmanan et al. 2009), a method for identifying features in geospatial images. We discuss our choices for EWA parameters, including thresholds. The EWA is applied to ZDR observations of convective storms obtained during the 2016 and 2017 VORTEX-SE field campaign by the University of Massachusetts X-band, polarimetric, mobile Doppler radar (UMass X-Pol). During several intensive observing periods (IOPs), a variety of convective storm modes, including multicellular clusters, supercells and quasi-linear convective systems, were observed. Use of the EWA facilitates fast and objective tracking of the progression and behavior of each individual ZDR column, which is done using the Lakshmanan and Smith algorithm (LSA; Lakshmanan and Smith 2010).
590 $a School code: 0183.
650 4 $a Meteorology. $3 542822
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710 2 $a Purdue University. $b Earth, Atmospheric and Planetary Sciences. $3 2106006
773 0 $t Masters Abstracts International $g 79-12.
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793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10793434