Date of Award
5-2018
Degree Type
Thesis
Degree Name
Master of Science (MS)
Department
Earth, Atmospheric, and Planetary Sciences
Committee Chair
Robin Tanamachi
Committee Member 1
Daniel Dawson II
Committee Member 2
Michael Baldwin
Abstract
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).
Recommended Citation
Saunders, Patrick Evan, "Objective Identification and Tracking of ZDR Columns in X-band Radar Observations" (2018). Open Access Theses. 1452.
https://docs.lib.purdue.edu/open_access_theses/1452