Spectral processing and wind estimation with Jicamarca mesospheric radar data

Smith, Jennifer

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https://hdl.handle.net/2142/50631 Copy

Description

Title

Spectral processing and wind estimation with Jicamarca mesospheric radar data

Author(s)

Smith, Jennifer

Issue Date

2014-09-16

Director of Research (if dissertation) or Advisor (if thesis)

Kudeki, Erhan

Department of Study

Electrical & Computer Eng

Discipline

Electrical & Computer Engr

Degree Granting Institution

University of Illinois at Urbana-Champaign

Degree Name

M.S.

Degree Level

Thesis

Keyword(s)

• mesosphere
• mesosphere-stratosphere-troposphere (MST) Radar
• double Gaussians

Abstract

Since the first radar measurement of the mesosphere above the Jicamarca Radio Observatory in the 1970s, advancement in computing has allowed for increasingly complex processing on increasingly large sets of data. These advances have allowed for more accurate processing techniques to be applied to more data than was possible in the past. Presented in this thesis is an improved method of spectral processing using least-squares nonlinear curve fitting techniques. Using a constrained generalized Gaussian model, the spectral parameters are found for five years of data from Jicamarca's mesosphere-stratosphere-troposphere (MST) radar campaigns. The Doppler velocity from the spectral parameters is then used to estimate the zonal, meridional, and vertical wind velocities. The winds and spectral parameters will be uploaded to the CEDAR Archival Madrigal Database. Winds and spectral data are also displayed at http://remote2.csl.illinois.edu/MSTISR/showmaps_2 utilizing dynamic javascript tools. Abstract This thesis also discusses the detection and fitting of two peaked spectra, known as double Gaussians. An algorithm is described to detect when they occur, based on recognizing when there is a separation of spectral data points above a threshold. Knowing the location of the double peaked spectra allows for fitting them using a double Gaussian model, as well as facilitating the analysis of their causes.

Graduation Semester

2014-08

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http://hdl.handle.net/2142/50631

Copyright and License Information

Copyright 2014 Jennifer Smith

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