Spectral processing and wind estimation with Jicamarca mesospheric radar data

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.

Name thesis:degree_name

M.S.

Level thesis:degree_level

Thesis

Discipline thesis:degree_discipline

Electrical & Computer Engr

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2014

Author dc:creator

• Smith, Jennifer

Contributors dc:contributor

• Kudeki, Erhan

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

Statement dc:rights

• Copyright 2014 Jennifer Smith

Language dc:language

en

Handle dc:identifier

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

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/50631