Nonlinear regression method for estimating neutral wind and temperature from Fabry-Perot interferometer data

Brian J. Harding, Thomas W. Gehrels, Jonathan J. Makela

Research output: Contribution to journalArticle

Abstract

The Earth's thermosphere plays a critical role in driving electrodynamic processes in the ionosphere and in transferring solar energy to the atmosphere, yet measurements of thermospheric state parameters, such as wind and temperature, are sparse. One of the most popular techniques for measuring these parameters is to use a Fabry-Perot interferometer to monitor the Doppler width and breadth ofnaturally occurring airglow emissions in the thermosphere. In this work, we present a technique for estimating upper-atmospheric winds and temperatures from images of Fabry-Perot fringes captured by a CCD detector. We estimate instrument parameters from fringe patterns of a frequency-stabilized laser, and we use these parameters toestimate winds and temperatures from airglow fringe patterns. A unique feature of this technique is the model used for the laser and airglow fringe patterns, which fits all fringes simultaneously and attempts to model the effects of optical defects. This technique yields accurate estimates for winds, temperatures, and the associated uncertainties in these parameters, as we show with a Monte Carlo simulation.

Original languageEnglish (US)
Pages (from-to)666-673
Number of pages8
JournalApplied Optics
Issue number4
DOIs
StatePublished - Feb 1 2014

ASJC Scopus subject areas

  • Atomic and Molecular Physics, and Optics
  • Engineering (miscellaneous)
  • Electrical and Electronic Engineering

Fingerprint Dive into the research topics of 'Nonlinear regression method for estimating neutral wind and temperature from Fabry-Perot interferometer data'. Together they form a unique fingerprint.

  • Cite this