Open AccessNeutral wind estimation from 4‐D ionospheric electron density images
Author(s) -
DattaBarua S.,
Bust G. S.,
Crowley G.,
Curtis N.
Publication year - 2009
Publication title -
journal of geophysical research: space physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.67
H-Index - 298
eISSN - 2156-2202
pISSN - 0148-0227
DOI - 10.1029/2008ja014004
Subject(s) - thermosphere , ionosphere , airglow , atmospheric sciences , computational physics , electron density , longitude , solstice , physics , environmental science , meteorology , geophysics , latitude , geology , electron , geodesy , quantum mechanics
We develop a new inversion algorithm for Estimating Model Parameters from Ionospheric Reverse Engineering (EMPIRE). The EMPIRE method uses four‐dimensional images of global electron density to estimate the field‐aligned neutral wind ionospheric driver when direct measurement is not available. We begin with a model of the electron continuity equation that includes production and loss rate estimates, as well as E × B drift, gravity, and diffusion effects. We use ion, electron, and neutral species temperatures and neutral densities from the Thermosphere Ionosphere Mesosphere Electrodynamics General Circulation Model (TIMEGCM‐ASPEN) for estimating the magnitude of these effects. We then model the neutral wind as a power series at a given longitude for a range of latitudes and altitudes. As a test of our algorithm, we have input TIMEGCM electron densities to our algorithm. The model of the neutral wind is computed at hourly intervals and validated by comparing to the “true” TIMEGCM neutral wind fields. We show results for a storm day: 10 November 2004. The agreement between the winds derived from EMPIRE versus the TIMEGCM “true” winds appears to be time‐dependent for the day under consideration. This may indicate that the diurnal variation in certain driving processes impacts the accuracy of our neutral wind model. Despite the potential temporal and spatial limits on accuracy, estimating neutral wind speed from measured electron density fields via our algorithm shows great promise as a complement to the more sparse radar and satellite measurements.