
Modeling the longitudinal variation in the post‐sunset far‐ultraviolet OI airglow using the SAMI2 model
Author(s) -
England S. L.,
Immel T. J.,
Huba J. D.
Publication year - 2008
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 - 10.1029/2007ja012536
Subject(s) - airglow , brightness , dynamo , latitude , atmospheric sciences , ionosphere , physics , sunset , anomaly (physics) , geophysics , magnetic field , astronomy , quantum mechanics , condensed matter physics
Recent global‐scale observations of the low‐latitude airglow bands associated with the equatorial ionospheric anomaly (EIA) have revealed a longitudinal variation in the brightness and latitude of the peak airglow emission. For vernal equinox conditions, both of these display a wave number‐four pattern when plotted in a constant‐local‐time frame. It has been proposed that variations in the neutral‐wind driven dynamo electric fields from the E‐region are responsible for this pattern. Additionally, measurements of the electric fields in the E‐region have shown a wave number‐four pattern similar to that of the EIA. Here we use the SAMI2 model, that includes a detailed description of ion photochemistry and transport, to demonstrate that the recently observed zonal variations in the E‐region dynamo electric fields are sufficient to explain the observed variation in brightness and latitude of the airglow bands for these conditions. The vertical drifts associated with E‐region dynamo fields in the SAMI2 model are modified to produce simulations that represent the locations of a maximum and minimum in the wave number‐four pattern. The simulated airglow changes such that the brightness of the maximum case is ∼40% higher than the peak in the minimum case and the latitude of the peak brightness in the maximum case is located 3° poleward of the peak in the minimum case. Both of these results compare favorably with, and even exceed, the observed variations. This result adds quantitative support to the above stated mechanism. The effect of changes in the drifts at different local time periods on the nighttime airglow is also assessed. It is seen that changes at all local time periods make a significant contribution to the total change in the airglow, with the most significant being close to local noon and during the late afternoon.