1997
DOI: 10.1029/96ja03314
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Investigation of ionospheric O+ remote sensing using the 834‐Å airglow

Abstract: and PIM models o, we work a difficult test case following from recent comments on the concept of 834-A remote sensing of ionospheric O +. We find that the DIT method can correctly distinguish between distinctly different F layers that produce nearly identical intensity profiles, consistent with instrument specifications for future missions.

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Cited by 33 publications
(43 citation statements)
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“…This form of the Chap man layer is an ex ten sion to the lin early vary ing scale height pro posed by Picone et al (1997) and is a rea son able ap prox i ma tion for de scrib ing the ion o spheric den sity. The O + and elec tron den si ties are as sumed to be equal, which is a good as sump tion be low the H + /O + tran si tion height that typ i cally oc curs at ~750 km.…”
Section: Al Go Rithm 31 De Scrip Tionmentioning
confidence: 99%
“…This form of the Chap man layer is an ex ten sion to the lin early vary ing scale height pro posed by Picone et al (1997) and is a rea son able ap prox i ma tion for de scrib ing the ion o spheric den sity. The O + and elec tron den si ties are as sumed to be equal, which is a good as sump tion be low the H + /O + tran si tion height that typ i cally oc curs at ~750 km.…”
Section: Al Go Rithm 31 De Scrip Tionmentioning
confidence: 99%
“…A technique that has been proposed and tested obtains O + densities from measured altitude profiles of the triplet emission feature near 83.4 nm. 7,8 The method, derived from the approach developed initially for the daytime thermosphere (also discussed in Section 2.4), uses a parameterized model of the O + density as part of a forward model to calculate 83.4 nm volume and column emission rates. The model parameters are iteratively adjusted to compute the optimal values given the measured column emission rates as a function of look angle.…”
Section: Daytime Ionospherementioning
confidence: 99%
“…A subset of these coincident sets will be selected for a regression analysis, and the remaining coincident data will provide a basis for testing of the new empirical mapping from SSULI 83.4 nm to hmF2. A discrete inverse theory algorithm and code written by Dr. J. Michael Picone [2,3] (formerly at NRL, now at George Mason Univ.) will then be used to fit the coincident SSULI limb intensity profiles.…”
Section: Approachmentioning
confidence: 99%