Resolving Some Longstanding Issues in Far Ultraviolet Remote Sensing: A Self‐Consistent Analysis of the GUVI and SEE Observations on the TIMED Mission

Abstract

Far Ultraviolet (FUV) remote sensing has been used in aeronomy missions as a powerful means to measure the temperature and compositions in the upper atmospheres of terrestrial planets. However, despite decades of continual development, outstanding challenges remain in this field. Particularly, there is currently a lack of methods for the examination and improvement of the data products in FUV remote sensing. As a result, longstanding issues exist in many of those data products. Here we demonstrate that a self‐consistent analysis of multi‐band airglow observations in the spectral range of ∼120–180 nm can serve as a useful means for examination and improvement of the data products in FUV remote sensing. The Global Ultraviolet Imager (GUVI) and Solar EUV Experiment (SEE) observations on the Thermosphere Ionosphere Mesosphere Energetics and Dynamics mission are used for the demonstration. Through a self‐consistent analysis, we reconcile the thermospheric column O/N2 density ratios that are retrieved respectively from the GUVI limb and disk scans, by numerically correcting a systematic offset between those observations. We also reconcile the models with the observed 121.6 and 130.4 nm emission that have shown large discrepancies in the literature. The self‐consistent analysis indicates that the SEE measurements of the solar spectral irradiance below ∼45 nm need to be scaled down by ∼25%, whereas the SEE measurements of the solar 121.6 and 130.4 nm fluxes are highly accurate, with errors less than ∼3%. Our results achieve unprecedented agreement (better than ∼5%) between models and observations and provide a novel method for data examination and improvement in FUV remote sensing.

A Comparative Analysis of the Solar Ultraviolet Spectral Irradiance Measured from Earth and Mars: Toward a General Empirical Model for the Study of Planetary Aeronomy

“…They found that the Q EUV measurements by SEE need to be lowered by ∼30% to reconcile the GUVI and SEE measurements. More recently, Qin (2024) examined the accuracies of the GUVI and SEE data products through a self-consistent analysis and modeling of the airglow emissions acquired from all the five GUVI channels. The author found that SEE overestimates Q EUV by ∼25%, which is highly consistent with the results shown in Figure 8.…”