Abstract
<strong class="journal-contentHeaderColor">Abstract.</strong> This paper presents a new technique to derive thermospheric temperature from space-based disk observations of far ultraviolet airglow. The technique, guided by findings from principal component analysis of synthetic daytime LymanâBirgeâHopfield (LBH) disk emissions, uses a ratio of the emissions in two spectral channels that together span the LBH (2,0) band to determine the change in band shape with respect to a change in the rotational temperature of <span class="inline-formula">N<sub>2</sub></span>. The two-channel-ratio approach limits representativeness and measurement error by only requiring measurement of the relative magnitudes between two spectral channels and not radiometrically calibrated intensities, simplifying the forward model from a full radiative transfer model to a vibrationalârotational band model. It is shown that the derived temperature should be interpreted as a column-integrated property as opposed to a temperature at a specified altitude without utilization of a priori information of the thermospheric temperature profile. The two-channel-ratio approach is demonstrated using NASA GOLD Level 1C disk emission data for the period of 2â8 November 2018 during which a moderate geomagnetic storm has occurred. Due to the lack of independent thermospheric temperature observations, the efficacy of the approach is validated through comparisons of the column-integrated temperature derived from GOLD Level 1C data with the GOLD Level 2 temperature product as well as temperatures from first principle and empirical models. The storm-time thermospheric response manifested in the column-integrated temperature is also shown to corroborate well with hemispherically integrated Joule heating rates, ESA SWARM mass density at 460âkm, and GOLD Level 2 column <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M4" display="inline" overflow="scroll" dspmath="mathml"><mrow class="chem"><mi mathvariant="normal">O</mi><mo>/</mo><msub><mi mathvariant="normal">N</mi><mn mathvariant="normal">2</mn></msub></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="29pt" height="14pt" class="svg-formula" dspmath="mathimg" md5hash="7003ba1ac83e7c29f962255ae440df67"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="amt-14-6917-2021-ie00001.svg" width="29pt" height="14pt" src="amt-14-6917-2021-ie00001.png"/></svg:svg></span></span> ratio.
Highlights
Remote sensing of Earth’s far ultraviolet (FUV) airglow from space provides important insights into the energetics, dynamics, and composition of the upper atmosphere (Meier, 1991; Paxton et al, 2017)
The utility of the LBH bands for probing thermospheric temperature was demonstrated by Aksnes et al (2006) with limb observations by the Advanced Research and Global Observation Satellite’s (ARGOS) High-resolution Ionospheric and Thermospheric Spectrograph (HITS) instrument
The technique, unlike in past work, uses the ratio of two spectral channels that span a single LBH band to determine the change in band shape with respect to a change in the rotational temperature of N2
Summary
Remote sensing of Earth’s far ultraviolet (FUV) airglow from space provides important insights into the energetics, dynamics, and composition of the upper atmosphere (Meier, 1991; Paxton et al, 2017). Due to the lack of independent remotely sensed or in situ temperature measurements in the lower to middle thermosphere, the derived column-integrated temperatures are compared to (1) synthetically generated columnintegrated temperatures from model simulations by NOAA’s Whole Atmosphere Model (WAM) (Akmaev, 2011) and the Naval Research Laboratory Mass Spectrometer and Incoherent Scatter Radar Extended (NRLMSISE-00) (Picone et al, 2002) and (2) observations of other thermospheric states, including the GOLD Level 2 O/N2 data product (Correira et al, 2018) and mass density by ESA’s SWARM constellation (Astafyeva et al, 2017), as well as hemispherically integrated Joule heating rates estimated from SuperDARN and groundbased magnetometer data by using the Assimilative Mapping of Geospace Observations (AMGeO) (AMGeO Collaboration, 2019; Matsuo, 2020)
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