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Record W4392630674 · doi:10.5194/egusphere-egu24-15735

Feasibility study of a satellite-borne terahertz heterodyne spectrometer for the retrieval of atomic oxygen and temperature in the Earth's atmosphere

2024· preprint· en· W4392630674 on OpenAlexaboutno aff
P. Hansen, Martin Wienold, Heinz‐Wilhelm Hübers

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldChemistry
TopicSpectroscopy and Laser Applications
Canadian institutionsnot available
Fundersnot available
KeywordsSatelliteHeterodyne (poetry)Atmosphere (unit)SpectrometerTerahertz radiationEarth observation satelliteEarth (classical element)OxygenRemote sensingAtomic oxygenLow earth orbitEnvironmental sciencePhysicsAstrobiologyMaterials scienceOpticsMeteorologyGeologyAstronomy

Abstract

fetched live from OpenAlex

Atomic oxygen is one of the main species in the mesosphere and lower thermosphere (MLT) of the Earth’s atmosphere. Thus, atomic oxygen and the local temperature plays an important role for the energy balance in the MLT region. By remote sensing of the emission from the atomic oxygen fine-structure transitions at 2.06 THz and the 4.74 THz, atomic oxygen concentration profiles and neutral temperature profiles of the atmosphere can be derived. By resolving the line profile, heterodyne spectroscopy enables access to layers of the atmosphere for which the oxygen line is saturated. The first spectrally resolved measurements of the 4.74-THz line of atomic oxygen in the atmosphere were performed with the heterodyne spectrometer GREAT on board of the airborne astronomic observatory SOFIA [1]. Based on the experiences from GREAT, the heterodyne spectrometer OSAS-B was developed as a balloon-borne instrument dedicated to the measurement of atomic oxygen in Earth’s atmosphere [2].In this study, we investigate the feasibility of a satellite-borne heterodyne spectrometer for the retrieval of atomic oxygen concentration and temperature in the MLT. Compared to airborne observations, a satellite instrument has the advantage of a limb observation geometry which facilitates the retrieval. A satellite instrument also has the advantage of a fast and almost global coverage.For investigating the feasibility of such an instrument, we use the vertical density and temperature profiles provided by the NRLMSIS 2.0 atmosphere model to simulate 2.06 THz and 4.74 THz emission spectra as measured by a satellite. We then apply retrieval algorithms for the atomic oxygen concentration and temperature and compare the retrieved profiles to the reference, i.e. the original NRLMSIS 2.0 profiles. We consider the scenario of a satellite in a circular orbit at an altitude of 500 km and an inclination of 8°. The emission spectra are simulated using radiative transfer under the assumption of local thermodynamic equilibrium.By considering two separate heterodyne receivers with sensitivity of 11,000 K and 25,000 K noise temperature for the 2.06 THz and 4.74 THz lines, respectively, and data accumulated over 100 seconds of measurement time, corresponding to a ground track of 700 km, we can retrieve a vertical temperature profile from 100 km altitude to 300 km altitude with 5 % relative uncertainties and an atomic oxygen concentration profile from 120 km to 300 km with 5 % relative uncertainties. From 100 km to 120 km the uncertainty in the atomic oxygen concentration is higher and within 25 %.[1] Richter, H. et al. Commun Earth Environ 2,19 (2021), doi: 10.1038/s43247-020-00084-5[2] Wienold, M. et al. 48th IRMMW-THz, Montreal, Canada (2023), doi: 10.1109/IRMMW-THz57677.2023.10299165

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.020
GPT teacher head0.297
Teacher spread0.277 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2024
Admission routes1
Has abstractyes

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