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Record W1791495664 · doi:10.5194/amt-9-1063-2016

New temperature and pressure retrieval algorithm for high-resolution infrared solar occultation spectroscopy: analysis and validation against ACE-FTS and COSMIC

2016· article· en· W1791495664 on OpenAlexafffund
Kevin Olsen, Geoffrey C. Toon, C. D. Boone, Kimberly Strong

Bibliographic record

VenueAtmospheric measurement techniques · 2016
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric Ozone and Climate
Canadian institutionsUniversity of WaterlooUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsOccultationRadio occultationMars Exploration ProgramRemote sensingEnvironmental scienceTrace gasAtmosphere of MarsCOSMIC cancer databaseMeteorologyMartianPhysicsGeologyAstronomy

Abstract

fetched live from OpenAlex

Motivated by the initial selection of a high-resolution solar occultation Fourier transform spectrometer (FTS) to fly to Mars on the ExoMars Trace Gas Orbiter, we have been developing algorithms for retrieving volume mixing ratio vertical profiles of trace gases, the primary component of which is a new algorithm and software for retrieving vertical profiles of temperature and pressure from the spectra. In contrast to Earth-observing instruments, which can rely on accurate meteorological models, a priori information, and spacecraft position, Mars retrievals require a method with minimal reliance on such data. The temperature and pressure retrieval algorithms developed for this work were evaluated using Earth-observing spectra from the Atmospheric Chemistry Experiment (ACE) FTS, a solar occultation instrument in orbit since 2003, and the basis for the instrument selected for a Mars mission. ACE-FTS makes multiple measurements during an occultation, separated in altitude by 1.5–5 km, and we analyse 10 CO 2 vibration–rotation bands at each altitude, each with a different usable altitude range. We describe the algorithms and present results of their application and their comparison to the ACE-FTS data products. The Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) provides vertical profiles of temperature up to 40 km with high vertical resolution. Using six satellites and GPS radio occultation, COSMIC's data product has excellent temporal and spatial coverage, allowing us to find coincident measurements with ACE with very tight criteria: less than 1.5 h and 150 km. We present an intercomparison of temperature profiles retrieved from ACE-FTS using our algorithm, that of the ACE Science Team (v3.5), and from COSMIC. When our retrievals are compared to ACE-FTS v3.5, we find mean differences between −5 and +2 K and that our retrieved profiles have no seasonal or zonal biases but do have a warm bias in the stratosphere and a cold bias in the mesosphere. When compared to COSMIC, we do not observe a warm/cool bias and mean differences are between −4 and +1 K. COSMIC comparisons are restricted to below 40 km, where our retrievals have the best agreement with ACE-FTS v3.5. When comparing ACE-FTS v3.5 to COSMIC we observe a cold bias in COSMIC of 0.5 K, and mean differences are between −0.9 and +0.6 K.

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)0.002
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: none
Teacher disagreement score0.010
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.011
GPT teacher head0.219
Teacher spread0.208 · 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".

Quick stats

Citations6
Published2016
Admission routes2
Has abstractyes

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