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Record W4293503666 · doi:10.1175/jas-d-22-0026.1

Dynamical Core Damping of Thermal Tides in the Martian Atmosphere

2022· article· en· W4293503666 on OpenAlexaff
Yuan Lian, M. I. Richardson, Claire Newman, Chris Lee, A. D. Toigo, Scott D. Guzewich, R. V. Yelle

Bibliographic record

VenueJournal of the Atmospheric Sciences · 2022
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPlanetary Science and Exploration
Canadian institutionsUniversity of Toronto
FundersNational Aeronautics and Space Administration
KeywordsAtmospheric tideMartianAtmosphere (unit)AmplitudeAtmospheric sciencesAtmosphere of MarsThermalMars Exploration ProgramAtmospheric temperatureGeophysicsEnvironmental scienceGeologyPhysicsAstrobiologyThermosphereMeteorologyIonosphere

Abstract

fetched live from OpenAlex

Abstract Atmospheric oscillations with daily periodicity are observed in in situ near-surface pressure, temperature, and winds observations and also in remotely sensed temperature and pressure observations of the Martian atmosphere. Such oscillations are interpreted as thermal tides driven by the diurnal cycle of solar radiation and occur at various frequencies, with the most prominent being the diurnal, semidiurnal, terdiurnal, and quadiurnal tides. Mars global circulation models reproduce these tides with varying levels of success. Until recently, both the MarsWRF and newly developed MarsMPAS models were able to produce realistic diurnal and semidiurnal tide amplitudes but predicted higher-order mode amplitudes that were significantly weaker than observed. We use linear wave analysis to show that the divergence damping applied within both MarsWRF and MarsMPAS is responsible for suppressing the amplitude of thermal tides with frequency greater than 2 per sol, despite being designed to suppress only acoustic wave modes. Decreasing the strength of the divergence damping in MarsWRF and MarsMPAS allows for excellent prediction of the higher-order tidal modes. This finding demonstrates that care must be taken when applying numerical dampers and filters that may eliminate some desired dynamical features in planetary atmospheres.

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)0.000
metaresearch head score (Gemma)0.001
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

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

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 head0.022
GPT teacher head0.246
Teacher spread0.224 · 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

Citations5
Published2022
Admission routes1
Has abstractyes

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