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Record W2056110566 · doi:10.1175/jas3483.1

The GCM Response to Current Parameterizations of Nonorographic Gravity Wave Drag

2005· article· en· W2056110566 on OpenAlexaff
C. McLandress, John Scinocca

Bibliographic record

VenueJournal of the Atmospheric Sciences · 2005
Typearticle
Languageen
FieldPhysics and Astronomy
TopicIonosphere and magnetosphere dynamics
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsDissipationNonlinear systemDragPhysicsGCM transcription factorsMomentum (technical analysis)Gravity waveMechanicsGravitational waveParameterized complexityGeneral Circulation ModelGeologyComputer scienceClimate changeThermodynamicsAstrophysics

Abstract

fetched live from OpenAlex

Abstract A comparison is undertaken of the response of a general circulation model (GCM) to the nonorographic gravity wave drag parameterizations of Hines, Warner and McIntyre, and Alexander and Dunkerton. The analysis is restricted to a comparison of each parameterization’s nonlinear dissipation mechanism since, in principle, this is the only component that differs between the schemes. This is achieved by developing a new, more general parameterization that can represent each of these dissipation mechanisms, while keeping all other aspects of the problem identical. The GCM simulations reveal differences in the climatological response to the three dissipation mechanisms. These differences are documented for both tropopause and surface launch elevations of the parameterized waves. The simulations also reveal systematic differences in the height at which momentum is deposited. This behavior is investigated further in a set of experiments designed to reduce these systematic differences, while leaving the details of the dissipation mechanisms unaltered. These sensitivity experiments demonstrate that it is possible to obtain nearly identical responses from all three mechanisms, which indicates that the GCM response is largely insensitive to the precise details of the dissipation mechanisms. This finding is supported by an additional experiment in which the nonlinear dissipation mechanisms are turned off and critical-level filtering is left to act as the only source of dissipation. In this experiment, critical-level filtering effectively replaces the nonlinear dissipation mechanism, producing a nearly identical response. The results of this study suggest that climate modeling efforts would potentially benefit more from the refinement of other aspects of the parameterization problem, such as the properties of the launch spectrum, than they have benefited from the refinement of dissipation mechanisms.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.738
Threshold uncertainty score0.376

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.011
GPT teacher head0.260
Teacher spread0.249 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
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

Citations79
Published2005
Admission routes1
Has abstractyes

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