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Record W2098324926 · doi:10.5194/angeo-24-2493-2006

Winter warmings, tides and planetary waves: comparisions between CMAM (with interactive chemistry) and MFR-MetO observations and data

2006· article· en· W2098324926 on OpenAlexafffundabout
A. H. Manson, C. E. Meek, T. Chshyolkova, C. McLandress, S. K. Avery, David C. Fritts, Chris Hall, W. K. Hocking, K. Igarashi, J. W. MacDougall, Yasuhiro Murayama, C. Riggin, Denise Thorsen, R. A. Vincent

Bibliographic record

VenueAnnales Geophysicae · 2006
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric Ozone and Climate
Canadian institutionsWestern UniversityUniversity of TorontoUniversity of Saskatchewan
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Space AgencyUniversity of Saskatchewan
KeywordsEquatorLatitudeAtmospheric modelAtmospheric sciencesMiddle latitudesMesosphereLow latitudeClimatologyAtmosphere (unit)StratosphereGeologyThermosphereEnvironmental scienceIonosphereMeteorologyOceanographyGeophysicsGeographyGeodesy

Abstract

fetched live from OpenAlex

Abstract. Following earlier comparisons using the Canadian Middle Atmosphere Model (CMAM, without interactive chemistry), the dynamical characteristics of the model are assessed with interactive chemistry activated. Time-sequences of temperatures and winds at Tromsø (70° N) show that the model has more frequent and earlier stratospheric winter warmings than typically observed. Wavelets at mesospheric heights (76, 85 km) and from equator to polar regions show that CMAM tides are generally larger, but planetary waves (PW) smaller, than medium frequency (MF) radar-derived values. Tides modelled for eight geographic locations during the four seasons are not strikingly different from the earlier CMAM experiment; although monthly data now allow these detailed seasonal variations (local combinations of migrating and non-migrating components) within the mesosphere (circa 50–80 km) to be demonstrated for the first time. The dominant semi-diurnal tide of middle latitudes is, as in the earlier papers, quite well realized in CMAM. Regarding the diurnal tide, it is shown here and in an earlier study by one of the authors, that the main characteristics of the diurnal tide at low latitudes (where the S (1,1) mode dominates) are well captured by the model. However, in this experiment there are some other unobserved features for the diurnal tide, which are quite similar to those noted in the earlier CMAM experiment: low latitude amplitudes are larger than observed at 82 km, and middle latitudes feature an unobserved low altitude (73 km) summer maximum. Phases, especially at low and middle (circa 42° N) latitudes, do not match observations well. Mesospheric seasonal tidal variations available from the CUJO (Canada U.S.\\ Japan Opportunity) radar (MFR) network (sites 40–45° N) reveal interesting longitudinal differences between the CMAM and the MFR observations. In addition, model and observations differ in the character of the vertical phase variations at each network-location. Finally, the seasonal variations of planetary wave (PW) activity available from CMAM and the MFR show quite good agreement, apart from the amplitude differences (smaller in CMAM above 70 km). A major difference for the 16-d PW is that CMAM shows large amplitudes before the winter solstice; and for the 2-d PW, while both CMAM and MFR show summer and winter activity, the observed summer mesopause and winter mesospheric wave activities are stronger and more extended in height. Models such as CMAM, operated without data-assimilation, are now able to provide increasingly realistic climatologies of middle atmosphere tides and PW activity. Differences do exist however, and so discussion of the various factors affecting tidal and PW characteristics in atmospheres, modelled and observed, is provided. Other diagnostics of model-characteristics and of future desirable model experiments are suggested.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.520

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.029
GPT teacher head0.239
Teacher spread0.210 · 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 designObservational
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

Citations23
Published2006
Admission routes3
Has abstractyes

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