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Record W2129917805 · doi:10.1002/qj.2319

Impact of analyses on the dynamical balance of global and limited‐area atmospheric models

2013· article· en· W2129917805 on OpenAlexafffundabout
Kamel Chikhar, Pierre Gauthier

Bibliographic record

VenueQuarterly Journal of the Royal Meteorological Society · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate variability and models
Canadian institutionsUniversité du Québec à Montréal
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsIntertropical Convergence ZoneEnvironmental scienceClimatologyData assimilationSpurious relationshipConvectionMeteorologyInterimHorizontal resolutionAtmospheric sciencesPrecipitationMathematicsGeologyGeographyStatistics

Abstract

fetched live from OpenAlex

Dynamical imbalances can induce spurious variability which can be diagnosed from the physical tendencies observed in the first moments of short‐term forecasts using as initial conditions analyses obtained from an assimilation system using this model. In this article this approach is taken to investigate differences in the balance obtained from 3D‐ and 4D‐Var analyses, using the forecast–assimilation system of the Meteorological Service of Canada (MSC). The results indicate that the model is then in good balance globally but the 4D‐Var analyses slightly upset the balance in the Tropics, thereby altering the characteristics of the Intertropical Convergence Zone (ITCZ). As the assimilation is driven by a particular model, the resulting analyses keep an imprint of the dynamics of that model and use of this analysis with another model may not be as well in balance due to the differences between the two models. To study this point, ERA‐Interim 4D‐Var reanalyses were used as initial conditions first at a lower horizontal and vertical resolution, and then at a resolution closer to that of the Global Environmental Multiscale (GEM) model. The higher‐resolution reanalyses led to a better balance than that with a lower‐resolution version of the ERA‐Interim reanalyses. The coarser analyses create significant imbalances in the Canadian global model which persist for more than 5 days. In particular, it was noted that convection is nearly absent early on as if at a lower resolution, the ERA‐interim analyses did not inject sufficient humidity to trigger convection. It was also noted that reducing the vertical resolution is more damaging than using a coarser horizontal resolution. In limited‐area regional climate models, external analyses are used to define the boundary conditions and the Canadian Regional Climate Model (CRCM) was used to assess the impact of different ways to define the boundary conditions. The CRCM is a limited‐area configuration of the GEM global model used in the 3D‐ and 4D‐Var assimilation. Experiments were conducted in which the boundary conditions driving the CRCM are provided every 6 h as is usually done for the CRCM climate simulations. When using 4D‐Var analyses and ERA‐Interim reanalyses (coarse and full resolution) to define the boundary conditions, the results indicate that imbalances persist even after 15 days and are more significant for the coarser analyses. Moreover, even though the model exhibits relatively good balance initially, after 5 days imbalances appear gradually in the interior of the regional model domain.

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)0.004
metaresearch head score (Gemma)0.013
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 score0.022
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.013
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.030
GPT teacher head0.272
Teacher spread0.242 · 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

Citations9
Published2013
Admission routes3
Has abstractyes

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