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Record W2099242177 · doi:10.5194/tc-8-853-2014

Parameterization of atmosphere–surface exchange of CO <sub>2</sub> over sea ice

2014· article· en· W2099242177 on OpenAlexafffund
Lise Lotte Sørensen, Bente Thoft Jensen, Ronnie N. Glud, Daniel F. McGinnis, Mikael K. Sejr, J. Sievers, D. H. Søgaard, Jean‐Louis Tison, Søren Rysgaard

Bibliographic record

Venue˜The œcryosphere · 2014
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsUniversity of Manitoba
FundersComisión de Investigaciones CientíficasForsknings- og InnovationsstyrelsenCanada Excellence Research Chairs, Government of CanadaDanmarks Tekniske UniversitetSight Research UKKommissionen for Videnskabelige Undersøgelser i GrønlandNatural Environment Research CouncilDanmarks GrundforskningsfondDanish Agency for Science and Higher EducationNational Research FoundationNordisk MinisterrådDeutsches Krebsforschungszentrum
KeywordsSea ice growth processesSea iceSnowSea ice thicknessAtmospheric sciencesAtmosphere (unit)BrineEnvironmental scienceFlux (metallurgy)Carbon dioxideCryosphereClimatologyGeologyChemistryMeteorologyPhysicsGeomorphology

Abstract

fetched live from OpenAlex

Abstract. We suggest the application of a flux parameterization commonly used over terrestrial areas for calculation of CO2 fluxes over sea ice surfaces. The parameterization is based on resistance analogy. We present a concept for parameterization of the CO2 fluxes over sea ice suggesting to use properties of the atmosphere and sea ice surface that can be measured or calculated on a routine basis. Parameters, which can be used in the conceptual model, are analysed based on data sampled from a seasonal fast-ice area, and the different variables influencing the exchange of CO2 between the atmosphere and ice are discussed. We found the flux to be small during the late winter with fluxes in both directions. Not surprisingly we find that the resistance across the surface controls the fluxes and detailed knowledge of the brine volume and carbon chemistry within the brines as well as knowledge of snow cover and carbon chemistry in the ice are essential to estimate the partial pressure of pCO2 and CO2 flux. Further investigations of surface structure and snow cover and driving parameters such as heat flux, radiation, ice temperature and brine processes are required to adequately parameterize the surface resistance.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.300
Threshold uncertainty score0.999

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)0.0020.000

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 head0.008
GPT teacher head0.199
Teacher spread0.191 · 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.

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

Citations21
Published2014
Admission routes2
Has abstractyes

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