MétaCan
Menu
Back to cohort
Record W2012542375 · doi:10.1175/jhm-d-11-0116.1

A Process-Oriented Small Lake Scheme for Coupled Climate Modeling Applications

2012· article· en· W2012542375 on OpenAlexaffabout
Murray Mackay

Bibliographic record

VenueJournal of Hydrometeorology · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate variability and models
Canadian institutionsEnvironment and Climate Change Canada
Fundersnot available
KeywordsThermoclineSensible heatEnvironmental scienceLatent heatMixed layerAtmosphere (unit)Atmospheric sciencesClimatologyClimate modelBuoyancyMeteorologyGeologyClimate changeMechanicsOceanographyGeographyPhysics

Abstract

fetched live from OpenAlex

Abstract A one-dimensional dynamic lake model is presented as a candidate for simulating small unresolved lakes within the land surface scheme of a regional or global climate model. This model is based largely on well-established process algorithms with some exceptions. The complete nonlinear surface energy balance is computed in a skin layer of arbitrary thickness in order to ensure rapid response times with the atmosphere. Turbulent mixing in the surface mixed layer is achieved through stirring and buoyancy production as well as shear production along the diurnal thermocline. The net effect of Kelvin–Helmholtz instability on thermocline structure is grossly accounted for by computing a linear temperature profile within a thermocline layer. The energetics of billowing is not considered; however, a significant thermocline leakage term is included. The model has been incorporated into the Canadian Land Surface Scheme and used to estimate regional turbulent sensible and latent heat fluxes over the Experimental Lakes Area in the boreal forest of northwestern Ontario—an area about 30% lake covered. It is demonstrated that the presence of open water has a significant effect on the net flux exchange with the atmosphere in this region. Sensible heat flux to the atmosphere is suppressed during the summer stratified period but enhanced in the fall, resulting in an increased accumulation of about 5% by the end of the open water season due to the presence of lakes. Turbulent latent heat flux to the atmosphere is more enhanced during autumn, with a final accumulation about 24% larger.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.485
Threshold uncertainty score0.505

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.027
GPT teacher head0.279
Teacher spread0.252 · 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 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

Citations61
Published2012
Admission routes2
Has abstractyes

Explore more

Same venueJournal of HydrometeorologySame topicClimate variability and modelsFrench-language works237,207