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Record W7162014141 · doi:10.82308/51923

Validating Canadian land surface scheme heat fluxes under subarctic tundra conditions

2002· dissertation· en· W7162014141 on OpenAlexaboutno aff
David G. Rodgers

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsnot available
Fundersnot available
KeywordsPermafrostSubarctic climateTundraPeatWater contentSubsoilLatent heatSoil water

Abstract

fetched live from OpenAlex

This study tests the ability of the Canadian Land Surface Scheme (CLASS) to simulate sensible and latent heat fluxes over two subarctic tundra sites in the Trail Valley Creek (TVC) drainage basin, North West Territories, Canada. CLASS simulations with and without the new organic soil parameterisation developed for peatland conditions were compared with three summer months of measurements at each site. The sites are located in a cryoturbated region and are underlain by continuous permafrost and feature mineral soil hummocks and organic soil inter-hummock zones. Results from the peatland version of CLASS showed significant improvement over the standard version although in both cases, there was an underestimation of latent heat fluxes and overestimation of sensible heat fluxes. The observed soil moisture contents are almost constant at both sites. Field photographs show the sites are located in low-lying areas, one in a local depression and the other at the bottom of a valley. Thus, it is reasonable to assume that the constant soil moisture content is maintained by lateral flow from adjacent hillslopes. This assumption could be further supported by the influence of mineral earth hummocks in TVC drainage basin. CLASS is a one-dimensional column model and it is not possible to explicitly represent lateral flow. Thus a nudging module is added to the peatland version of CLASS to reflect this horizontal water movement. Simulations were further improved with this modification. This additional module is a simple and effective way to represent the effect of lateral flow.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.093
Threshold uncertainty score0.188

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.045
GPT teacher head0.261
Teacher spread0.216 · 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 designBench or experimental
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

Citations0
Published2002
Admission routes1
Has abstractyes

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