MétaCan
Menu
Back to cohort
Record W2133419860 · doi:10.5194/amt-8-3229-2015

A study of turbulent fluxes and their measurement errors for different wind regimes over the tropical Zongo Glacier (16° S) during the dry season

2015· article· en· W2133419860 on OpenAlexaff
Maxime Litt, Jean‐Emmanuel Sicart, Warren Helgason

Bibliographic record

VenueAtmospheric measurement techniques · 2015
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsUniversity of Saskatchewan
FundersAgence Nationale de la RechercheInstitut de Recherche pour le Développement
KeywordsSensible heatEddy covarianceKatabatic windAtmospheric sciencesLatent heatTurbulenceGlacierEnvironmental scienceSink (geography)Wind speedClimatologyGeologyMeteorologyPhysicsGeographyGeomorphology

Abstract

fetched live from OpenAlex

Abstract. Over glaciers in the outer tropics, during the dry winter season, turbulent fluxes are an important sink of melt energy due to high sublimation rates, but measurements in stable surface layers in remote and complex terrains remain challenging. Eddy-covariance (EC) and bulk-aerodynamic (BA) methods were used to estimate surface turbulent heat fluxes of sensible (H) and latent heat (LE) in the ablation zone of the tropical Zongo Glacier, Bolivia (16° S, 5080 m a.s.l.), from 22 July to 1 September 2007. We studied the turbulent fluxes and their associated random and systematic measurement errors under the three most frequent wind regimes. For nightly, density-driven katabatic flows, and for strong downslope flows related to large-scale forcing, H generally heats the surface (i.e. is positive), while LE cools it down (i.e. is negative). On average, both fluxes exhibit similar magnitudes and cancel each other out. Most energy losses through turbulence occur for daytime upslope flows, when H is weak due to small temperature gradients and LE is strongly negative due to very dry air. Mean random errors of the BA method (6 % on net H + LE fluxes) originated mainly from large uncertainties in roughness lengths. For EC fluxes, mean random errors were due mainly to poor statistical sampling of large-scale outer-layer eddies (12 %). The BA method is highly sensitive to the method used to derive surface temperature from longwave radiation measurements and underestimates fluxes due to vertical flux divergence at low heights and nonstationarity of turbulent flow. The EC method also probably underestimates the fluxes, albeit to a lesser extent, due to underestimation of vertical wind speed and to vertical flux divergence. For both methods, when H and LE compensate each other in downslope fluxes, biases tend to cancel each other out or remain small. When the net turbulent fluxes (H + LE) are the largest in upslope flows, nonstationarity effects and underestimations of the vertical wind speed do not compensate, and surface temperature errors are important, so that large biases on H + LE are expected when using both the EC and the BA method.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.576

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 head0.058
GPT teacher head0.239
Teacher spread0.181 · 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

Citations20
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueAtmospheric measurement techniquesSame topicCryospheric studies and observationsFrench-language works237,207