MétaCan
Menu
Back to cohort
Record W2895586530 · doi:10.3389/feart.2018.00144

The Importance of Turbulent Fluxes in the Surface Energy Balance of a Debris-Covered Glacier in the Himalayas

2018· article· en· W2895586530 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueFrontiers in Earth Science · 2018
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsUniversity of Northern British Columbia
FundersEuropean Research CouncilNederlandse Organisatie voor Wetenschappelijk OnderzoekEuropean CommissionInternational Centre for Integrated Mountain Development
KeywordsEddy covarianceLatent heatSensible heatGlacierEnvironmental scienceAtmospheric sciencesTurbulenceEnergy balanceDebrisNoonHeat fluxFlux (metallurgy)Radiative fluxRadiative transferClimatologyMeteorologyGeologyHeat transferMechanicsGeographyPhysicsMaterials scienceGeomorphology

Abstract

fetched live from OpenAlex

Surface energy balance models are common tools to estimate melt rates of debris-covered glaciers. In the Himalayas, radiative fluxes are occasionally measured, but very limited observations of turbulent fluxes on debris-covered tongues exist to date. We present measurements collected in autumn 2016 from the 26$^{th}$ of September to the 12$^{th}$ of October from an eddy correlation (EC) tower installed on the debris-covered Lirung Glacier in Nepal during the transition between monsoon and post-monsoon. Our observations suggest that surface energy losses through turbulent fluxes reduce the positive net radiative fluxes during daylight hours between 10 and 100\%, and even lead to a net negative surface energy balance after noon. During clear days, turbulent flux losses increase to over 250 W m$^{-2}$ mainly due to high sensible heat fluxes. During overcast days the latent heat flux dominates the turbulent losses and together they reach just above 100 W m$^{-2}$. Subsequently, we validate the performance of three bulk approaches in reproducing the EC observations. Large differences exist between the approaches, and accurate estimates of surface temperature, wind speed, and surface roughness are necessary for their performance to be reasonable. Moreover, the tested bulk approaches generally overestimate turbulent latent heat fluxes by a factor 3 on clear days, because the debris-covered surface dries out rapidly, while the bulk equations assume surface saturation. Improvements to bulk surface energy models should therefore include the drying process of the surface. A sensitivity analysis suggests that, in order to be useful in distributed melt models, an accurate extrapolation of wind speed, surface temperature and surface roughness in space is a prerequisite. \textcolor{red}{By applying the best performing bulk model over a complete melt period, we show that turbulent fluxes to reduce the available energy for melt at the debris surface by 17$\%$ even at very low wind speeds.} Overall, we conclude that turbulent fluxes play an essential role in the surface energy balance of debris-covered glaciers and that it is essential to include them in melt models.

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.

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)0.002
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 score0.028
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.011
GPT teacher head0.212
Teacher spread0.201 · 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