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Record W2166951591 · doi:10.5194/tc-4-179-2010

Modelling snowdrift sublimation on an Antarctic ice shelf

2010· article· en· W2166951591 on OpenAlexaff
Jan T. M. Lenaerts, M. R. van den Broeke, Stephen J. Déry, Gert König‐Langlo, J. Ettema, Peter Kuipers Munneke

Bibliographic record

Venue˜The œcryosphere · 2010
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsUniversity of Northern British Columbia
Fundersnot available
KeywordsSublimation (psychology)RadiosondeEnvironmental scienceSnowMeteorologyAtmospheric sciencesClimatologyGeologyPhysics

Abstract

fetched live from OpenAlex

Abstract. In this paper, we estimate the contribution of snowdrift sublimation (SUds) to the surface mass balance at Neumayer, located on the Ekström ice shelf in Eastern Antarctica. A single column version of the RACMO2-ANT model is used as a physical interpolation tool of high-quality radiosonde and surface measurements for a 15-yr period (1993–2007), and combined with a routine to calculate snowdrift sublimation and horizontal snow transport. The site is characterised by a relatively mild, wet and windy climate, so snowdrift is a common phenomenon. The modelled timing and frequency of snowdrift events compares well with observations. This is further illustrated by an additional simulation for Kohnen base, where the timing of snowdrift is realistic, although the modelled horizontal transport is overestimated. Snowdrift sublimation is mainly dependent on wind speed, but also on relative humidity and temperature. During high wind speeds, SUds saturates and cools the air, limiting its own strength. We estimate that SUds removes around 16%±8% of the accumulated snow from the surface. The total sublimation more than triples when snowdrift is considered, although snowdrift sublimation limits sublimation at the surface. SUds shows a strong seasonal cycle, as well as large inter-annual variability. This variability can be related to the variability of the atmospheric conditions in the surface layer.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.083
Threshold uncertainty score0.997

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.023
GPT teacher head0.223
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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

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

Citations92
Published2010
Admission routes1
Has abstractyes

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