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Record W2272341249 · doi:10.5194/tc-10-313-2016

Cloud effects on surface energy and mass balance in the ablation area of Brewster Glacier, New Zealand

2016· article· en· W2272341249 on OpenAlexaff
Jonathan P. Conway, Nicolas J. Cullen

Bibliographic record

Venue˜The œcryosphere · 2016
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsOvercastGlacierEnvironmental scienceAlbedo (alchemy)Ablation zoneSkyCloud coverGlacier mass balancePrecipitationAtmospheric sciencesEnergy balanceEarth's energy budgetLatent heatClimatologyMeteorologyGeologyRadiationGeomorphologyCloud computingPhysics

Abstract

fetched live from OpenAlex

Abstract. The effect of clouds on glacier surface energy balance (SEB) has received increased attention in the last decade, but how clouds interact with other meteorological forcing to influence surface mass balance (SMB) is not as well understood. This paper resolves the SEB and SMB at a site in the ablation zone of Brewster Glacier over a 22-month period, using high-quality radiation data to carefully evaluate SEB terms and define clear-sky and overcast conditions. A fundamental change in glacier SEB in cloudy conditions was driven by increased effective sky emissivity and surface vapour pressure, rather than a minimal change in air temperature and wind speed. During overcast conditions, positive net long-wave radiation and latent heat fluxes allowed melt to be maintained through a much greater length of time compared to clear-sky conditions, and led to similar melt in each sky condition. The sensitivity of SMB to changes in air temperature was greatly enhanced in overcast compared to clear-sky conditions due to more frequent melt and changes in precipitation phase that created a strong albedo feedback. During the spring and autumn seasons, the sensitivity during overcast conditions was strongest. To capture these processes, future attempts to explore glacier–climate interactions should aim to resolve the effects of atmospheric moisture (vapour, cloud, and precipitation) on melt as well as accumulation, through enhanced statistical or physically based methods.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.072
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 studies0.0000.000
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 head0.011
GPT teacher head0.193
Teacher spread0.182 · 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

Citations43
Published2016
Admission routes1
Has abstractyes

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