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Record W2023528449 · doi:10.1175/bams-87-4-465

Weather And Death On Mount Everest: An Analysis Of The Into Thin Air Storm

2006· article· en· W2023528449 on OpenAlexafffund
G. W. K. Moore, John L. Semple

Bibliographic record

VenueBulletin of the American Meteorological Society · 2006
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHigh Altitude and Hypoxia
Canadian institutionsUniversity of Toronto
FundersNational Oceanic and Atmospheric AdministrationNatural Sciences and Engineering Research Council of CanadaEuropean Centre for Medium-Range Weather Forecasts
KeywordsMountTroposphereStormClimatologyEnvironmental scienceWinter stormSynoptic scale meteorologyMeteorologyAtmospheric sciencesGeologyGeography

Abstract

fetched live from OpenAlex

Scientific interest in Mount Everest has been largely focused on the physiology of hypoxia caused by the summit's low barometric pressure. Although weather is recognized as a significant risk for climbers on the mountain, it has not been extensively studied. In this paper, we reconstruct the meteorological conditions associated with the deadly outbreak of high-impact weather on Mount Everest that occurred in May 1996 and was the subject of the best-selling book Into Thin Air. The authors show that during this event, two jet streaks—an upper-level shortwave trough and an intrusion of stratospheric air into the upper troposphere—were present in the vicinity of Mount Everest. Meanwhile, in the lower troposphere, there was convergence of water vapor transport from both the Arabian Sea and the Bay of Bengal into the region to the south of Mount Everest. The authors propose that the ageostrophic circulation associated with the upper-level features resulted in a region of large-scale ascent near Mount Everest that, in combination with the anomalous availability of moisture in the region, triggered convective activity. The resulting high-impact weather trapped over 20 climbers on Mount Everest's exposed upper slopes leading to the deaths of 8. These synoptic-scale characteristics provide some expectation of predicting life-threatening high-altitude storms in the Himalayas. In addition, the authors argue that the falling barometric pressure and the presence of ozone-rich stratospheric air that occurred near the summit of Mount Everest during this event could have shifted a coping climber from a state of brittle tolerance to physiological distress.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.495
Threshold uncertainty score0.389

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 studies0.0000.001
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 head0.007
GPT teacher head0.236
Teacher spread0.228 · 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

Citations38
Published2006
Admission routes2
Has abstractyes

Explore more

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