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Record W3204619218 · doi:10.5194/acp-2021-620

Measurement Report: Strong Valley Wind Events during the International Collaborative Experiment – PyeongChang 2018 Olympic and Paralympic Winter Games Project

2021· article· en· W3204619218 on OpenAlexaff
Paul Joe, GyuWon Lee, Kwonil Kim

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicWind and Air Flow Studies
Canadian institutionsEnvironment and Climate Change Canada
FundersMinistry of Science and ICT, South KoreaNational Research Foundation of KoreaKorea Meteorological AdministrationNational Research Foundation
KeywordsMeteorologyNowcastingMorningEnvironmental scienceWakeSupercellClimatologyEveningAtmospheric sciencesGeographyStormPhysicsGeology

Abstract

fetched live from OpenAlex

Abstract. Strong gusty wind events were responsible for some of the poor performances of competitors and resulted in schedule changes during the PyeongChang 2018 Olympic and Paralympic Winter Games. Three events at two venues were investigated to document and articulate the wind forecasting and nowcasting challenges. Upper air analysis showed that the Games were dominated by northwesterly synoptic flow. Froude and Reynolds number analyses indicated that vortex shedding or wake turbulence were the dominant mechanisms in the lee of the mountains where the free-style competitions were conducted. Three types of wind data (10 and 1 min averages plus 1 minute maximums) from automatic weather stations that were reported every minute were analyzed using advanced techniques (Hovmueller, wavelet and eigen analysis frequency estimation). For the two days of Event 1, the conditions were well mixed throughout the day and night. For the other events, diurnal variations were observed with a stable atmosphere at night, well mixed in the afternoon and with 2–4 hour transition periods in the morning and evenings. Turbulence was best portrayed using wavelet analysis and vortex shedding was best portrayed using the eigen analysis frequency estimation method. The latter revealed dominant frequencies, presumably associated with vortex shedding with periodicities of 20 to 90 minutes. Nowcast implications are discussed.

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 score0.026
Threshold uncertainty score0.897

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)0.0010.000

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 head0.260
Teacher spread0.237 · 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

Citations1
Published2021
Admission routes1
Has abstractyes

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