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Record W7163826692 · doi:10.32045/pg-2022-031

DELIMITACJA PRĄDÓW STRUMIENIOWYCH NAD PÓŁKULĄ PÓŁNOCNĄ NA PODSTAWIE REANALIZ ERA5 O WYSOKIEJ ROZDZIELCZOŚCI PRZESTRZENNEJ

2022· article· pl· W7163826692 on OpenAlexaboutno aff
Jan Degirmendžić

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2022
Typearticle
Languagepl
FieldEarth and Planetary Sciences
TopicMeteorological Phenomena and Simulations
Canadian institutionsnot available
Fundersnot available
KeywordsOrographyWind speedJet (fluid)Jet streamRADIUSLatitudePosition (finance)Wind direction

Abstract

fetched live from OpenAlex

The aim of this research is an attempt at delimiting the upper tropospheric jet streams based on high resolution (0.25°×0.25°) wind fields from ERA5. The procedure is intended to position the jet streaks (JS), i.e. regions cyclogenetically active, embedded within a jet stream. The geographic coordinates of JS-central grid (JSC) and also wind speed in that grid are specified. The analysis: extends for the winter seasons of 1981-2020, is applied to the 300-hPa level and covers the Northern Hemisphere. Jet streak center (JSC) is defined as a local wind maximum. It meets the following criteria: 1. wind speed in JSC ≥ 50 ms-1, 2. wind speed at every other grid, situated no further then 500 km from the JSC ≤ wind speed at JSC. The spherical cap matrix with constant radius equal to 500 km was used for the JSC detection. The lat×lon matrices are not applicable because their dimension decreases with increasing latitude – therefore they have an ability to detect an excessive number of small-scale wind features in high latitudes. It is an undesirable property because smaller than meso-alfa wind features cannot be classified as jet streaks. JSC points were identified on 6-hourly maps. A total number of 311 712 jet streak centers were inventoried. The results of the analysis are presented on the JSC frequency map and average JSC wind speed map. The local impact of orography was also identified on the JSC frequency maps. Macro-structure of jet streams reveals spiral-like shape with entrance region over Africa and exit region over the northern Europe. NAAJ (North Africa-Asian Jet) and EAJ (East Asian Jet) represent subtropical jet stream. Separation zone is formed from weakly active jet streaks over Himalaya. NAAJ and EAJ are relatively narrow and zonally oriented. Variability in jet stream latitude is higher over the eastern Pacific (eastern part of NPJ) and Atlantic (NAJ), which is manifested as a widening of the jet stream flow. In these two geographic regions the jet flow is WSW – ENE oriented. There is a clear division into two streams over the continents: polar in higher latitudes and subtropical. PFJ over the middle and northern Europe and STJ branch over the North America are episodic in nature. The last one, visible below 35°N in JSC frequency field, vanishes in JSC wind speed field. The jet stream over the western Pacific (EAJ / the western part of NPJ) is the strongest of all macro-scale structures in the Northern Hemisphere. Mountain areas that contribute to the formation of jet streaks by interaction with the hemispheric jet stream have been identified. These areas are as follows: Zagros Mountains, Himalayas, mountains of north-eastern Burma, Sayan and Altai Mountains, Scandinavian Mountains, Alps, Pyrenees, mountains of Scotland, Iceland and western Ireland, Japanese Alps, Kyushu Mountains, Chugach Mountains (Alaska), Coast Mountains of Canada, Cascade Range, Sierra Nevada, Sierra Madre Occidental, Appalachian Mountains (Blue Ridge Mountains, Allegheny Plateau, Adirondack Mountains) and the ice cap of southern tip of Greenland. This study presents a novel approach that enables the accurate detection of the jet streaks. It will be used in future research focusing on the contemporary changes in the position and activity of the upper tropospheric jet streams.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.009
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0000.000
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.321
GPT teacher head0.507
Teacher spread0.186 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2022
Admission routes1
Has abstractyes

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