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Record W4225000224 · doi:10.1002/joc.7678

Thunderstorm activity at high latitudes observed at manned<scp>WMO</scp>weather stations

2022· article· en· W4225000224 on OpenAlexaboutno aff
Daniel Kępski, Marek Kubicki

Bibliographic record

VenueInternational Journal of Climatology · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsnot available
FundersMinistry of Education and Science
KeywordsThunderstormLatitudeClimatologyEnvironmental scienceGeographyMeteorologyGeology

Abstract

fetched live from OpenAlex

Abstract Ongoing global warming particularly affects the coldest regions of our planet, where thunderstorm activity is considered to be the lowest. Scientific studies usually predict that lightning will become more frequent in polar areas in a warmer world. The aim of this study is to test this hypothesis and present the current knowledge on thunderstorm occurrence at high latitudes (>60°) based on SYNOP data from manned WMO stations operating from 2000 to 2019. According to this source, most thunderstorm events at high latitudes occur in summer (85%), when the air temperature ranges from 15 to 25°C (70%), during the days with positive temperature anomalies (75%) and negative sea‐level pressure anomalies (65%). The highest thunderstorm activity is observed over inland areas, especially in the European part of Russia. The changes in thunderstorm frequency are only visible at certain WMO manned stations and mostly during the summer months. The regional Kendall test revealed a statistically significant increase in the number of thunderstorm days north of 60°N in Interior Alaska, northwestern Canada, much of Siberia and European Russia. A decrease in thunderstorm frequency over a larger area was detected only on the shores of the southern Norwegian Sea, and seasonally in spring in the northern Urals. The observed trends were strongest in the Central Siberia and Interior Alaska regions, where the increase in the number of thunderstorm days exceeded 5 per decade. For the entire high‐latitude area, the change in the number of days with thunderstorms was statistically insignificant, but for stations located 250–1,000 km from the coastline, the averaged increase amounted 1 day per decade.

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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
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 head0.020
GPT teacher head0.252
Teacher spread0.232 · 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

Citations6
Published2022
Admission routes1
Has abstractyes

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