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Record W3092327759 · doi:10.1029/2020gl090844

Record‐Breaking Increases in Arctic Solar Ultraviolet Radiation Caused by Exceptionally Large Ozone Depletion in 2020

2020· article· en· W3092327759 on OpenAlexafffundabout
G. Bernhard, Vitali Fioletov, Jens‐Uwe Grooß, Iolanda Ialongo, Bjørn Johnsen, Kaisa Lakkala, G. L. Manney, Rolf Müller, Tove Svendby

Bibliographic record

VenueGeophysical Research Letters · 2020
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric Ozone and Climate
Canadian institutionsEnvironment and Climate Change Canada
FundersMiljødirektoratetEnvironment and Climate Change CanadaEuropean Space AgencyNorges ForskningsrådEuropean CommissionAcademy of Finland
KeywordsOzone depletionArcticEnvironmental scienceOzoneAtmospheric sciencesUltraviolet radiationOzone layerSubarctic climateThe arcticClimatologyMeteorologyOceanographyGeographyGeologyChemistry

Abstract

fetched live from OpenAlex

Measurements of solar ultraviolet radiation (UVR) performed between January and June 2020 at 10 Arctic and subarctic locations are compared with historical observations. Differences between 2020 and prior years are also assessed with total ozone column and UVR data from satellites. Erythemal (sunburning) UVR is quantified with the UV Index (UVI) derived from these measurements. UVI data show unprecedently large anomalies, occurring mostly between early March and mid-April 2020. For several days, UVIs observed in 2020 exceeded measurements of previous years by up to 140%. Historical means were surpassed by more than six standard deviations at several locations in the Arctic. In northern Canada, the average UVI for March was about 75% larger than usual. UVIs in April 2020 were elevated on average by about 25% at all sites. However, absolute anomalies remained below 3.0 UVI units because the enhancements occurred during times when the solar elevation was still low.

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)0.001
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 score0.019
Threshold uncertainty score0.984

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.022
GPT teacher head0.268
Teacher spread0.246 · 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

Citations68
Published2020
Admission routes3
Has abstractyes

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