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Record W4386405312

Persistent anticyclonic conditions and climate change exacerbated the exceptional 2022 European-Mediterranean drought

2023· article· en· W4386405312 on OpenAlexaff
Salvatore Pascale, Burak Bulut

Bibliographic record

VenueHAL (Le Centre pour la Communication Scientifique Directe) · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate variability and models
Canadian institutionsImpact
FundersEuropean Commission
KeywordsMediterranean climateClimate changeAnticycloneClimatologyPolitical scienceGeographyOceanographyGeology
DOInot available

Abstract

fetched live from OpenAlex

A prolonged drought affected Western Europe and the Mediterranean region in 2022 producing large socio-ecological impacts.The role of anthropogenic climate change (ACC) in exacerbating this drought has been often invoked in the public debate, but the link between atmospheric circulation and ACC has not received much attention so far.Here we address this question by applying the method of circulation analogs, which allows us to identify atmospheric patterns in the period 1836-2021 very similar to those occurred in 2022.By comparing the circulation analogs when global warming was absent (1836-1915) with those occurred recently , and by excluding interannual and interdecadal variability as possible drivers, we identify the contribution of ACC.The 2022 drought was associated with a persistent anticyclonic anomaly over Western Europe.Circulation analogs of this atmospheric pattern in 1941-2021 feature 500 hPa geopotential height anomalies larger in both extent and magnitude, and higher temperatures at the surface, relative to those in 1836-1915.Both factors exacerbated the drought, by increasing the area affected and enhancing soil drying through evapotranspiration.While the occurrence of the atmospheric circulation associated with the 2022 drought has not become more frequent in recent decades, the influence of the Atlantic Multidecadal oscillation cannot be ruled-out.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.030
GPT teacher head0.236
Teacher spread0.206 · 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
Published2023
Admission routes1
Has abstractno

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