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Record W1893936119 · doi:10.1002/grl.50459

Aerosol effect on climate extremes in Europe under different future scenarios

2013· article· en· W1893936119 on OpenAlexaff
Jana Sillmann, Luca Pozzoli, E. Vignati, S. Kloster, J. Feichter

Bibliographic record

VenueGeophysical Research Letters · 2013
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric chemistry and aerosols
Canadian institutionsUniversity of Victoria
FundersDeutsche Forschungsgemeinschaft
KeywordsAerosolEnvironmental scienceGreenhouse gasPrecipitationClimatologyAtmospheric sciencesClimate changeClimate modelGlobal warmingDaytimeCurrent (fluid)MeteorologyGeographyGeology

Abstract

fetched live from OpenAlex

Abstract This study investigates changes in extreme temperature and precipitation events under different future scenarios of anthropogenic aerosol emissions (i.e., SO2 and black and organic carbon) simulated with an aerosol‐climate model (ECHAM5‐HAM) with focus on Europe. The simulations include a maximum feasible aerosol reduction (MFR) scenario and a current legislation emission (CLEmod) scenario where Europe implements the MFR scenario, but the rest of the world follows the current legislation scenario and a greenhouse gas scenario. The strongest changes relative to the year 2000 are projected for the MFR scenario, in which the global aerosol reduction greatly enforces the general warming effect due to greenhouse gases and results in significant increases of temperature and precipitation extremes in Europe. Regional warming effects can also be identified from aerosol reductions under the CLEmodscenario. This becomes most obvious in the increase of the hottest summer daytime temperatures in Northern Europe.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0020.000
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 head0.022
GPT teacher head0.262
Teacher spread0.241 · 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 designSimulation or modeling
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

Citations43
Published2013
Admission routes1
Has abstractyes

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