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Record W2897031124 · doi:10.1029/2018gl079362

Predicted Chance That Global Warming Will Temporarily Exceed 1.5 °C

2018· article· en· W2897031124 on OpenAlexaff
Doug Smith, Adam A. Scaife, Ed Hawkins, Roberto Bilbao, G. J. Boer, Mihaela Caian, Louis‐Philippe Caron, Gökhan Danabasoglu, Thomas L. Delworth, Francisco J. Doblas‐Reyes, Ralf Doescher, Nick Dunstone, Rosie Eade, Leon Hermanson, Masayoshi Ishii, V. V. Kharin, Masahide Kimoto, Torben Koenigk, Yochanan Kushnir, Daniela Matei, Gerald A. Meehl, Martin Ménégoz, William J. Merryfield, Takashi Mochizuki, Wolfgang A. Müller, Holger Pohlmann, Scott B. Power, M. Rixen, Reinel Sospedra‐Alfonso, Matthias Tuma, Klaus Wyser, Xiaosong Yang, Stephen Yeager

Bibliographic record

VenueGeophysical Research Letters · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate variability and models
Canadian institutionsEnvironment and Climate Change Canada
FundersNatural Environment Research CouncilOffice of ScienceBundesministerium für Bildung und ForschungU.S. Department of EnergyBarcelona Supercomputing CenterEuropean CommissionSight Research UKNational Oceanic and Atmospheric AdministrationNational Science CouncilNational Science FoundationClimate Program OfficeDivision of Grants and AgreementsHorizon 2020 Framework ProgrammeDepartment for Business, Energy and Industrial Strategy, UK GovernmentMet OfficeDepartment for Environment, Food and Rural Affairs, UK Government
KeywordsGlobal warmingEnvironmental scienceClimatologyWarning systemClimate changeMeteorologyGeographyGeologyComputer scienceOceanography

Abstract

fetched live from OpenAlex

Abstract The Paris Agreement calls for efforts to limit anthropogenic global warming to less than 1.5 °C above preindustrial levels. However, natural internal variability may exacerbate anthropogenic warming to produce temporary excursions above 1.5 °C. Such excursions would not necessarily exceed the Paris Agreement, but would provide a warning that the threshold is being approached. Here we develop a new capability to predict the probability that global temperature will exceed 1.5 °C above preindustrial levels in the coming 5 years. For the period 2017 to 2021 we predict a 38% and 10% chance, respectively, of monthly or yearly temperatures exceeding 1.5 °C, with virtually no chance of the 5‐year mean being above the threshold. Our forecasts will be updated annually to provide policy makers with advanced warning of the evolving probability and duration of future warming events.

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)0.002
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 score0.024
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
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 head0.058
GPT teacher head0.326
Teacher spread0.268 · 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

Citations61
Published2018
Admission routes1
Has abstractyes

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