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Record W4379532246 · doi:10.5194/essd-15-2295-2023

Indicators of Global Climate Change 2022: annual update of large-scale indicators of the state of the climate system and human influence

2023· article· en· W4379532246 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEarth system science data · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric and Environmental Gas Dynamics
Canadian institutionsSimon Fraser UniversityEnvironment and Climate Change Canada
FundersH2020 European Research CouncilH2020 Excellent ScienceInternational Institute for Applied Systems AnalysisMet OfficeNatural Environment Research CouncilSight Research UK
KeywordsGreenhouse gasRadiative forcingClimate commitmentClimate changeEarth system scienceEnvironmental scienceUnited Nations Framework Convention on Climate ChangeClimate modelClimatologyGlobal warmingNegotiationForcing (mathematics)Environmental resource managementPolitical scienceEffects of global warmingKyoto ProtocolEcology

Abstract

fetched live from OpenAlex

Abstract. Intergovernmental Panel on Climate Change (IPCC) assessments arethe trusted source of scientific evidence for climate negotiations takingplace under the United Nations Framework Convention on Climate Change(UNFCCC), including the first global stocktake under the Paris Agreementthat will conclude at COP28 in December 2023. Evidence-based decision-makingneeds to be informed by up-to-date and timely information on key indicatorsof the state of the climate system and of the human influence on the globalclimate system. However, successive IPCC reports are published at intervalsof 5–10 years, creating potential for an information gap between reportcycles. We follow methods as close as possible to those used in the IPCC SixthAssessment Report (AR6) Working Group One (WGI) report. We compilemonitoring datasets to produce estimates for key climate indicators relatedto forcing of the climate system: emissions of greenhouse gases andshort-lived climate forcers, greenhouse gas concentrations, radiativeforcing, surface temperature changes, the Earth's energy imbalance, warmingattributed to human activities, the remaining carbon budget, and estimates ofglobal temperature extremes. The purpose of this effort, grounded in an opendata, open science approach, is to make annually updated reliable globalclimate indicators available in the public domain (https://doi.org/10.5281/zenodo.8000192, Smith et al., 2023a). As they aretraceable to IPCC report methods, they can be trusted by all partiesinvolved in UNFCCC negotiations and help convey wider understanding of thelatest knowledge of the climate system and its direction of travel. The indicators show that human-induced warming reached 1.14 [0.9 to 1.4] ∘C averaged over the 2013–2022 decade and 1.26 [1.0 to 1.6] ∘C in 2022. Over the 2013–2022 period, human-induced warming hasbeen increasing at an unprecedented rate of over 0.2 ∘C perdecade. This high rate of warming is caused by a combination of greenhousegas emissions being at an all-time high of 54 ± 5.3 GtCO2e overthe last decade, as well as reductions in the strength of aerosol cooling.Despite this, there is evidence that increases in greenhouse gas emissionshave slowed, and depending on societal choices, a continued series of theseannual updates over the critical 2020s decade could track a change ofdirection for human influence on climate.

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.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0000.003
Scholarly communication0.0000.001
Open science0.0020.005
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.007
GPT teacher head0.236
Teacher spread0.229 · 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