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Record W2127871426 · doi:10.1175/jcli3912.1

Evidence of Decadal Climate Prediction Skill Resulting from Changes in Anthropogenic Forcing

2006· article· en· W2127871426 on OpenAlexaff
Terry C. K. Lee, Francis W. Zwiers, Xuebin Zhang, Min Tsao

Bibliographic record

VenueJournal of Climate · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate variability and models
Canadian institutionsEnvironment and Climate Change CanadaUniversity of Victoria
Fundersnot available
KeywordsClimatologyForcing (mathematics)Anomaly (physics)Radiative forcingEnvironmental scienceClimate modelProbabilistic logicClimate changeGeologyMathematicsStatistics

Abstract

fetched live from OpenAlex

Abstract It is argued that simulations of the twentieth century performed with coupled global climate models with specified historical changes in external radiative forcing can be interpreted as climate hindcasts. A simple Bayesian method for postprocessing such simulations is described, which produces probabilistic hindcasts of interdecadal temperature changes on large spatial scales. Hindcasts produced for the last two decades of the twentieth century are shown to be skillful. The suggestion that skillful decadal forecasts can be produced on large regional scales by exploiting the response to anthropogenic forcing provides additional evidence that anthropogenic change in the composition of the atmosphere has influenced the climate. In the absence of large negative volcanic forcing on the climate system (which cannot presently be forecast), it is predicted that the global mean temperature for the decade 2000–09 will lie above the 1970–99 normal with a probability of 0.94. The global mean temperature anomaly for this decade relative to 1970–99 is predicted to be 0.35°C with a 5%–95% confidence range of 0.21°–0.48°C.

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)0.002
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 score0.146
Threshold uncertainty score0.453

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.026
GPT teacher head0.282
Teacher spread0.256 · 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

Citations50
Published2006
Admission routes1
Has abstractyes

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