Evidence of Decadal Climate Prediction Skill Resulting from Changes in Anthropogenic Forcing
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.039 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".