Changes in Interannual Variability and Decadal Potential Predictability under Global Warming
Bibliographic record
Abstract
Abstract Global warming will result in changes in mean temperature and precipitation distributions and is also expected to affect interannual and longer time-scale internally generated variability as a consequence of changes in climate processes and feedbacks. Multimodel estimates of changes in the variability of annual mean temperature and precipitation and in the variability of decadal potential predictability are investigated based on the collection of coupled climate model simulations in the Coupled Model Intercomparison Project phase 3 (CMIP3) data archive. Pooled, multimodel standard deviations of annual mean temperature and precipitation for the unforced preindustrial control climates of the models show good resemblance to observation-based estimates. The internally generated variability of the unforced climate is compared with that of the warmer conditions for simulations with the B1 and A1B climate change scenarios with forcing stabilized at year 2100 values. The standard deviation of annual mean temperature generally decreases with global warming at extratropical latitudes, with the largest percentage decreases over the oceans and largest percentage increases in the tropics and subtropics, although the magnitudes of these increases are smaller. The standard deviation of annual mean precipitation increases almost everywhere, with larger increases in the tropics. Changes are generally larger for the more strongly forced, warmer A1B scenario than for the B1 scenario. The characterization of decadal variability changes in terms of potential predictability stems from the growing interest in producing forecasts for the next decade or several decades. The potential predictability identifies that fraction of the long time-scale variability that is, at least potentially and with enough information, predictable on decadal time scales. There is a general decrease in the internally generated decadal variability of temperature and its potential predictability in the warmer world. The decrease tends to be largest where the decadal potential predictability of the unforced control climate is largest over the high-latitude oceans. The potential predictability of precipitation is small to begin with and generally decreases further. Therefore, there is a potential decrease in the decadal potential predictability of the internally generated component in a warmer world.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".