Seasonal to interannual climate predictability in mid and high northern latitudes in a global coupled model
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.
Bibliographic record
Abstract
The upper limit of climate predictability in mid and high northern latitudes on seasonal to interannual time scales is investigated by performing two perfect ensemble experiments with the global coupled atmosphere–ocean–sea ice model ECHAM5/MPI-OM. The ensembles consist of six members and are initialized in January and July from different years of the model’s 300-year control integration. The potential prognostic predictability is analyzed for a set of oceanic and atmospheric climate parameters. The predictability of the atmospheric circulation is small except for southeastern Europe, parts of North America and the North Pacific, where significant predictability occurs with a lead time of up to half a year. The predictability of 2 m air temperature shows a large land–sea contrast with highest predictabilities over the sub polar North Atlantic and North Pacific. A combination of relatively high persistence and advection of sea surface temperature anomalies into these areas leads to large predictability. Air temperature over Europe, parts of North America and Asia shows significant predictability of up to half a year in advance. Over the ice-covered Arctic, air temperature is not predictable at time scales exceeding 2 months. Sea ice thickness is highly predictable in the central Arctic mainly due to persistence and in the Labrador Sea due to dynamics. Surface salinity is highly predictable in the Arctic Ocean, northern North Atlantic and North Pacific for several years in advance. We compare the results to the predictability due to persistence and show the importance of dynamical processes for the predictability.
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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 | 0.000 | 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 it