Improvement in the decadal prediction skill of the North Atlantic extratropical winter circulation through increased model resolution
Bibliographic record
Abstract
Abstract. In this study the latest version of the MiKlip decadal hindcast system is analyzed, and the effect of an increased horizontal and vertical resolution on the prediction skill of the extratropical winter circulation is assessed. Four different metrics – the storm track, blocking, cyclone and windstorm frequencies – are analyzed in the North Atlantic and European region. The model bias and the deterministic decadal hindcast skill are evaluated in ensembles of five members in a lower-resolution version (LR, atm: T63L47, ocean: 1.5∘ L40) and a higher-resolution version (HR, atm: T127L95, ocean: 0.4∘ L40) of the MiKlip system based on the Max Planck Institute Earth System model (MPI-ESM). The skill is assessed for the lead winters 2–5 in terms of the anomaly correlation of the quantities' winter averages using initializations between 1978 and 2012. The deterministic predictions are considered skillful if the anomaly correlation is positive and statistically significant. While the LR version shows common shortcomings of lower-resolution climate models, e.g., a storm track that is too zonal and southward displaced as well as a negative bias of blocking frequencies over the eastern North Atlantic and Europe, the HR version counteracts these biases. Cyclones, i.e., their frequencies and characteristics like strength and lifetime, are particularly better represented in HR. As a result, a chain of significantly improved decadal prediction skill between all four metrics is found with the increase in the spatial resolution. While the skill of the storm track is significantly improved primarily over the main source region of synoptic activity – the North Atlantic Current – the other extratropical quantities experience a significant improvement primarily downstream thereof, i.e., in regions where the synoptic systems typically intensify. Thus, the skill of the cyclone frequencies is significantly improved over the central North Atlantic and northern Europe, the skill of the blocking frequencies is significantly improved over the Mediterranean, Scandinavia and eastern Europe, and the skill of the windstorms is significantly improved over Newfoundland and central Europe. Not only is the skill improved with the increase in resolution, but the HR system itself also exhibits significant skill over large areas of the North Atlantic and European sector for all four circulation metrics. These results are particularly promising regarding the high socioeconomic impact of European winter windstorms and blocking situations.
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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 | 0.001 | 0.003 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".