Interannual and decadal variability of Arctic summer sea ice associated with atmospheric teleconnection patterns during 1850-2017
Bibliographic record
Abstract
Abstract The interannual and decadal variability of summer Arctic sea ice is analyzed, using the longest reconstruction (1850-2017) of Arctic sea ice extent available, and its relationship with the dominant internal variabilities of the climate system is further investigated quantitatively. The leading empirical orthogonal function (EOF) mode of summer Arctic sea ice variability captures an in-phase fluctuation over the Arctic Basin. The second mode characterizes a sea ice dipolar pattern with out-of-phase variability between the Pacific Arctic and the Atlantic Arctic. Summer sea ice variability is impacted by the major internal climate patterns: the Atlantic Multidecadal Oscillation (AMO), North Atlantic Oscillation (NAO), Arctic Oscillation (AO), Pacific Decadal Oscillation (PDO) and Dipole Anomaly (DA), with descending order of importance based on the multiple regression analyses. The internal climate variability of the five teleconnection patterns accounts for up to 46% of the total variance in sea ice mode 1 (thermodynamical effect), and up to 30% of the total variance in mode 2 (dynamical effect). Furthermore, the variability of sea ice mode 1 decreased from 46% during 1953-2017 to 28% during 1979-2017, while the variability of mode 2 increased from 11% during 1953-2017 to 30% during 1979-2017. The increasingly greater reduction of Arctic summer sea ice during the recent four decades was enhanced with the positive ice/ocean albedo feedback loop being accelerated by the Arctic amplification, contributed in part by the atmospheric thermodynamical forcing from -AO, +NAO, +DA, +AMO, and –PDO and by the dynamical transpolar sea ice advection and outflow driven by +DA- and +AMO-derived strong anomalous meridional winds. Further analysis, using multiple large ensembles of climate simulations and single-forcing ensembles, indicates that the mode 1 of summer sea ice, dominated by the multidecadal oscillation, is partially a forced response to anthropogenic warming.
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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 | 0.001 | 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".