The role of North Pacific teleconnection in the sea level change of the Canadian Basin
Bibliographic record
Abstract
This study utilizes sea surface height (SSH) measurements from the CryoSat-2 satellite mission (2011–2020) to demonstrate the significant influence of the North Pacific Oscillation (NPO) on linking Pacific Ocean dynamics with sea level variability in the Canadian Basin. Results reveal a pronounced positive correlation between JJA NPO phases and SSH anomalies (SSHAs) in the Canadian Basin. During positive NPO phases, anomalous anticyclonic circulation intensifies over the Arctic, strengthening the Beaufort High. This atmospheric forcing drives enhanced freshwater transport from the Bering Sea to the Canadian Basin via the Bering Strait, thereby elevating local SSHAs. To extend the analysis beyond the observational period, the Community Earth System Model Version 2 Large Ensemble (CESM2-LE) is employed to simulate this North Pacific teleconnection mechanism driving Canadian Basin sea level variability from 1960 to 2100. The CESM2-LE results corroborate the positive NPO–SSHA relationship during 2011–2020. North Pacific pre-winter SST anomalies constitute a robust precursor for summer Canadian Basin SSH variability. These findings underscore a critical teleconnection pathway through which North Pacific SST variability modulates Arctic sea levels—a mechanism essential for refining future climate projections and regional sea level risk assessments. 研究基于2011–2020年的CryoSat-2卫星观测数据, 揭示了夏季北太平洋遥相关(NPO)与加拿大海盆的海表面高度异常(SSHA)之间存在显著的正相关关系.当NPO处于正位相时, 北极上空异常的反气旋式环流增强, 加强了波弗特高压.这种大气强迫使得从白令海向加拿大海盆输送的淡水通量增加, 从而抬升了局地SSHA.此外, 北太平洋前冬的海表温度(SST)异常, 可以作为预测后续夏季加拿大海盆海平面变化的一个有效“先兆”指标.这为提前预测北极海平面变化提供了可能性.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".