Characterizing cold surge induced storm surge in the northern East China Sea: A 60-year hindcast reveals paradoxical trends in surge heights and return levels
Bibliographic record
Abstract
Recurrent cold surges represent a major hazardous weather phenomenon in the northern East China Sea. While their synoptic-scale meteorological processes are well-established, their impact on oceanic dynamics, particularly storm surge behavior, remains insufficiently understood. This study presents the first detailed hindcast and analysis of storm surges associated with 780 cold surge events over the past 60 years. The investigation focuses on the spatiotemporal characteristics and long-term variability of these storm surges, with particular attention to changes in storm surge return levels. The results reveal a general decline in the occurrence frequency, annual maxima, and spatial extent of cold surge induced storm surges. However, a paradoxical increase in surge height return levels is observed across most coastal regions. This counterintuitive trend is attributed to shifts in the surge height distribution, characterized by a rising proportion of high-percentile surge events and a decreasing occurrence of moderate-percentile surges. This redistribution alters the exceedance probability curve by flattening the upper tail of the probability density, subsequently leading to increased 20-year and 50-year return level estimates. On a monthly scale, February exhibits the most intense and widespread storm surges. Long-term trends are evident in transitional months associated with the onset and weakening of the East Asian winter monsoon. Upward trends in maximum storm surges are found in September and March, while a declining trend is observed in April. These findings provide new insights into the evolving nature of cold surge induced storm surges and their implications for coastal disaster management and mitigation strategies. • 60-year hindcast finds declined intensity of cold surge induced storm surge • Coastal storm surge return level increased despite reduced maximum surge height • Variations in return levels are linked to shift in surge height distribution • Long-term changes in surge height are concentrated in transitional months
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 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".