Excess water availability in northern mid-high latitudes contiguously migrated from ocean under climate change
Bibliographic record
Abstract
Terrestrial water availability sustains livelihoods, socioeconomic development, and ecosystems. Despite an understanding of contributions of oceanic moisture to terrestrial hydroclimatic extremes, whether surpluses of terrestrial water availability migrate directly and contiguously from the ocean and the influence of climate change on this process remain unclear. Here, we use a coherent feature-tracking method to identify ocean-to-land water availability surpluses (OWASs), characterized by spatiotemporally contiguous migration of excess atmospheric freshwater (precipitation-minus-evapotranspiration) from ocean to land. Over the past several decades, especially in northern mid-high latitudes (NMHL; above 48°N), OWASs have exhibited longer persistence, wider areal extent, and greater intensity than those developed solely over land. These landward migrations are associated with seasonal Atlantic teleconnection and Pacific circulation shift. Under the business-as-usual scenario, these two processes are projected to be enhanced, markedly increasing OWAS characteristics in NMHL driven by thermodynamic atmospheric responses to future warming. Intensified OWASs may not only help alleviate long-term droughts but also have the potential to accentuate pluvial risks.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".