Variability of north Pacific ocean surface sensible and latent heat fluxes
Bibliographic record
Abstract
Interannual variability in North Pacific Ocean (20°N — 56°N) winter-time surface sen sible and latent heat fluxes and their relation to Northern Hemisphere sea-level pressure and 500 mb height fields is explored. Observational data based on the Comprehen sive Ocean-Atmosphere Data Set (COADS) and National Meteorological Center (NMC) gridded data set over the 1950—89 period are analysed and compared with 10 years of simulated data from the Canadian Climate Centre (CCC) second generation general cir culation model (GCM). Two regions of the North Pacific Ocean are examined closely: the Kuroshio Current region (KCR), where the mean and anomalies of the heat fluxes are largest (implying a strong link between the ocean and atmosphere); and a region in the central North Pacific (NPR) near 3l°N 165°W where the heat flux means and anomalies are moderately large and where several authors have found a strong correlation between sea surface temperatures and the Northern Hemisphere atmospheric circulation. In the COADS/NMC data, positive KCR heat flux anomalies are associated with sig nificant differences from the climatological mean atmospheric fields: there are stronger ridges over Eastern Asia and Western North America, and deeper troughs over the North west Pacific and Northwest Atlantic. These patterns are similar to previous modelling studies of the atmospheric response to positive heat flux and sea surface temperature anomalies, and to a dominant mode of variability observed in the 500 mb height field known as the Western Pacific (WP) pattern. The corresponding GCM relations are quite different. Positive KCR heat flux anomalies are associated with a deeper trough over the Northeast Pacific and Northwest Atlantic at sea-level pressure, and a deeper trough over the Northwest Pacific at 500 mb. The atmospheric anomalies associated with NPR heat flux anomalies are generally weaker than those accompanying KCR heat flux anomalies. In the COADS/NMC data, positive NPR latent heat flux anomalies are associated with deeper troughs over the Northeast Pacific and Eastern North America, stronger jets, a stronger ridge over Western North America, and a more intense Aleutian Low. However, positive NPR sensible heat flux anomalies are associated with weaker atmospheric anomalies in the opposite sense: a shallower trough over Eastern North America, a weaker North American Jet, a weaker ridge over Western North America, and a less intense Aleutian Low. The corresponding GCM relations are somewhat similar, with positive NPR heat flux anomalies accompanied by a deeper trough over the Northeast Pacific and a stronger ridge and weaker trough over North America. VARIMAX rotated principal component analysis shows the two dominant modes of variation of COADS and GCM sensible and latent heat fluxes are strongly associated with variability over KCR and NPR, respectively. The greater complexity of the GCM principal components may reflect the smaller signal-to-noise ratio in the model data and the limitations of the mixed-layer ocean model. It also suggests spatial autocorrelation within the COADS and GCM heat flux fields is very different. This difference may have important implications for a more complete assessment of the model’s simulation of both the observed atmospheric fields (“current” climate) and the anticipated changes in atmospheric circulation due to anthropogenic emissions of greenhouse gases.
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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 | 0.001 |
| 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) | 0.001 | 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".