A quantitative assessment of air–sea heat flux trends from ERA5 since 1950 in the North Atlantic basin
Bibliographic record
Abstract
Abstract. This work aims to investigate the temporal stability and reliability of trends in air–sea heat fluxes from ERA5 forecasts over the North Atlantic basin for the period 1950–2019. Driving forces of the trends are investigated using analyzed state quantities from ERA5. Estimating trends from reanalysis data can be challenging as changes in the observing system may introduce temporal inconsistencies. To this end, the impact of analysis increments is discussed. For individual sub-regions in the North Atlantic basin, parametrization formulas for latent and sensible heat fluxes are linearized to quantitatively attribute trends to long-term changes in wind speed, moisture, and temperature. Our results suggest good temporal stability and reliability of air–sea heat fluxes from ERA5 forecasts on sub-basin scales and below. Regional averages show that trends are largely driven by changes in the skin temperature and atmospheric advection (e.g., of warmer or drier air masses). The influence of modes of climate variability, such as the North Atlantic Oscillation (NAO) and Atlantic Multidecadal Oscillation, on the patterns found is discussed as well. Results indicate a significant impact on trends in the Irminger and Labrador seas associated with more positive NAO phases during the past 4 decades. Finally, we use basin-wide trends of air–sea heat fluxes in combination with an observational ocean heat content estimate to provide an energy-budget-based trend estimate of the Atlantic Meridional Overturning Circulation (AMOC). A decrease in area-averaged air–sea heat fluxes in the North Atlantic basin suggests a decline in the AMOC over the study period. However, basin-wide flux trends are deemed partially artificial, as indicated by temporally varying moisture increments. Thus, the exact magnitude of change is uncertain, but its sign appears robust and adds complementary evidence that the AMOC has weakened over the past 70 years.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".