A comparison of aircraft‐based surface‐layer observations over Denmark Strait and the Irminger Sea with meteorological analyses and QuikSCAT winds
Bibliographic record
Abstract
Abstract A compilation of aircraft observations of the atmospheric surface layer is compared with several meteorological analyses and QuikSCAT wind products. The observations are taken during the Greenland Flow Distortion Experiment, in February and March 2007, during cold‐air outbreak conditions and moderate to high wind speeds. About 150 data points spread over six days are used, with each data point derived from a 2‐min run (equivalent to a 12 km spatial average). The observations were taken 30–50 m above the sea surface and are adjusted to standard heights. Surface‐layer temperature, humidity and wind, as well as sea‐surface temperature (SST) and surface turbulent fluxes are compared against co‐located data from the ECMWF operational analyses, NCEP Global Reanalyses, NCEP North American Regional Reanalyses (NARR), Met Office North Atlantic European (NAE) operational analyses, two MM5 hindcasts, and two QuikSCAT products. In general, the limited‐area models are better at capturing the mesoscale high wind speed features and their associated structure; often the models underestimate the highest wind speeds and gradients. The most significant discrepancies are: a poor simulation of relative humidity by the NCEP global and MM5 models, a cold bias in 2 m air temperature near the sea‐ice edge in the NAE model, and an overestimation of wind speed above 20 m s −1 in the QuikSCAT wind products. In addition, the NCEP global, NARR and MM5 models all have significant discrepancies associated with the parametrisation of surface turbulent heat fluxes. A high‐resolution prescription of the SST field is crucial in this region, although these were not generally used at this time. Copyright © 2009 Royal Meteorological Society
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 teacher head, 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".