The Role of Anomalously Warm Sea Surface Temperatures on the Intensity of Hurricane Juan (2003) during Its Approach to Nova Scotia
Bibliographic record
Abstract
Abstract When Hurricane Juan tracked toward Nova Scotia, Canada, in September 2003, forecasters were faced with the challenge of predicting the intensity and timing of the hurricane’s landfall. There were two competing factors dictating the storm’s intensity: 1) the decreasing sea surface temperatures (SSTs) over which the hurricane tracked that were conducive to weakening; and 2) the increased forward motion of the storm that enhanced the surface winds on the right (storm relative) side of the storm. Since Hurricane Juan was moving very quickly (forward speed approximately 15 m s−1) it spent less time over the cooler continental shelf waters between Nova Scotia and the >26°C water of the Gulf Stream than would have been the case for a slower-moving storm. However, those waters were warmer than normal during this event, by ∼4°C. It is argued that these warmer SSTs made a significant contribution (among other factors) to this rare category-2 hurricane at landfall in Nova Scotia. To assess the role of SSTs on the decay rate of Hurricane Juan, the Mesoscale Compressible Community model of the atmosphere is used. The model consists of a fixed, nested 3-km grid driven by a coarser 12-km grid, and is initiated using a synthetic hurricane vortex constructed from observational information such as storm size and intensity, thus giving a decent representation of the real storm. The model is initiated at 0000 UTC 28 September, when the hurricane was close to maximum intensity. An ensemble of experiments are conducted for each of two SST configurations: 1) analyzed SST of 28 September 2003 and 2) climatological SST representative of late September. Results from the 3-km simulations indicate that the intensity of Hurricane Juan’s maximum surface wind just prior to landfall was ∼5 m s−1 (±∼1.5 m s−1) weaker in the normal SST case, a result that is statistically significant at the 99% level. The destructiveness of the maximum landfall winds in the normal SST case is generally about 70% of that in the observed (warmer than normal) SST case. Model performance is measured using surface weather data, as well as data collected from a research aircraft that flew into the storm just prior to landfall.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".