Weather Observations Across the Southern Andes at 53°S
Bibliographic record
Abstract
Regional variations of weather pattern were analyzed along a west-to-east profile across the Southern Andes (53°S), one of the most pronounced climate-divides in the world. For the first time we present a meteorological record from an array of three automatic weather stations (AWS), operated by the authors, for the central part of the climate divide which, together with previously existing Chilean weather stations, complete the transect. These data cover a time period of 3 yr. from October 1999 until September 2002. Air temperatures along the profile are highly correlated. Annual precipitation drops from between 6000 mm and 7000 mm at sea level along the main divide of the mountains to only about 1000 mm at the eastern slopes of the Andes and to as little as 430 mm at Punta Arenas. The variations of rainfall with wind direction and synoptic weather types are markedly different between the central part of the Andes and Punta Arenas. At the center of the climate divide precipitation correlates positively with wind speed from the west, whereas at Punta Arenas, east of the Andes, higher rainfall rates occur with easterly air flow. It is assumed that this reflects the barrier effect of the mountain range of the Andes. The results indicate that in order to make references about present or past climatic variations in Patagonia, it is essential to consider the effect of changes in circulation patterns.
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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 | 0.001 | 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".