Meteorological Interpretation of Orographic Precipitation Gradients along an Andes West Slope Basin at 30°S (Elqui Valley, Chile)
Bibliographic record
Abstract
Abstract To better forecast streamflow and water resource availability, it is important to have an understanding of the meteorological drivers of the orographic precipitation gradient (OPG), especially critical in semiarid mountainous areas. Although forced ascent over topography typically results in precipitation increasing with altitude (positive OPGs), mean annual OPGs and especially OPGs associated with individual storms can change widely in magnitude and even sign. Precipitation measurements from the Elqui Valley in the semiarid Andes of Chile (30°S) reveal a mean annual OPG of 6.3 mm km−1 (millimeters of precipitation over kilometers in elevation) ranging from −42 to 52 mm km−1 for individual storms over the last 35 years (1979–2013). Reanalysis data and precipitation measurements are used to characterize the observed OPG in this region in relation with their synoptic-scale flow. It is found that the Froude number correlates positively with the OPG, reflecting stronger zonal winds and less static stability during storms that have positive OPGs. Altitude of the Andes barrier jet shows only a weak relationship with the OPG. Significant storms with positive OPGs are typically linked with an austral blocking of the westerlies and an equatorward migration of the midlatitude storm track. For negative OPGs, either a cutoff low or the northern edge of a surface migratory cyclone reaches the Elqui Valley in such a way that significant rainfall only occurs in the near-coastal region without major snowfall accumulation over the Andes.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".