Synoptic control over orographic precipitation distributions during OLYMPEX
Bibliographic record
Abstract
During the Olympic Mountains Experiment (OLYMPEX) in Washington State in winter 2015-16, intensive precipitation and upper-air measurements were obtained within frontal systems traversing the Olympic mountain range. In this study, an analysis and interpretation of the observed precipitation distributions, as a function of synoptic conditions, is undertaken. The synoptic conditions are categorized as warm-frontal (ahead of a surface warm front), warm-sector (between the surface warm and cold fronts), and post-frontal (behind the surface cold front). Six periods of each frontal class are selected, for which observed precipitation distributions are retrieved using a combination of operational S-band radars and a relatively dense regional rain-gauge network. Radar and rain gauge data is merged using a unique combination of bias correction and optimal estimation techniques. Not surprisingly, far greater orographic precipitation amounts are observed during warm-frontal and warm-sector periods than during post-frontal periods. The warm-sector periods exhibit the largest orographic enhancement directly over the massif, the warm-frontal periods exhibit a smaller enhancement over a large area upstream of the mountain and the post-frontal periods are characterised by a local maximum at the foot of the mountain. Analysis of upstream soundings indicates that the upstream shift of precipitation in warm frontal and postfrontal conditions is associated with a large nondimensional mountain height, suggesting strong upstream blocking. To enhance the physical interpretation, quasi-idealized simulations with the Weather Research and Forecasting (WRF) model are conducted. The simulations use the real Olympics terrain and idealized soundings based on the upper-air observations. Crucially, upstream precipitation (an element often missing from idealized orographic precipitation simulations) is considered by applying a large-scale lifting profile in the warm-frontal and warm-sector simulations, or by producing oceanic cellular convection upstream of the Olympics for the post-frontal simulations. Key differences between observed frontal periods are reproduced by the simulations. Sensitivity tests of upstream precipitation indicate that while the structure of the orographic enhancement fundamentally changes when upstream precipitation is included, the degree of orographic enhancement is not strongly dependent on the intensity of the upstream precipitation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 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".