Event‐Scale Dynamics of a Parabolic Dune and Its Relevance for Mesoscale Evolution
Bibliographic record
Abstract
Abstract Parabolic dunes are widespread aeolian landforms found in a variety of environments. Despite modeling advances and good understanding of how they evolve, there is limited empirical data on their dynamics at short time scales of hours and on how these dynamics relate to their medium‐term evolution. This study presents the most comprehensive data set to date on aeolian processes (airflow and sediment transport) inside a parabolic dune at an event scale. This is coupled with information on elevation changes inside the landform to understand its morphological response to a single wind event. Results are contextualized against the medium‐term (years) allowing us to investigate one of the most persistent conundrums in geomorphology, that of the significance of short‐term findings for landform evolution. Our field data suggested three key findings: (1) sediment transport rates inside parabolic dunes correlate well with wind speeds rather than turbulence; (2) up to several tonnes of sand can move through these landforms in a few hours; and (3) short‐term elevation changes inside parabolic dunes can be complex and different from long‐term net spatial patterns, including simultaneous erosion and accumulation along the same wall. Modeled airflow patterns along the basin were similar to those measured in situ for a range of common wind directions, demonstrating the potential for strong transport during multiple events. Mesoscale analyses suggested that the measured event was representative of the type of events potentially driving significant geomorphic changes over years, with supply‐limiting conditions playing an important role in resultant flux amounts.
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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 | 0.001 |
| 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) | 0.001 | 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".