Whole-island wind bifurcation and localized topographic steering: Impacts on aeolian dune dynamics
Bibliographic record
Abstract
Topographic steering has been observed around Gran Canaria, a high-profile circular island located in the Canary Island Archipelago, Spain, culminating in a complex lee-side wind regime at the Maspalomas dunefield. Maspalomas has experienced rapid environmental changes since the 1960s, coincident with a boom in the tourism industry in the region and requires further examination on the linkages between meso-scale airflow patterns and aeolian processes modifying the landscape. The aim of this work is to simulate mean and turbulent airflow conditions at Maspalomas due to incremental changes in the regional wind direction and to compare these results to the predicted and observed aeolian dynamics taken from meteorological records, a global wind retro-analysis model, and remote sensing data. A Smagorinsky Large Eddy Simulation (S-LES) model was used to identify meso-scale airflow perturbations and turbulence at different locations around the island. Variability in meteorological data was also identified, with sites recording accelerated or retarded velocities and directional distributions ranging between unimodal to bimodal. Using a global retro-analysis model, relatively consistent up-wind conditions were predicted over a period coinciding with three aerial LiDAR surveys (i.e., 2006, 2008, and 2011) at the Maspalomas dunefield. Despite the consistent predicted airflow conditions, dune migration rates dropped from 7.26 m y−1 to 2.80 m y−1 and 28% of dunes experienced crest reversal towards the east, or opposite of the primary westerly migration direction during the second time period. Our results indicate that meso-scale airflow steering alters local wind conditions that can modify sediment transport gradients at Maspalomas. Given the rapidity of environmental changes and anthropogenic impacts at Maspalomas, these findings improve our understanding on the aeolian dynamics at Maspalomas and can be used to inform future management strategies. Lastly, the approach used in this study could be applied to other high-profile island settings or similarly complex aeolian environments.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".