Resolution Dependence of Extreme Wind Speed Projections in the Great Lakes Region
Bibliographic record
Abstract
Abstract The effect of anthropogenic climate change on extreme near-surface wind speeds is uncertain. Observed trends are weak and difficult to disentangle from internal variability, and model projections disagree on the sign and magnitude of trends. Standard coarse-resolution climate models represent the fine structures of relevant physical phenomena such as extratropical cyclones (ETCs), upper-level jet streaks, surface energy fluxes, and land surface variability less skillfully than their high-resolution counterparts. Here, we use simulations with the NCAR Community Earth System Model with both uniform (110 km) resolution and the variable-resolution configuration (VR-CESM-SONT, from 110 to 7 km) to study the effect of refined spatial resolution on projections of extreme strong and weak wind speeds in the Great Lakes region under end-of-century RCP8.5 forcing. The variable-resolution configuration projects strengthening of strong-wind events in the refined region with the opposite occurring in the uniform-resolution simulation. The two configurations provide consistent changes to synoptic-scale circulations associated with high-wind events. However, only the variable-resolution configuration projects weaker static stability, enhanced turbulent vertical mixing, and consequentially enhanced surface wind speeds because boundary layer dynamics are better captured in the refined region. Both models project increased frequency of extreme weak winds, though only VR-CESM-SONT resolves the cold-season inversions and summertime high temperatures associated with stagnant wind events. The identifiable mechanism of the changes to strong winds in VR-CESM-SONT provides confidence in its projections and demonstrates the value of enhanced spatial resolution for the study of extreme winds under climate change. Significance Statement In this study, we compare climate change projections of high and low extreme wind speeds in the Great Lakes region between a standard coarse-resolution simulation and a high-resolution simulation performed using the same climate model. The fine-resolution simulation projects strengthening high wind speeds, opposite to the coarse-resolution simulation. Both project increasing frequency of extreme weak winds, but the human-health-related impacts of stagnant winds are only captured at fine resolution. The changes in the coarse-resolution simulation are explained by changes to large-scale circulation, while the fine-resolution changes are linked to local processes the coarse model does not resolve. This helps explain the diverging projections of strong winds and gives greater credibility to the fine-resolution simulation.
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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 | 0.001 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".