Projection of near-surface winds in Antarctica using ESMs downscaled by a regional atmospheric model (MAR)
Bibliographic record
Abstract
Antarctica's climate is unique, partly due to strong westerlies on the ocean and strong easterlies at the ice sheet margins. On the continent, near-surface winds play a major role in shaping the climate of the continent as they influence sea-ice formation, the amount of precipitation reaching the ground or the stability of the boundary layer. They result from both large-scale and surface forcings, whose relative magnitude and future evolution is yet uncertain.We show an evaluation at present day of a selection of Earth System Models (ESMs) from CMIP6 and their downscalings by the regional atmospheric model MAR. The ESMs have been selected based on their demonstrated ability to represent fairly well the southern hemisphere general atmospheric circulation. They are thus expected to have a good representation of the large-scale forcing of near-surface wind. We present a framework for evaluating against field observations how accurately different CMIP6 products are able to represent near-surface winds over Antarctica. We also present the selection process for the automatic weather stations to use and the metrics for the evaluation.Then, we investigate the future evolution of near-surface winds on the Antarctic continent as projected by the ESMs and their downscalings. We show maps of their projected changes up to 2100 and investigate whether these changes are significant with regards to the internal variability of the ESMs and their historical biases. This evaluation provides us with a first step towards characterizing the future evolution of near-surface winds in Antarctica. Further work will then be undertaken to provide a more comprehensive analysis of their potential drivers, including the evolution of both large-scale and surface forcings.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".