Influence of meter-scale wind-formed features on the variability of the microwave brightness temperature around Dome C in Antarctica
Bibliographic record
Abstract
Abstract. Space-borne passive microwave radiometers are widely used to retrieve information in snowy regions by exploiting the high sensitivity of microwave emission to snow properties. For the Antarctic Plateau, many studies presenting retrieval algorithms or numerical simulations have assumed, explicitly or not, that the subpixel-scale heterogeneity is negligible and that the retrieved properties were representative of whole pixels. In this paper, we investigate the spatial variations of brightness temperature over a range of a few kilometers in the Dome C area. Using ground-based radiometers towed by a vehicle, we collected brightness temperature at 11, 19 and 37 GHz at horizontal and vertical polarizations along transects with meter resolution. The most remarkable observation was a series of regular undulations of the signal with a significant amplitude reaching 10 K at 37 GHz and a quasi-period of 30–50 m. In contrast, the variability at longer length scales seemed to be weak in the investigated area, and the mean brightness temperature was close to SSM/I and WindSat satellite observations for all the frequencies and polarizations. To establish a link between the snow characteristics and the microwave emission undulations, we collected detailed snow grain size and density profiles at two points where opposite extrema of brightness temperature were observed. Numerical simulations with the DMRT-ML microwave emission model revealed that the difference in density in the upper first meter explained most of the brightness temperature variations. In addition, we found that these variations of density near the surface were linked to snow hardness. Patches of hard snow – probably formed by wind compaction – were clearly visible and covered as much as 39% of the investigated area. Their brightness temperature was higher than in normal areas. This result implies that the microwave emission measured by satellites over Dome C is more complex than expected and very likely depends on the year-to-year areal proportion of the two different types of snow.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".