The glaciers of the Dolomites: the last 40 years of melting
Bibliographic record
Abstract
Abstract. Small Alpine glaciers located below the regional equilibrium line altitude are experiencing considerable ice loss and are expected to fragment into smaller glacial bodies and eventually disappear. Monitoring such glaciers by satellite remote sensing is often challenging because their size and surrounding topography are incompatible with the current spatial resolution of non-commercial satellites. The Italian Dolomites (southeastern Alps) are a region clearly illustrating such challenges and where no long-term glacier mass balance data are available. This renowned Alpine sector hosted tens of glaciers up until a few decades ago, with now only 12 remaining. This study presents a multi-decadal (1980s–2023) estimation of surface elevation change and geodetic mass balance of the current mountain glaciers present in the area. Calculations are based on geodetic data: high resolution and accuracy are obtained with uncrewed aerial vehicle (UAV), structure from motion (SfM), and airborne light detection and ranging (lidar) methods, from 2010 to 2023. SfM on historical aerial imagery is used for previous decades. We found an average cumulative surface elevation change of -28.7±2.6 m from 1980s to 2023, 33 % of which occurred between 2010–2023. The average geodetic mass balance rate for the whole period is -0.64±0.06 mw.e.yr-1 (water equivalent), varies widely among sites, and is less negative than the Alpine reference glaciers' mass balance. Regionally, 66 % of the volume loss is related to the Marmolada glacier alone. Losses of ice mass and area show that the Dolomites are rapidly losing their glaciers.
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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 | 0.001 |
| Science and technology studies | 0.001 | 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".