Aerosols and clouds affecting the radiation budget at Pituffik (Thule), northern Greenland: Insights on the installed and newly developed ground-based instruments at the Thule High Arctic Atmospheric Observatory (THAAO)
Bibliographic record
Abstract
The relevance of the Arctic has become apparent in the last decades, and it is today widely agreed that this area is affected by fast and unavoidable changes taking place at the global and local scale. The Arctic environment is interesting from geopolitical, economic, and scientific perspectives, and the study of the natural components characterising the area, such as aerosols and clouds, their evolution and their response to external forcing, is of primary importance. This Dissertation contains a scientific contribution to the field of atmospheric physics focusing on satellite measurements and ground-based instruments available at the Thule High Arctic Atmospheric Observatory (THAAO, www.thuleatmos-it.it, 76.5° N, 68.8° W, 220 m a.s.l) located near Pituffik Space Base, PSB (formerly known as Thule Air Base (TAB)), in northern Greenland. In particular, aerosols produced by Canadian wildfires in 2017 strongly affected the Arctic and reached the Pituffik area. The combined analysis of surface measurements and satellite observations allowed us to estimate and extend the local radiative impact to a broader area. Clouds are another critical component of the Earth system from which most of the uncertainties in climate models and forecasts originate. This research exploited zenith spectral measurements conducted at THAAO to develop a retrieval algorithm for cloud optical thickness, especially when dealing with surfaces presenting high albedo, such as snow. The results have been compared to other methods based on different ground-based instruments and satellites.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 source (direct Gemma or distilled Codex), 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".