Characterization of transport regimes and the polar dome during Arctic spring and summer using in situ aircraft measurements
Bibliographic record
Abstract
The springtime composition of the Arctic lower troposphere is to a large extent controlled by the transport of midlatitude air masses into the Arctic. In contrast, precipitation and natural sources play the most important role during summer. Within the Arctic region sloping isentropes create a barrier to horizontal transport, known as the polar dome. The polar dome varies in space and time and exhibits a strong influence on the transport of air masses from midlatitudes, enhancing transport during winter and inhibiting transport during summer. We analyzed aircraft-based trace gas measurements in the Arctic from two NETCARE airborne field campaigns (July 2014 and April 2015) with the Alfred Wegener Institute Polar 6 aircraft, covering an area from Spitsbergen to Alaska (134 to 17 ∘ W and 68 to 83 ∘ N). Using these data we characterized the transport regimes of midlatitude air masses traveling to the high Arctic based on CO and CO 2 measurements as well as kinematic 10 d back trajectories. We found that dynamical isolation of the high Arctic lower troposphere leads to gradients of chemical tracers reflecting different local chemical lifetimes, sources, and sinks. In particular, gradients of CO and CO 2 allowed for a trace-gas-based definition of the polar dome boundary for the two measurement periods, which showed pronounced seasonal differences. Rather than a sharp boundary, we derived a transition zone from both campaigns. In July 2014 the polar dome boundary was at 73.5 ∘ N latitude and 299–303.5 K potential temperature. During April 2015 the polar dome boundary was on average located at 66–68.5 ∘ N and 283.5–287.5 K. Tracer–tracer scatter plots confirm different air mass properties inside and outside the polar dome in both spring and summer. Further, we explored the processes controlling the recent transport history of air masses within and outside the polar dome. Air masses within the springtime polar dome mainly experienced diabatic cooling while traveling over cold surfaces. In contrast, air masses in the summertime polar dome were diabatically heated due to insolation. During both seasons air masses outside the polar dome slowly descended into the Arctic lower troposphere from above through radiative cooling. Ascent to the middle and upper troposphere mainly took place outside the Arctic, followed by a northward motion. Air masses inside and outside the polar dome were also distinguished by different chemical compositions of both trace gases and aerosol particles. We found that the fraction of amine-containing particles, originating from Arctic marine biogenic sources, is enhanced inside the polar dome. In contrast, concentrations of refractory black carbon are highest outside the polar dome, indicating remote pollution sources. Synoptic-scale weather systems frequently disturb the transport barrier formed by the polar dome and foster exchange between air masses from midlatitudes and polar regions. During the second phase of the NETCARE 2014 measurements a pronounced low-pressure system south of Resolute Bay brought inflow from southern latitudes, which pushed the polar dome northward and significantly affected trace gas mixing ratios in the measurement region. Mean CO mixing ratios increased from 77.9±2.5 to 84.9±4.7 ppbv between these two regimes. At the same time CO 2 mixing ratios significantly decreased from 398.16 ± 1.01 to 393.81 ± 2.25 ppmv. Our results demonstrate the utility of applying a tracer-based diagnostic to determine the polar dome boundary for interpreting observations of atmospheric composition in the context of transport history.
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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 | 0.001 | 0.001 |
| 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 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".