Interpretation of the High Resolution, Multivariate Mt. Logan (Yukon Territory) Ice Core - A Record of North Pacific Climate and Atmospheric Chemistry
Bibliographic record
Abstract
The recently developed Mt. Logan ice core glaciochemical dataset provides an unprecedented opportunity to understand Holocene climate change and the sources and fluxes of natural and anthropogenic chemicals in the North Pacific atmosphere. The 185 m-long ice core has been sampled at very high resolution using a refined and updated continuous ice core melter system, and analyzed for over 40 chemical species, including major ions, trace elements, rare earth elements, and stable isotopes. Subseasonal samples spanning the top ~500 years allow for annual layer counting, followed by ice flow modeling for the remainder of the timescale spanning the Holocene and portions of the late glacial period. Its continuous and high-resolution samples, breadth of co-registered chemical measurements, time span and location in the North Pacific free troposphere make the Mt. Logan glaciochemical dataset a new benchmark in ice core analyses with the potential for understanding paleoclimate variability and atmospheric chemistry far beyond the boundaries of the soon to be completed initial project. Interpretation of the new Mt. Logan record suggests that anthropogenic pollutants from Asia.have contaminated the North Pacific free troposphere since the early 1970s. Mt. Logan dust and sea-salt concentrations show statistically significant correlations to atmospheric pressure centers over their Asian desert and Pacific Ocean source regions, respectively. Funds are requested for a graduate student, and subsequent post-doctoral researcher, to continue interpretation of this unique record, and produce additional chemical time series from existing samples and archived core. This graduate student was responsible for expanding the University of Maine capabilities continuous ice melter system, producing the Mt. Logan glaciochemical record, and interpreting the dataset, and consequently has pre-existing, extensive knowledge of the dataset and the study area.Intellectual Merit of the Proposed Activity: This research will build upon previousinterpretations of the Mt. Logan record, while adding specific new time series to clarify the sources of Asian anthropogenic metals and natural dust. It will directly contribute to the understanding of: 1) Anthropogenic and natural aerosol emissions and their sources, particularly from Asia,2) Millennial scale Northern Hemisphere Holocene climate variability and forcing mechanisms,3) Annual to decadal scale North Pacific Holocene climate variability and forcing mechanisms,4) Recent climate change in the North Pacific that is climatologically linked to Earth's, thus far, region of greatest response to greenhouse gas warming, the Arctic. Using multivariate statistics and time series analyses, the timing, intensity and forcing mechanisms of North Pacific annual to millennial climate fluctuations will be investigated by comparing the Mt. Logan summit record to regional proxy records from ice cores at lower elevations, tree rings, lake and marine sediment cores, glaciers, and existing climate forcing records. Links between northern hemisphere and tropical climate patterns and the nature of global Holocene climate shifts will be investigated by comparing the Mt. Logan record to ice core and paleoclimate proxy records from globally distributed locations.Broader Impacts: Interpretations from this record will contribute to understand the potential for future climate changes over North America, the Pacific and Asia, and the impact of land-use changes and industrialization by Asian countries on the North American atmosphere. All data produced by this project will be provided to WDC-A for Glaciology and WDC for paleoclimatology.
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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 | 0.002 |
| 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) | 0.001 | 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".