Investigations of paleoclimate variations using accelerator mass spectrometry
Bibliographic record
Abstract
This project has used Accelerator Mass Spectrometry (AMS) {sup 14}C measurements to study climate and carbon cycle variations on time scales from decades to millennia over the past 30,000 years, primarily in the western US and the North Pacific. {sup 14}C dates provide a temporal framework for records of climate change, and natural radiocarbon acts as a carbon cycle tracer in independently dated records. The overall basis for the study is the observation that attempts to model future climate and carbon cycle changes cannot be taken seriously if the models have not been adequately tested. Paleoclimate studies are unique because they provide realistic test data under climate conditions significantly different from those of the present, whereas instrumental results can only sample the system as it is today. The aim of this project has been to better establish the extent, timing, and causes of past climate perturbations, and the carbon cycle changes with which they are linked. This provides real-world data for model testing, both for the development of individual models and also for inter-model diagnosis and comparison activities such as those of LLNL's PCMDI program; it helps us achieve a better basic understanding of how the climate system works so that models can be improved; and it gives an indication of the natural variability in the climate system underlying any anthropogenically-driven changes. The research has involved four projects which test hypotheses concerning the overall behavior of the North Pacific climate system. All are aspects of an overall theme that climate linkages are strong and direct, so that regional climate records are correlated, details of fine structure are important, and accurate and precise dating is critical for establishing correlations and even causality. An important requirement for such studies is the requirement for an accurate and precise radiocarbon calibration, to allow better correlation of radiocarbon-dated records with calendric paleoclimate archives such as ice cores. The extension of the radiocarbon calibration back into the late Pleistocene (the period of deglaciation) thus constitutes a fifth project. This project has been Institute-oriented in that it was only possible through collaborations with researchers from several UC campuses, and other US and foreign institutions. These collaborators have provided expertise in sampling and access to the best available paleoclimate records. In turn, CAMS scientists have provided expertise in selecting the best samples for {sup 14}C measurements, and in interpreting radiocarbon results in terms of climate and carbon cycle changes, plus access to unmatched {sup 14}C measurement capabilities. Project output has included climate model test data plus fundamental information on the carbon cycle and the climate system, assisting LLNL modelers (and the modeling community as a whole) to improve their simulations.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".