Millennial Cycles in Greenland and Antarctic Ice Core Records: Evidence of Astronomical Influence on Global Climate
Bibliographic record
Abstract
Abstract Multimillennial‐scale climate events are well‐documented in ice‐core records from both Greenland and Antarctica, yet the role of orbital and solar input oscillations in shaping these events remains unresolved. In this study, we analyze two high‐resolution oxygen isotope records from Greenland and Antarctica to assess the influence of orbital cycles on global climate variability. Using two techniques, synchrosqueezing transform (SST) and Bayesian statistical analysis (BSA), we identify prominent climatic periodicities at ∼11, ∼5.5, and ∼2.75 kyr. The duration and amplitude of these oscillations correspond to bi‐hemispherical (BHI) and equatorial insolation (EI) cycles and their harmonic emphasizing their role in shaping climate transitions during glacial and interglacial periods. We suggest that the shorter ∼2.75 kyr cycle may match the Hallstatt cycle, which is currently interpreted as a hypothetical solar cycle but could appear to be an EI harmonic. Further comparison with high‐resolution BHI and EI records from other geographic zones confirms the presence of these cycles across multiple regions. The use of both SST and BSA techniques increases the robustness of our analysis by ensuring that potential signal artifacts are minimized and that weaker ∼5.5 and ∼2.75 kyr cycles are accurately detected. This study provides new insights into the drivers of major climate variability over the past 150,000 years, demonstrating the significant influence of BHI and EI cycles on Earth's climate system in the past and offering new perspectives on how these orbital cycles may continue to impact Earth's climate in the future.
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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 | 0.002 |
| 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 | 0.001 | 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".