El Niño–Southern Oscillation signal in a new East Antarctic ice core, Mount Brown South
Bibliographic record
Abstract
Paleoclimate archives, such as high-resolution ice core records, provide a means to investigate past climate variability. Until recently, the Law Dome (Dome Summit South site) ice core record remained one of few millennial-length high-resolution coastal records in East Antarctica. A new ice core drilled in 2017/2018 at Mount Brown South, approximately 1000 km west of Law Dome, provides an additional high-resolution record that will likely span the last millennium in the Indian Ocean sector of East Antarctica. Here, we compare snow accumulation rates and sea salt concentrations in the upper portion (∼ 20 m) of three Mount Brown South ice cores and an updated Law Dome record over the period 1975–2016. Annual sea salt concentrations from the Mount Brown South site record preserve a stronger signal for the El Niño–Southern Oscillation (ENSO; austral winter and spring, r = 0.533, p < 0.001, Multivariate El Niño Index) compared to a previously defined Law Dome record of summer sea salt concentrations (November–February, r = 0.398, p = 0.010, Southern Oscillation Index). The Mount Brown South site record and Law Dome record preserve inverse signals for the ENSO, possibly due to longitudinal variability in meridional transport in the southern Indian Ocean, although further analysis is needed to confirm this. We suggest that ENSO-related sea surface temperature anomalies in the equatorial Pacific drive atmospheric teleconnections in the southern mid-latitudes. These anomalies are associated with a weakening (strengthening) of regional westerly winds to the north of Mount Brown South that correspond to years of low (high) sea salt deposition at Mount Brown South during La Niña (El Niño) events. The extended Mount Brown South annual sea salt record (when complete) may offer a new proxy record for reconstructions of the ENSO over the recent millennium, along with improved understanding of regional atmospheric variability in the southern Indian Ocean, in addition to that derived from Law Dome.
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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) | 0.001 | 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".