Seasonal temperatures in West Antarctica during the Holocene.

The recovery of long-term climate proxy records with seasonal resolution is rare because of natural smoothing processes, discontinuities and limitations in measurement resolution. Yet insolation forcing, a primary driver of multimillennial-scale climate change, acts through seasonal variations with direct impacts on seasonal climate1. Whether the sensitivity of seasonal climate to insolation matches theoretical predictions has not been assessed over long timescales. Here, we analyse a continuous record of water-isotope ratios from the West Antarctic Ice Sheet Divide ice core to reveal summer and winter temperature changes through the last 11,000 years. Summer temperatures in West Antarctica increased through the early-to-mid-Holocene, reached a peak 4,100 years ago and then decreased to the present. Climate model simulations show that these variations primarily reflect changes in maximum summer insolation, confirming the general connection between seasonal insolation and warming and demonstrating the importance of insolation intensity rather than seasonally integrated insolation or season duration2,3. Winter temperatures varied less overall, consistent with predictions from insolation forcing, but also fluctuated in the early Holocene, probably owing to changes in meridional heat transport. The magnitudes of summer and winter temperature changes constrain the lowering of the West Antarctic Ice Sheet surface since the early Holocene to less than 162 m and probably less than 58 m, consistent with geological constraints elsewhere in West Antarctica4-7.

Antarctic surface temperature and elevation during the Last Glacial Maximum.

Water-stable isotopes in polar ice cores are a widely used temperature proxy in paleoclimate reconstruction, yet calibration remains challenging in East Antarctica. Here, we reconstruct the magnitude and spatial pattern of Last Glacial Maximum surface cooling in Antarctica using borehole thermometry and firn properties in seven ice cores. West Antarctic sites cooled ~10°C relative to the preindustrial period. East Antarctic sites show a range from ~4° to ~7°C cooling, which is consistent with the results of global climate models when the effects of topographic changes indicated with ice core air-content data are included, but less than those indicated with the use of water-stable isotopes calibrated against modern spatial gradients. An altered Antarctic temperature inversion during the glacial reconciles our estimates with water-isotope observations.

A 120,000-year long climate record from a NW-Greenland deep ice core at ultra-high resolution.

We report high resolution measurements of the stable isotope ratios of ancient ice (δ18O, δD) from the North Greenland Eemian deep ice core (NEEM, 77.45° N, 51.06° E). The record covers the period 8-130 ky b2k (y before 2000) with a temporal resolution of ≈0.5 and 7 y at the top and the bottom of the core respectively and contains important climate events such as the 8.2 ky event, the last glacial termination and a series of glacial stadials and interstadials. At its bottom part the record contains ice from the Eemian interglacial. Isotope ratios are calibrated on the SMOW/SLAP scale and reported on the GICC05 (Greenland Ice Core Chronology 2005) and AICC2012 (Antarctic Ice Core Chronology 2012) time scales interpolated accordingly. We also provide estimates for measurement precision and accuracy for both δ18O and δD.

An information-theoretic approach to extracting climate signals from deep polar ice cores.

Paleoclimate records are rich sources of information about the past history of the Earth system. Information theory provides a new means for studying these records. We demonstrate that weighted permutation entropy of water-isotope data from the West Antarctica Ice Sheet (WAIS) Divide ice core reveals meaningful climate signals in this record. We find that this measure correlates with accumulation (meters of ice equivalent per year) and may record the influence of geothermal heating effects in the deepest parts of the core. Dansgaard-Oeschger and Antarctic Isotope Maxima events, however, do not appear to leave strong signatures in the information record, suggesting that these abrupt warming events may actually be predictable features of the climate's dynamics. While the potential power of information theory in paleoclimatology is significant, the associated methods require well-dated and high-resolution data. The WAIS Divide core is the first paleoclimate record that can support this kind of analysis. As more high-resolution records become available, information theory could become a powerful forensic tool in paleoclimate science.

Anomaly Detection in Paleoclimate Records Using Permutation Entropy.

Permutation entropy techniques can be useful for identifying anomalies in paleoclimate data records, including noise, outliers, and post-processing issues. We demonstrate this using weighted and unweighted permutation entropy with water-isotope records containing data from a deep polar ice core. In one region of these isotope records, our previous calculations (See Garland et al. 2018) revealed an abrupt change in the complexity of the traces: specifically, in the amount of new information that appeared at every time step. We conjectured that this effect was due to noise introduced by an older laboratory instrument. In this paper, we validate that conjecture by reanalyzing a section of the ice core using a more advanced version of the laboratory instrument. The anomalous noise levels are absent from the permutation entropy traces of the new data. In other sections of the core, we show that permutation entropy techniques can be used to identify anomalies in the data that are not associated with climatic or glaciological processes, but rather effects occurring during field work, laboratory analysis, or data post-processing. These examples make it clear that permutation entropy is a useful forensic tool for identifying sections of data that require targeted reanalysis-and can even be useful for guiding that analysis.