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Early reanalyses are less than optimal for investigating the regional effects of ozone depletion on Southern Hemisphere (SH) high-latitude climate because the availability of satellite sounder data from 1979 significantly improved their accuracy in data sparse regions, leading to a coincident inhomogeneity. To determine whether current reanalyses are better at SH high-latitudes in the pre-satellite era, here we examine the capabilities of the European Centre for Medium-range Weather Forecasts (ECMWF) fifth generation reanalysis (ERA5), the Twentieth Century Reanalysis version 3 (20CRv3), and the Japanese Meteorological Agency (JMA) 55-year reanalysis (JRA-55) to reproduce and help explain the pronounced change in the relationship between the Southern Annular Mode (SAM) and Antarctic near-surface air temperatures (SAT) between 1950 and 1979 (EARLY period) and 1980–2020 (LATE period). We find that ERA5 best reproduces Antarctic SAT in the EARLY period and is also the most homogeneous reanalysis across the EARLY and LATE periods. ERA5 and 20CRv3 provide a good representation of SAM in both periods with JRA-55 only similarly skilful in the LATE period. Nevertheless, all three reanalyses show the marked change in Antarctic SAM-SAT relationships between the two periods. In particular, ERA5 and 20CRv3 demonstrate the observed switch in the sign of the SAM-SAT relationship in the Antarctic Peninsula: analysis of changes in SAM structure and associated meridional wind anomalies reveal that in these reanalyses positive SAM is linked to cold southerly winds during the EARLY period and warm northerly winds in the LATE period, thus providing a simple explanation for the regional SAM-SAT relationship reversal.

The Southern Annular Mode (SAM) is the leading mode of extratropical Southern Hemisphere climate variability, associated with changes in the strength and position of the polar jet around Antarctica. This variability in the polar jet drives large fluctuations in the Southern Hemisphere climate, from the lower stratosphere into the troposphere, and stretching from the midlatitudes across the Southern Ocean to Antarctica. Notably, the SAM index has displayed marked positive trends in the austral summer season (stronger and poleward shifted westerlies), associated with stratospheric ozone loss. Historical reconstructions demonstrate that these recent positive SAM index values are unprecedented in the last millennia, and fall outside the range of natural climate variability. Despite these advances in the understanding of the SAM behavior, several areas of active research are identified that highlight gaps in our present knowledge.

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Paleoclimates and Current Trends > Earth System Behavior

While gridded seasonal pressure reconstructions poleward of 60°S extending back to 1905 have been recently completed, their skill has not been assessed prior to 1958. To provide a more thorough evaluation of the skill and performance in the early 20th century, these reconstructions are compared to other gridded datasets, historical data from early Antarctic expeditions, ship records, and temporary bases. Overall, the comparison confirms that the reconstruction uncertainty of 2–4 hPa (evaluated after 1979) over the Southern Ocean is a valid estimate of the reconstruction error in the early 20th century. Over the interior and near the coast of Antarctica, direct comparisons with historical data are challenged by elevation‐based reductions to sea level pressure. In a few cases, a simple linear adjustment of the reconstruction to sea level matches the historical data well, but in other cases, the differences remain greater than 10 hPa. Despite these large errors, comparisons with continuous multi‐season observations demonstrate that aspects of the interannual variability are often still captured, suggesting that the reconstructions have skill representing variations on this timescale, even if it is difficult to determine how well they capture the mean pressure at these higher elevations. Additional comparisons with various 20th‐century reanalysis products demonstrate the value of assimilating the historical observations in these datasets, which acts to substantially reduce the reanalysis ensemble spread, and bring the reanalysis ensemble mean within the reconstruction and observational uncertainty.