Recent variability and trends of Antarctic near-surface temperature

A new monthly 1 degrees x 1 degrees Antarctic near-surface temperature reconstruction for 1960-2005 is presented. The use of numerical model fields to establish spatial relationships between fifteen continuous observational temperature records and the voids to which they are interpolated inherently accounts for the effects of the atmospheric circulation and topography on temperature variability. Employing a fixed observation network ensures that the reconstruction uncertainty remains constant in time. Comparison with independent observations indicates that the reconstruction and two other gridded observational temperature records are useful for evaluating regional near-surface temperature variability and trends throughout Antarctica. The reconstruction has especially good skill at reproducing temperature trends during the warmest months when melt contributes to ice sheet mass loss. The spatial variability of monthly near-surface temperature trends is strongly dependent on the season and time period analyzed. Statistically insignificant (p > 0.05) positive trends occur over most regions and months during 1960-2005. By contrast, 1970-2005 trends are weakly negative overall, consistent with positive trends in the Southern Hemisphere Annular Mode (SAM) during summer and autumn. Subtle near-surface temperature increases during winter from 1970 to 2000 are consistent with tropospheric warming from radiosonde records and a lack of winter SAM trends. Widespread but statistically insignificant (p > 0.05) warming over Antarctica from 1992 to 2005 coincides with a leveling off of upward SAM trends during summer and autumn since the mid-1990s. Weakly significant annual trends (p < 0.10) of about +1 K decade(-1) are found at three stations in interior and coastal East Antarctica since 1992. The subtle shift toward warming during the past 15 years raises the question of whether the recent trends are linked more closely to anthropogenic influences or multidecadal variability.