Description: Climate trends in the Antarctic region remain poorly characterized, owing to the brevity and scarcity of direct climate observations and the large magnitude of interannual to decadal-scale climate variability. Here, within the framework of the PAGES Antarctica2k working group, we build an enlarged database of ice core water stable isotope records from Antarctica, consisting of 112 records. We produce both unweighted and weighted isotopic (δ18O) composites and temperature reconstructions since 0 CE, binned at 5- and 10-year resolution, for seven climatically distinct regions covering the Antarctic continent. Following earlier work of the Antarctica2k working group, we also produce composites and reconstructions for the broader regions of East Antarctica, West Antarctica and the whole continent. We use three methods for our temperature reconstructions: (i) a temperature scaling based on the δ18O–temperature relationship output from an ECHAM5-wiso model simulation nudged to ERA-Interim atmospheric reanalyses from 1979 to 2013, and adjusted for the West Antarctic Ice Sheet region to borehole temperature data, (ii) a temperature scaling of the isotopic normalized anomalies to the variance of the regional reanalysis temperature and (iii) a composite-plus-scaling approach used in a previous continent-scale reconstruction of Antarctic temperature since 1 CE but applied to the new Antarctic ice core database. Our new reconstructions confirm a significant cooling trend from 0 to 1900 CE across all Antarctic regions where records extend back into the 1st millennium, with the exception of the Wilkes Land coast and Weddell Sea coast regions. Within this long-term cooling trend from 0 to 1900 CE, we find that the warmest period occurs between 300 and 1000 CE, and the coldest interval occurs from 1200 to 1900 CE. Since 1900 CE, significant warming trends are identified for the West Antarctic Ice Sheet, the Dronning Maud Land coast and the Antarctic Peninsula regions, and these trends are robust across the distribution of records that contribute to the unweighted isotopic composites and also significant in the weighted temperature reconstructions. Only for the Antarctic Peninsula is this most recent century-scale trend unusual in the context of natural variability over the last 2000 years. However, projected warming of the Antarctic continent during the 21st century may soon see significant and unusual warming develop across other parts of the Antarctic continent. The extended Antarctica2k ice core isotope database developed by this working group opens up many avenues for developing a deeper understanding of the response of Antarctic climate to natural and anthropogenic climate forcings. The first long-term quantification of regional climate in Antarctica presented herein is a basis for data–model comparison and assessments of past, present and future driving factors of Antarctic climate.

Description: Reproducible climate reconstructions of the Common Era (1 CE to present) are key to placing industrial-era warming into the context of natural climatic variability. Here we present a community-sourced database of temperature-sensitive proxy records from the PAGES2k initiative. The database gathers 692 records from 648 locations, including all continental regions and major ocean basins. The records are from trees, ice, sediment, corals, speleothems, documentary evidence, and other archives. They range in length from 50 to 2000 years, with a median of 547 years, while temporal resolution ranges from biweekly to centennial. Nearly half of the proxy time series are significantly correlated with HadCRUT4.2 surface temperature over the period 1850–2014. Global temperature composites show a remarkable degree of coherence between high- and low-resolution archives, with broadly similar patterns across archive types, terrestrial versus marine locations, and screening criteria. The database is suited to investigations of global and regional temperature variability over the Common Era, and is shared in the Linked Paleo Data (LiPD) format, including serializations in Matlab, R and Python.