Spatio-temporal variability of Arctic summer temperatures over the past 2 millennia
Peer reviewed, Journal article
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Original versionWerner J, Divine D, Ljungqvist, Nilsen T, Francus P. Spatio-temporal variability of Arctic summer temperatures over the past 2 millennia. Climate of the Past. 2018;14:527-557 https://doi.org/10.5194/cp-14-527-2018
In this article, the first spatially resolved and millennium-length summer (June–August) temperature reconstruction over the Arctic and sub-Arctic domain (north of 60°N) is presented. It is based on a set of 44 annually dated temperature-sensitive proxy archives of various types from the revised PAGES2k database supplemented with six new recently updated proxy records. As a major advance, an extension of the Bayesian BARCAST climate field (CF) reconstruction technique provides a means to treat climate archives with dating uncertainties. This results not only in a more precise reconstruction but additionally enables joint probabilistic constraints to be imposed on the chronologies of the used archives. The new seasonal CF reconstruction for the Arctic region can be shown to be skilful for the majority of the terrestrial nodes. The decrease in the proxy data density back in time, however, limits the analyses in the spatial domain to the period after 750CE, while the spatially averaged reconstruction covers the entire time interval of 1–2002CE. The centennial to millennial evolution of the reconstructed temperature is in good agreement with a general pattern that was inferred in recent studies for the Arctic and its subregions. In particular, the reconstruction shows a pronounced Medieval Climate Anomaly (MCA; here ca. 920–1060CE), which was characterised by a sequence of extremely warm decades over the whole domain. The medieval warming was followed by a gradual cooling into the Little Ice Age (LIA), with 1766–1865CE as the longest centennial-scale cold period, culminating around 1811–1820CE for most of the target region. In total over 600 independent realisations of the temperature CF were generated. As showcased for local and regional trends and temperature anomalies, operating in a probabilistic framework directly results in comprehensive uncertainty estimates, even for complex analyses. For the presented multi-scale trend analysis, for example, the spread in different paths across the reconstruction ensemble prevents a robust analysis of features at timescales shorter than ca. 30 years. For the spatial reconstruction, the benefit of using the spatially resolved reconstruction ensemble is demonstrated by focusing on the regional expression of the recent warming and the MCA. While our analysis shows that the peak MCA summer temperatures were as high as in the late 20th and early 21st centuries, the spatial coherence of extreme years over the last decades of the reconstruction (1980s onwards) seems unprecedented at least back until 750CE. However, statistical testing could not provide conclusive support of the contemporary warming to exceed the peak of the MCA in terms of the pan-Arctic mean summer temperatures: the reconstruction cannot be extended reliably past 2002CE due to lack of proxy data and thus the most recent warming is not captured.