South American (SA) societies are highly vulnerable to droughts and pluvials, but lack of long-term climate observations severely limits our understanding of the global processes driving climatic variability in the region. The number and quality of SA climate-sensitive tree ring chronologies have significantly increased in recent decades, now providing a robust network of 286 records for characterizing hydroclimate variability since 1400 CE. We combine this network with a self-calibrated Palmer Drought Severity Index (scPDSI) dataset to derive the South American Drought Atlas (SADA) over the continent south of 12°S. The gridded annual reconstruction of austral summer scPDSI is the most spatially complete estimate of SA hydroclimate to date, and well matches past historical dry/wet events. Relating the SADA to the Australia–New Zealand Drought Atlas, sea surface temperatures and atmospheric pressure fields, we determine that the El Niño–Southern Oscillation (ENSO) and the Southern Annular Mode (SAM) are strongly associated with spatially extended droughts and pluvials over the SADA domain during the past several centuries. SADA also exhibits more extended severe droughts and extreme pluvials since the mid-20th century. Extensive droughts are consistent with the observed 20th-century trend toward positive SAM anomalies concomitant with the weakening of midlatitude Westerlies, while low-level moisture transport intensified by global warming has favored extreme rainfall across the subtropics. The SADA thus provides a long-term context for observed hydroclimatic changes and for 21st-century Intergovernmental Panel on Climate Change (IPCC) projections that suggest SA will experience more frequent/severe droughts and rainfall events as a consequence of increasing greenhouse gas emissions.

Abstract. Here we analyse the maximum latewood density (MXD) chronologies of two published tree-ring data sets: one from Torneträsk region in northernmost Sweden (TORN; Melvin et al., 2013) and one from northern Fennoscandia (FENN; Esper et al., 2012). We paid particular attention to the MXD low-frequency variations to reconstruct summer (June–August, JJA) long-term temperature history. We used published methods of tree-ring standardization: regional curve standardization (RCS) combined with signal-free implementation. Comparisons with RCS chronologies produced using single and multiple (non-climatic) ageing curves (to be removed from the initial MXD series) were also carried out. We develop a novel method of standardization, the correction implementation of signal-free standardization, tailored for detection of pure low-frequency signal in tree-ring chronologies. In this method, the error in RCS chronology with signal-free implementation is analytically assessed and extracted to produce an advanced chronology. The importance of correction becomes obvious at lower frequencies as smoothed chronologies become progressively more correlative with correction implementation. Subsampling the FENN data to mimic the lower chronology sample size of TORN data shows that the chronologies bifurcate during the 7th, 9th, 17th and 20th centuries. We used the two MXD data sets to reconstruct summer temperature variations over the period 8 BC through AD 2010. Our new reconstruction shows multi-decadal to multi-centennial variability with changes in the amplitude of the summer temperature of 2.2 °C on average during the Common Era. Although the MXD data provide palaeoclimate research with a highly reliable summer temperature proxy, the bifurcating dendroclimatic signals identified in the two data sets imply that future research should aim at a more advanced understanding of MXD data on distinct issues: (1) influence of past population density variations on MXD production, (2) potential biases when calibrating differently produced MXD data to produce one proxy record, (3) influence of the biological age of MXD data when introducing young trees into the chronology over the most recent past and (4) possible role of waterlogging in MXD production when analysing tree-ring data of riparian trees.

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