Testing long-term summer temperature reconstruction based on maximum density chronologies obtained by reanalysis of tree-ring data sets from northernmost Sweden and Finland

Abstract

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.

Temperature variability in the Iberian Range since 1602 inferred from tree-ring records

“…Tree-ring data might therefore have more variance in common with the regionally averaged climatic record than with the climatic record of the nearest weather station. Generally, studies have shown that the measurements of MXD produce chronologies with an improved climatic signal (Briffa et al, 2002) as it was revealed for summer temperature reconstructions (Hughes et al, 1984;Büntgen et al, 2008;Matskovsky and Helama, 2014). However, based on a TRW chronology, the high correlation coefficient is remarkable for the full calibration period and the CRU dataset (r = −0.78).…”

Early land use and centennial scale changes in lake-water organic carbon prior to contemporary monitoring

“…S6). Regional climate reconstructions indicate that the scale of climate change during the LIA was not unprecedented (50), whereas the decline in lake-water TOC (∼10 mg·L −1 ) over the past 500 y had no precedent following the early Holocene landscape development.…”

“…An explicit separation between climate and land-use effects on lake-water TOC is complicated by the temporal overlap between the expansion of summer farms and climate cooling during the Little Ice Age (LIA), when temperatures were ∼1°C cooler than at present (50). The climate deterioration during the LIA may have contributed to the TOC decline during the period A.D. 1450-1950; however, because of the limited variation in TOC during the preceding 8,850 y despite other periods with significant changes in climate, we suggest that climate was not the main driver.…”

Bayesian multiproxy temperature reconstruction with black spruce ring widths and stable isotopes from the northern Quebec taiga

“…However, the resulting RCS chronologies are sensitive to various sampling procedures and data treatment approaches (Melvin et al 2013;Matskovsky and Helama 2014). In particular, Autin et al (2015) showed that ring width chronologies combining subfossil and living trees are prone to biases if they are built with common RCS techniques.…”