Abstract
We test the application of parametric, non-parametric, and semi-parametric calibration models for reconstructing summer (June–August) temperature from a set of tree-ring width and density data on the same dendro samples from 40 sites across Europe. By comparing the performance of the three calibration models on pairs” of tree-ring width (TRW) and maximum density (MXD) or maximum blue intensity (MXBI), we test whether a non-linear temperature response is more prevalent in TRW or MXD (MXBI) data, and whether it is associated with the temperature sensitivity and/or autocorrelation structure of the dendro parameters. We note that MXD (MXBI) data have a significantly stronger temperature response than TRW data as well as a lower autocorrelation that is more similar to that of the instrumental temperature data, whereas TRW exhibits a redder” variability continuum. This study shows that the use of non-parametric calibration models is more suitable for TRW data, while parametric calibration is sufficient for both MXD and MXBI data – that is, we show that TRW is by far the more non-linear proxy.
Highlights
Tree-ring data play a central role for reconstructing temperature and hydroclimate variability over the past one to two millennia (Cook et al, 2004, 2010, 2015; Esper et al, 2016, 2018; Ljungqvist et al, 2016, 2019b,a; Wilson et al, 2016; Anchukaitis et al, 2017)
By comparing the performance of the three calibration models on öpairs” of tree-ring width (TRW) and maximum density (MXD) or maximum blue intensity (MXBI), we test whether a non-linear temperature response is more prevalent in TRW or MXD (MXBI) data, and whether it is associated with the temperature sensitivity and/or autocorrelation structure of the dendro parameters
This study shows that the use of non-parametric calibration models is more suitable for TRW data, while parametric calibration is sufficient for both MXD and MXBI data – that is, we show that TRW is by far the more non-linear proxy
Summary
Tree-ring data play a central role for reconstructing temperature and hydroclimate variability over the past one to two millennia (Cook et al, 2004, 2010, 2015; Esper et al, 2016, 2018; Ljungqvist et al, 2016, 2019b,a; Wilson et al, 2016; Anchukaitis et al, 2017). This palaeoclimate archive has a strong advantage due to its annual resolution and absolute dating accuracy (Schweingruber, 1988; Cook and Kairiukstis, 1990; Büntgen et al, 2018) in combination with relatively good knowledge of the biological processes governing tree growth (Fritts, 1976; Speer, 2010; Anchukaitis, 2017). Techniques using reflected light from the surface of wood (blue intensity) (see Appendix A) as a surrogate for the X-ray derived MXD has shown promising results (Wilson et al, 2017a), both in terms of replicating variability of the MXD parameter by using the corresponding maximum blue intensity (MXBI) parameter (Björklund et al, 2014), and in terms of its ability to reconstruct temperature (Kaczka et al, 2018).
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