Spatial reconstruction of Scottish summer temperatures from tree rings

Abstract

A detailed understanding of past temporal patterns and spatial expression of temperature variations is important to place recent anthropogenic climate change into a longer term context. In order to fill the current gap in our understanding of northwest European temperature variability, point‐by‐point principal component regression was used to reconstruct a spatial field of 0.5° temperature grids across Scotland. A sequence of reconstructions utilizing several combinations of detrending and disturbance correction procedures, and a selection of tree‐ring parameters [including ring width (RW), maximum latewood density (MXD) and blue intensity (BI)] was used in an evaluation of reconstruction skill. The high resolution of the reconstructed field serves also as a diagnostic tool to spatially assess the temperature reconstruction potential of local chronologies. Best reconstruction results, reaching calibration r2 = 65.8% and verification r2 = 63.7% in central Scotland over the 1901–1976 period, were achieved using disturbance‐corrected and signal‐free detrended RW chronologies merged with BI data after low‐pass (high‐pass) filtering the RW (BI) chronologies. Calibration and verification r2 > 50% was attained for central, north and east Scotland, >40% in west and northwest, and >30% in southern Scotland with verification of nearly all grids showing some reconstruction skill. However, the full calibration potential of reconstructions outside central Scotland was reduced either due to residual disturbance trends undetected by the disturbance correction procedure or due to other climatic or non‐climatic factors which may have adversely affected the strength of the climate signal.

Scientific Merits and Analytical Challenges of Tree‐Ring Densitometry

“…However, as this correction was found to be imperfect in fully correcting discoloration biases, Björklund et al () proposed a BI contrast adjustment prior to the calculation of delta BI, producing encouraging results. Features of discoloration bias can also be mathematically filtered out (Rydval, Loader, et al, ; Rydval, Gunnarson, et al, ; Sheppard, ), though this approach typically only retains up to decadal scale variability.…”

“…Despite limitations, maximum BI has featured in a number of climate response and reconstruction studies (primarily summer temperature) that have been partly (or entirely) derived from this parameter, covering many regions, including northern (Björklund et al, ; Fuentes et al, ; Linderholm et al, ; McCarroll et al, ), northwest (Rydval, Gunnarson, et al, , Rydval, Loader, et al, ; Tene et al, ; Wilson et al, ), western (Trachsel et al, ), and eastern Europe (Kaczka et al, , ; Rydval et al, ), North America (Wilson et al, ; Wilson, D'Arrigo, et al, ), and the Caucasus (Dolgova, ). The parameter has also been included in large‐scale (hemispheric) reconstructions of temperature (Anchukaitis et al, ; Wilson et al, ) and the development of a temperature reconstruction in the tropics (Buckley et al, ).…”

Improved dendroclimatic calibration using blue intensity in the southern Yukon

“…LWB expresses similar information to MXD as both essentially measure the combined hemicellulose, cellulose and lignin content of the latewood, which is well correlated with summer temperatures. LWB (and related reflectance parameter) chronologies have been successfully used in several summer temperature reconstructions (Björklund et al, 2015;Fuentes et al 2018;Rydval et al, 2017aRydval et al, , 2017bWilson et al, 2014Wilson et al, , 2017. However, LWB is arguably still an experimental TR parameter and more studies are needed to evaluate its utility for different species and across multiple regions.…”

“…Similarly, many conifer species express a distinct colour change between darker heartwood to lighter sapwood, again inducing low frequency related colour intensity biases. Multiple methods have been proposed to overcome these potential biases, but application of these approaches remains limited (Björklund et al, 2014(Björklund et al, , 2015Rydval et al 2017aRydval et al , 2017bWilson et al 2017).…”

Multi‐variable approach pinpoints origin of oak wood with higher precision

“…Environmental information on growing conditions as stored in tree rings is widely used to predict growth responses of trees to climate change (Holz et al, 2018;Williams, Michaelsen, Leavitt, & Still, 2010), to model potential future species distribution (Gutiérrez, Snell, & Bugmann, 2016;van der Maaten et al, 2017), to quantify forest resistance to drought events (Gazol, Camarero, Anderegg, & Vicente-Serrano, 2017) and to reconstruct growth-limiting climate factors during the pre-instrumental period (Čufar, De Luis, Zupančič, & Eckstein, 2008;Rydval et al, 2017;Schofield, Barker, Gelman, Cook, & Briffa, 2016). Information on spatial variation of climatic signals in tree rings is also important for archaeological and historical studies, as it serves as a basis for dating and determining the geographical origin of historical timbers ("dendroprovenancing") (Speer, 2010).…”