This study presents a summer temperature reconstruction using Scots pine tree-ring chronologies for Scotland allowing the placement of current regional temperature changes in a longer-term context. ‘Living-tree’ chronologies were extended using ‘subfossil’ samples extracted from nearshore lake sediments resulting in a composite chronology >800 years in length. The North Cairngorms (NCAIRN) reconstruction was developed from a set of composite blue intensity high-pass and ring-width low-pass filtered chronologies with a range of detrending and disturbance correction procedures. Calibration against July–August mean temperature explains 56.4% of the instrumental data variance over 1866–2009 and is well verified. Spatial correlations reveal strong coherence with temperatures over the British Isles, parts of western Europe, southern Scandinavia and northern parts of the Iberian Peninsula. NCAIRN suggests that the recent summer-time warming in Scotland is likely not unique when compared to multi-decadal warm periods observed in the 1300s, 1500s, and 1730s, although trends before the mid-sixteenth century should be interpreted with some caution due to greater uncertainty. Prominent cold periods were identified from the sixteenth century until the early 1800s—agreeing with the so-called Little Ice Age observed in other tree-ring reconstructions from Europe—with the 1690s identified as the coldest decade in the record. The reconstruction shows a significant cooling response 1 year following volcanic eruptions although this result is sensitive to the datasets used to identify such events. In fact, the extreme cold (and warm) years observed in NCAIRN appear more related to internal forcing of the summer North Atlantic Oscillation.
CITATION STYLE
Rydval, M., Loader, N. J., Gunnarson, B. E., Druckenbrod, D. L., Linderholm, H. W., Moreton, S. G., … Wilson, R. (2017). Reconstructing 800 years of summer temperatures in Scotland from tree rings. Climate Dynamics, 49(9–10), 2951–2974. https://doi.org/10.1007/s00382-016-3478-8
Mendeley helps you to discover research relevant for your work.