Closing a gap in Northern Hemisphere paleoclimatology: Temperature history of the Caucasus reconstructed from tree-ring density parameters

• Applicant: Professorin Dr. Lea Schneider
• Subject Area: Physical Geography
• Term: since 2024
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 543966483

The global average of surface air temperature is a useful metric to describe and understand the response of the climate system to external forcing and the impact of feedback mechanisms at different time-scales. Extending this temperature record beyond the relatively short period of instrumental observations requires natural proxy archives. Tree-rings are the most abundant and wide-spread high-resolution archive for century or millennial long climate reconstructions. In multiple studies, large networks of local climate-sensitive tree-ring chronologies have been compiled to reconstruct temperature variability over the extratropical Northern hemisphere. However, in the tree-ring network remains a noticeable gap in the Caucasus region. To overcome this gap, we propose a three-step approach. First, we aim at establishing a regional network of temperature sensitive tree-ring chronologies. In theory, temperature limits tree growth in high elevation tree line ecotones, but due to a long history of human activity and land use the natural tree line is shifted downwards in the Caucasus. Additionally, tree growth is often disturbed by anthropogenic impacts resulting in weak temperature signals in tree-ring width data from the tree line. In our preliminary work we could show that measuring Blue Intensity (BI), a surrogate for wood density, enhances the temperature signal significantly in the study region. Since BI is known to be a stronger temperature proxy, a network of BI chronologies is expected to show generally higher temperature correlations which will allow us to distinguish between species and site related growth patterns (“noise”) and regional climate variability ("signal"). In a second step, samples from those sites with the strongest temperature signals undergo further analysis with the final aim of producing a regional temperature reconstruction. The temperature signal in BI data is often restricted to short-term variability. Recovering longer-term temperature trends requires X-ray wood density measurements. In the past this has been a very labor-intense analysis with multiple processing steps. A new technically advanced system for microdensitometric measurements (X-ray CT) in wood is ready to accelerate the workflow significantly by digitizing and partly automating this routine. With density data from X-ray CT measurements we will produce the first temperature reconstruction based on this new technology. Finally, we will integrate our new temperature reconstruction and other recently published records into large-scale data products to improve the spatial representation of the Caucasus region and beyond. We will evaluate an updated European reconstruction by critically analyzing uncertainty in different frequency domains. More robust reconstructed temperatures will allow us to address the agreement with early instrumental data and simulations from earth system models eventually increasing our understanding of past climate variability.

• DFG Programme: Research Grants