Variability of climate in Central Europe during the late Holocene from dendrochronological and documentary data (HOLOFLOOD)

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The research proposal will determine climate dynamics due to analysis of precipitation, temperature, circulation modes and anomalies during the Holocene. This will be done by combining two unique climate archives (documentary data back to 1.000 AD, dendrochronological data back 10.000 BP) both on true annual time scales. During the first stage of HOLOFLOOD data analysis, especially the parallelisation of tree-ring width and wood anatomical variables with documentary data succeeded encouragingly. Improvements had been achieved with the development and refinement of the transfer functions resulting in the reconstruction of flood, temperature and precipitation variability during historical time in Central Europe as well as for the 4,7k BP event. In the second stage of INTERDYNAMIK, HOLOFLOOD will intensively focus on the last 1200 years including the full Medieval Warm Period and the Little Ice Age. During this period a large amount of dendrochronological data from different regions as well as a broad variety of documentary data is available. Furthermore the two prominent climate fluctuations in the Holocene (8,2 k BP resp. 4,7 k BP) are investigated in a greater detail, laying the focus on human and natural driving forces of sudden climate changes. In the second stage of HOLOFLOOD further and more detailed transfer functions will be worked out involving non-linear and spectral analyses techniques as well as enhancing the existing approach by adding a wider variety of other climate proxies (e.g. warves and speleothems). On a more large scale approach the reconstruction of the leading modes of the European atmospheric circulation will be tested against the results of climatic reconstructions. In close collaboration with modellers the results derived from the research of the tree response to the influence of “Grosswetterlagen” will be improved by using data which provide daily information describing circulation modes on spatial and temporal scale, e.g. NCEP/NCAR Reanalysis data, GCMs etc. This will help to generate a better understanding of - and improved insight into future climate variability.