Abstract

The Late Miocene paleogeography of central Europe and its climatic history are well studied with a resolution of c. 106years. Small-scale climatic variations are yet unresolved. Observing past climatic change of short periods, however, would encourage the understanding of the modern climatic system. Therefore, past climate archives require a resolution on a decadal to millennial scale.To detect such a short-term evolution, a continuous 6-m-core of the Paleo-Lake Pannon was analyzed in 1-cm-sample distance to provide information as precise and regular as possible. Measurements of the natural gamma radiation and magnetic susceptibility combined with the total abundance of ostracod shells were used as proxies to estimate millennial- to centennial scale environmental changes during the mid-Tortonian warm period.Patterns emerged, but no indisputable age model can be provided for the core, due to the lack of paleomagnetic reversals and the lack of minerals suitable for absolute dating. Therefore, herein we propose another method to determine a hypothetic time frame for these deposits.Based on statistical processes, including Lomb–Scargle and REDFIT periodograms along with Wavelet spectra, several distinct cyclicities could be detected. Calculations considering established off-shore sedimentation rates of the Tortonian Vienna Basin revealed patterns resembling Holocene solar-cycle-records well. The comparison of filtered data of Miocene and Holocene records displays highly similar patterns and comparable modulations. A best-fit adjustment of sedimentation rate results in signals which fit to the lower and upper Gleissberg cycle, the de Vries cycle, the unnamed 500-year- and 1000-year-cycles, as well as the Hallstatt cycle. Each of these cycles has a distinct and unique expression in the investigated environmental proxies, reflecting a complex forcing-system. Hence, a single-proxy-analysis, as often performed on Holocene records, should be considered cautiously as it might fail to capture the full range of solar cycles.

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