Description: The Arctic hydrological cycle throughout the Holocene is analyzed based on the results of transient simulations with the coupled atmosphere-ocean circulation model ECHO-G. The results suggest a ~ 2% increase of mid-Holocene to preindustrial Arctic river discharges for the Eurasian continent. However, rivers of the North America Arctic realm show a moderate runoff decline of approximately 4 to 5% for the same period. The total river discharge into the Arctic Ocean has remained at an approximately constant preindustrial level since the mid-Holocene. The positive discharge trend within Eurasia is caused by a more rapid decrease in local net evaporation compared to a smaller decline in advected moisture and hence precipitation. This effect is neither recognized within the North American Arctic domain nor in the far eastern part of the Eurasian Arctic realm. A detailed comparison of these model findings with a variety of proxy studies is conducted. The collected proxy records show trends of continental surface temperatures and precipitation rates that are consistent with the simulations. A continuation of the transient Holocene runs for the 19th and 20th century with increased greenhouse gasses indicates an increase of the total river influx into the Arctic Ocean of up to 7.6%. The Eurasian river discharges increase by 7.5%, the North American discharges by up to 8.4%. The most rapid increases have been detected since the beginning of the 20th century. These results are corroborated by the observed rising of Arctic river discharges during the last century which is attributed to anthropogenic warming. The acceleration of the Arctic hydrological cycle in the 20th century is without precedence in the Holocene.

Description: We introduce a technique of time series analysis, potential forecasting, which is based on dynamical propagation of the probability density of time series. We employ polynomial coefficients of the orthogonal approximation of the empirical probability distribution and extrapolate them in order to forecast the future probability distribution of data. The method is tested on artificial data, used for hindcasting observed climate data, and then applied to forecast Arctic sea-ice time series. The proposed methodology completes a framework for ‘potential analysis’ of tipping points which altogether serves anticipating, detecting and forecasting nonlinear changes including bifurcations using several independent techniques of time series analysis. Although being applied to climatological series in the present paper, the method is very general and can be used to forecast dynamics in time series of any origin.

Description: A critical problem in radiocarbon dating is the spatial and temporal variability of marine 14C reservoir ages. This is particularly true for the time scale beyond the tree-ring calibration range. Here, we propose a method to assess the evolution of marine reservoir ages during the last deglaciation by numerical modeling. We apply a self-consistent iteration scheme in which existing radiocarbon chronologies can be readjusted by transient, three-dimensional simulations of marine and atmospheric Δ14C. To estimate the uncertainties regarding the ocean ventilation during the last deglaciation, we consider various ocean overturning scenarios which are based on different climatic background states. An example readjusting 14C data from the Caribbean points to marine reservoir ages varying between 200 and 900 a during the last deglaciation. Correspondingly, the readjustment leads to enhanced variability of atmospheric Δ14C by ± 30‰, and increases the mysterious drop of atmospheric Δ14C between 17.5 and 14.5 cal ka BP by about 20‰.