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Holocene (the last 12,000 years) temperature variation, including thetransition out of the last Ice Age to a warmer climate, is reconstructed atmultiple locations in southern Finland, Sweden and Estonia based on pollenfossil data from lake sediment cores. A novel Bayesian statistical approach isproposed that allows the reconstructed temperature histories to interactthrough shared environmental response parameters and spatial dependence. Theprior distribution for past temperatures is partially based on numericalclimate simulation. The features in the reconstructions are consistent with thequantitative climate reconstructions based on more commonly used reconstructiontechniques. The results suggest that the novel spatio-temporal approach canprovide quantitative reconstructions that are smoother, less uncertain andgenerally more realistic than the site-specific individual reconstructions.

A Bayesian spatiotemporal model for reconstructing climate from multiple pollen records