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A Bayesian spatiotemporal model for reconstructing climate from multiple pollen records. (English) Zbl 1454.62448

Summary: Holocene (the last 12,000 years) temperature variation, including the transition out of the last Ice Age to a warmer climate, is reconstructed at multiple locations in southern Finland, Sweden and Estonia based on pollen fossil data from lake sediment cores. A novel Bayesian statistical approach is proposed that allows the reconstructed temperature histories to interact through shared environmental response parameters and spatial dependence. The prior distribution for past temperatures is partially based on numerical climate simulation. The features in the reconstructions are consistent with the quantitative climate reconstructions based on more commonly used reconstruction techniques. The results suggest that the novel spatio-temporal approach can provide quantitative reconstructions that are smoother, less uncertain and generally more realistic than the site-specific individual reconstructions.

MSC:

62P12 Applications of statistics to environmental and related topics
62F15 Bayesian inference
62M30 Inference from spatial processes
86A32 Geostatistics

Software:

spBayes; BayesDA

References:

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