A Bayesian time series model for reconstructing hydroclimate from multiple proxies


We propose a Bayesian model which produces probabilistic reconstructions of hydroclimatic variability in Queensland Australia. The model provides a standardized approach to hydroclimate reconstruction using multiple palaeoclimate proxy records derived from natural archives such as speleothems, ice cores and tree rings. The method combines time‐series modeling with inverse prediction to quantify the relationships between a given hydroclimate index and relevant proxies over an instrumental period and subsequently reconstruct the hydroclimate back through time.