We propose a Bayesian hierarchical model which produces probabilistic reconstructions of hydroclimatic variability in Queensland Australia. The model provides a standardised 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 modelling 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. We present case studies for Brisbane and Fitzroy catchments focusing on two hydroclimate indices, the Rainfall Index (RFI) and the Standardised Precipitation-Evapotranspiration Index (SPEI). The probabilistic nature of the reconstructions allows us to estimate the probability that a hydroclimate index in any reconstruction year was lower (higher) than the minimum (maximum) value observed over the instrumental period. In Brisbane, the RFI is unlikely (probabilities < 20%) to have exhibited extremes beyond the minimum/maximum values observed between 1889 and 2017. However, in Fitzroy there are several years during the reconstruction period where the RFI is likely (> 50% probability) to have exhibited behaviour beyond the minimum/maximum of what has been observed. For SPEI, the probability of observing such extremes since the end of the instrumental period in 1889 doesn't exceed 50% in any reconstruction year in Brisbane or Fitzroy.
翻译:我们建议采用贝叶斯等级模型,在昆士兰澳大利亚州对水文气候变异性进行概率重建。该模型利用来自诸如石棺、冰芯和树环等自然档案的多种古地气候替代记录,为水文气候重建提供了标准化的方法。该方法结合了时间序列模型和反向预测,以量化某一水文气候指数与相关代理人在一个工具时期的关系,并随后通过时间重建水文气候。我们介绍了布里斯班和菲茨罗伊集水区的案例研究,重点是两个水文气候指数,即降雨指数和标准降水-蒸发指数。这些重建的概率性使我们能够估计任何重建年份的水文气候指数低于(高)在某一工具时期观察到的最低(最大)值,随后又将水温气候气候恢复到一段时间。在布里斯班内,RFI不可能(概率 < 20 % ) 展示超出1889年至201717年所观察到的最低/最大值的极端值。然而,50年的重建概率是SFICFI(在1889至201717年观察的任何最起码的概率期中) 。在FI 的重建中,这种概率是,在1889年或最接近50年之后的重建期里欧。