We propose a Bayesian model which produces probabilistic reconstructions of hydroclimatic variability in Queensland Australia. The approach uses instrumental records of hydroclimate indices such as rain and evaporation, as well as palaeoclimate proxy records derived from natural archives such as sediment cores, speleothems, ice cores and tree rings. The method provides a standardised approach to using multiple palaeoclimate proxy records for hydroclimate reconstruction. Our approach combines time series modelling with an inverse prediction approach to quantify the relationships between the hydroclimate and proxies over the instrumental period and subsequently reconstruct the hydroclimate back through time. Further analysis of the model output allows us to estimate the probability that a hydroclimate index in any reconstruction year was lower (higher) than the minimum (maximum) hydroclimate value observed over the instrumental period. We present model-based reconstructions of the Rainfall Index (RFI) and Standardised Precipitation Evaporation Index (SPEI) for two case study catchment areas, namely Brisbane and Fitzroy. In Brisbane, we found that the RFI is unlikely (probability between 0 and 20%) to have exhibited extremes beyond the minimum/maximum of what has been 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 the Brisbane or Fitzroy catchments.
翻译:我们建议采用贝叶斯模型,在昆士兰澳大利亚州进行水文气候变异的概率重建。该方法使用诸如雨和蒸发等水文气候指数的有用记录,以及来自自然档案的古气候代用记录,如沉积岩芯、石质歌、冰芯和树环。该方法提供了一种标准化的方法,用多种古色气候代用记录进行水文气候重建。我们的方法将时间序列模型与反向预测方法结合起来,以量化在工具时期的水文气候和代理人之间的关系,并随后在时间上重建水文气候。对模型产出的进一步分析使我们能够估计,任何重建年份的水文气候指数都低于(高于)在工具时期所观察到的最低(最高)水温气候值。我们为两个案例研究地区(即布里斯班和菲茨罗伊)提供了基于模型的重建模型(SPEI)模型,在两个案例研究地区(即布里斯班尼和菲茨罗马),我们发现,在50年之后,RFI值的概率指数在50年之后的概率是最低(最低值),在20—18年的重建期之间是最低值。