Abstract. Spatiotemporal paleoclimate reconstructions that seek to estimate climate conditions over the last several millennia are derived from multiple climate proxy records (e.g. tree rings, ice cores, corals, and cave formations) that are heterogeneously distributed across land and marine environments. Assessing the skill of the methods used for these reconstructions is critical as a means of understanding the spatiotemporal uncertainties in the derived reconstruction products. Traditional statistical measures of skill have been applied in past applications, but they often lack formal null hypotheses that incorporate the spatiotemporal characteristics of the fields and allow for formal significance testing. More recent attempts have developed assessment metrics to evaluate the difference of the characteristics between two spatiotemporal fields. We apply these assessment metrics herein to results from synthetic reconstruction experiments based on multiple climate model simulations to assess the skill of four reconstruction methods. We further interpret the comparisons using analysis of Empirical Orthogonal Functions that represent the noise-filtered climate field. The features of climate models and reconstruction methods identified in this paper demonstrate more detailed assessments of reconstruction methods and point to important areas of testing and improving real-world reconstruction methods.

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关于气候场重建方法为何在时空上表现出方式的伪代理评估

摘要。试图估计过去几千年的气候条件的时空古气候重建来自多个气候代用记录（例如，年轮，冰芯，珊瑚和洞穴形成），这些记录在陆地和海洋环境中分布不均。评估用于这些重建的方法的技能至关重要，这是理解派生重建产品中时空不确定性的一种手段。传统的技能统计方法已应用于过去的应用程序中，但它们通常缺少正式的零假设，这些假设结合了该领域的时空特征并允许进行正式的重要性检验。最近的尝试已经开发出评估指标，以评估两个时空场之间的特征差异。我们将这些评估指标应用于基于多种气候模型模拟的综合重建实验的结果，以评估四种重建方法的技能。我们使用经验正交函数的分析来进一步解释这些比较，这些经验函数代表了经过噪声过滤的气候场。本文确定的气候模型和重建方法的特征展示了对重建方法的更详细评估，并指出了测试和改进实际重建方法的重要领域。我们使用经验正交函数的分析来进一步解释这些比较，这些经验函数代表了经过噪声过滤的气候场。本文确定的气候模型和重建方法的特征展示了对重建方法的更详细评估，并指出了测试和改进实际重建方法的重要领域。我们使用经验正交函数的分析来进一步解释这些比较，这些经验函数代表了经过噪声过滤的气候场。本文确定的气候模型和重建方法的特征展示了对重建方法的更详细评估，并指出了测试和改进实际重建方法的重要领域。