Estimating the timescale-dependent uncertainty of paleoclimate records – a spectral approach. Part I: Theoretical concept

T. Kunz, A. Dolman, T. Laepple
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引用次数: 1

Abstract

Abstract. Proxy records represent an invaluable source of information for reconstructing past climatic variations, but they are associated with considerable uncertainties. For a systematic quantification of these reconstruction errors, however, knowledge is required not only of their individual sources but also of their auto-correlation structure, as this determines the timescale dependence of their magnitude, an issue that is often ignored until now. Here a spectral approach to uncertainty analysis is provided for paleoclimate reconstructions obtained from single sediment proxy records. The formulation in the spectral domain, rather than the time domain, allows for an explicit demonstration as well as quantification of the timescale dependence that is inherent in any proxy-based reconstruction uncertainty. This study is published in two parts. In this first part, the theoretical concept is presented and analytic expressions are derived for the power spectral density of the reconstruction error of sediment proxy records. The underlying model takes into account the spectral structure of the climate signal, seasonal and orbital variations, bioturbation, sampling of a finite number of signal carriers, uncorrelated measurement noise, and it includes the effects of spectral aliasing and leakage. The uncertainty estimation method, based upon this model, is illustrated by simple examples. In the second part of this study, published separately, the method is implemented in an application-oriented context, and more detailed examples are presented.
估算古气候记录随时间变化的不确定性——光谱方法。第一部分:理论概念
摘要替代记录是重建过去气候变化的宝贵信息来源,但它们具有相当大的不确定性。然而,为了系统地量化这些重建误差,不仅需要了解它们的单个来源,还需要了解它们的自相关结构,因为这决定了它们的大小的时间尺度依赖性,这是一个迄今为止经常被忽视的问题。本文提出了一种不确定性分析的光谱方法,用于从单一沉积物代用记录中获得的古气候重建。谱域的公式,而不是时域的公式,允许一个明确的演示,以及在任何基于代理的重建不确定性中固有的时间尺度依赖的量化。本研究分为两部分发表。第一部分提出了泥沙代用记录重建误差的功率谱密度的理论概念,并推导了其解析表达式。基础模型考虑了气候信号的频谱结构、季节和轨道变化、生物扰动、有限数量的信号载波采样、不相关的测量噪声,并包括频谱混叠和泄漏的影响。通过简单的实例说明了基于该模型的不确定性估计方法。在本研究的第二部分(单独发表)中,该方法在面向应用的上下文中实现,并给出了更详细的示例。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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