Prewhitening of hydroclimatic time series? Implications for inferred change and variability across time scales
Prewhitening of hydroclimatic time series? Implications for inferred change and variability across time scales
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DOI：
10.1016/j.jhydrol.2017.11.053
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发表时间：
2018-02-01
影响因子：
6.4
通讯作者：
Vogel, Richard
中科院分区：
文献类型：
--
作者：
Razavi, Saman;Vogel, Richard
预白化是消除或减少短期随机持续性以检测确定性变化的过程，已广泛应用于一系列地球物理变量的时间序列分析。尽管围绕其效用的争议，预白化时间序列的方法仍然是一个重要的功能，包括各种分析：水文气候变量的趋势检测和重建的气候和/或水文通过代理记录，如树木年轮。以后者为重点，本文提出了一种广义的方法来探索水文气候时间序列的变异性的短期和长期持久性的随机结构的影响。通过这种方法，我们研究了预白化对跨时间尺度的时间序列的推断变异性的影响。我们记录了如何专注于预白化，剩余的时间序列可能会产生误导，因为它可以大大扭曲（或删除）跨时间尺度的变异性结构。通过实际数据的例子，我们展示了这种信息的损失，在预白化的时间序列的树木年轮（所谓的“剩余年表”）可能会导致低估极端条件下的气候和水文，特别是干旱，重建几个世纪之前的历史时期。(C)2017作者由爱思唯尔公司出版
Prewhitening, the process of eliminating or reducing short-term stochastic persistence to enable detection of deterministic change, has been extensively applied to time series analysis of a range of geophysical variables. Despite the controversy around its utility, methodologies for prewhitening time series continue to be a critical feature of a variety of analyses including: trend detection of hydroclimatic variables and reconstruction of climate and/or hydrology through proxy records such as tree rings. With a focus on the latter, this paper presents a generalized approach to exploring the impact of a wide range of stochastic structures of short- and long-term persistence on the variability of hydroclimatic time series. Through this approach, we examine the impact of prewhitening on the inferred variability of time series across time scales. We document how a focus on prewhitened, residual time series can be misleading, as it can drastically distort (or remove) the structure of variability across time scales. Through examples with actual data, we show how such loss of information in prewhitened time series of tree rings (so-called "residual chronologies") can lead to the underestimation of extreme conditions in climate and hydrology, particularly droughts, reconstructed for centuries preceding the historical period. (C) 2017 The Authors. Published by Elsevier B.V.