Abstract

Large-scale climate history of the past millennium reconstructed solely from tree-ring data is prone to underestimate the amplitude of low-frequency variability. In this paper, we aimed at solving this problem by utilizing a novel method termed “MDVM”, which was a combination of the ensemble empirical mode decomposition (EEMD) and variance matching techniques. We compiled a set of 211 tree-ring records from the extratropical Northern Hemisphere (30–90°N) in an effort to develop a new reconstruction of the annual mean temperature by the MDVM method. Among these dataset, a number of 126 records were screened out to reconstruct temperature variability longer than decadal scale for the period 850–2000 AD. The MDVM reconstruction depicted significant low-frequency variability in the past millennium with evident Medieval Warm Period (MWP) over the interval 950–1150 AD and pronounced Little Ice Age (LIA) cumulating in 1450–1850 AD. In the context of 1150-year reconstruction, the accelerating warming in 20th century was likely unprecedented, and the coldest decades appeared in the 1640s, 1600s and 1580s, whereas the warmest decades occurred in the 1990s, 1940s and 1930s. Additionally, the MDVM reconstruction covaried broadly with changes in natural radiative forcing, and especially showed distinct footprints of multiple volcanic eruptions in the last millennium. Comparisons of our results with previous reconstructions and model simulations showed the efficiency of the MDVM method on capturing low-frequency variability, particularly much colder signals of the LIA relative to the reference period. Our results demonstrated that the MDVM method has advantages in studying large-scale and low-frequency climate signals using pure tree-ring data.

Highlights

  • Knowledge of climate change in the past is essential for understanding the response of the climate system to natural and anthropogenic forcings, and useful for evaluating the observedPLOS ONE | DOI:10.1371/journal.pone.0146776 January 11, 2016Northern Hemisphere Temperature Reconstruction Based on a Novel Method study design, data collection and analysis, decision to publish, or preparation of the manuscript

  • Further details in the process of performing MDVM method including the statistical results of threshold values derived from Monte Carlo simulation, as well as the scaling and calibrating were provided in S1 and S2 Tables, S1 Fig

  • Based on the high values of reduction of error (RE) and coefficient of efficiency (CE) calculated from proxy experiment (PPE) test, we could basically infer a good ability of MDVM method to preserve the low-frequency signals

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Summary

Objectives

The objectives of this study were (1) to introduce the MDVM method, (2) to evaluate its performance by establishing a reconstruction of the extratropical

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