title: The Extratropical Northern Hemisphere Temperature Reconstruction during the Last Millennium Based on a Novel Method.
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.
authors.affiliation: Center for Earth System Science, Tsinghua University, Beijing, China.|Beijing Municipal Climate Center, Beijing, China.
authors.forename: Pei
authors.initials: P
authors.lastname: Xing
authors.affiliation: Center for Earth System Science, Tsinghua University, Beijing, China.|Joint Center for Global Change Studies (JCGCS), Beijing, China.
authors.forename: Xin
authors.initials: X
authors.lastname: Chen
authors.affiliation: Center for Earth System Science, Tsinghua University, Beijing, China.|Joint Center for Global Change Studies (JCGCS), Beijing, China.
authors.forename: Yong
authors.initials: Y
authors.lastname: Luo
authors.affiliation: National Climate Center, China Meteorological Administration, Beijing, China.
authors.forename: Suping
authors.initials: S
authors.lastname: Nie
authors.affiliation: Center for Earth System Science, Tsinghua University, Beijing, China.|Joint Center for Global Change Studies (JCGCS), Beijing, China.
authors.forename: Zongci
authors.initials: Z
authors.lastname: Zhao
authors.affiliation: Center for Earth System Science, Tsinghua University, Beijing, China.|Joint Center for Global Change Studies (JCGCS), Beijing, China.
authors.forename: Jianbin
authors.initials: J
authors.lastname: Huang
authors.affiliation: Department of Atmospheric Sciences, School of Physics, Peking University, Beijing, China.
authors.forename: Shaowu
authors.initials: S
authors.lastname: Wang
mesh_terms: D002138:Calibration; D002980:Climate; D003198:Computer Simulation; D003625:Data Collection; D057232:Global Warming; D015233:Models, Statistical; D009010:Monte Carlo Method; D015203:Reproducibility of Results; D012621:Seasons; D012984:Software; D013696:Temperature; D013997:Time Factors; D014197:Trees / Q000502:physiology*; D018707:Volcanic Eruptions