Ensemble empirical mode decomposition for tree-ring climate reconstructions
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A novel data adaptive method named ensemble empirical mode decomposition (EEMD) was used to reconstruct past temperature and precipitation variability in two 2,328- and 1,837-year tree-ring chronologies from the Dulan region, northeastern Qinghai–Tibetan Plateau. Our results show that EEMD can be used to extract low-frequency signals from the Dulan tree-ring data. The extracted low-frequency temperature trends in the two chronologies correlate significantly with Northern Hemisphere temperatures over the past two millennia. In addition, the newly reconstructed precipitation data have a higher standard deviation than that of data reconstructed with the conventional ordinary least squares and variance matching methods and yield the best amplitude match to the instrumental data. This study shows that EEMD is a powerful tool for extracting the full spectrum of climate information in tree-ring chronologies.
The authors thank two anonymous reviewers for their thoughtful and constructive comments. This paper also benefited from revisions by the editor Hartmut Graßl. The study was jointly funded by CAS Strategic Priority Research Program Grant (No. XDA05080801), Chinese Academy of Sciences (CAS) 100 Talents Project (29082762), and NSFC (Grant Nos. 41071130 and 40871091). Feng Shi was supported by West Light Program for Talent Cultivation of Chinese Academy of Sciences. Bao Yang gratefully acknowledges the support of K.C. Wong Education Foundation. Hong Kong. LvG was supported by Swiss NSF (PBBEP2-126056).
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