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Author Chen, X.; Zhang, Y.; Zhang, M.; Feng, Y.; Wu, Z.; Qiao, F.; Huang, N.E. url  doi
openurl 
  Title Intercomparison between observed and simulated variability in global ocean heat content using empirical mode decomposition, part I: modulated annual cycle Type $loc['typeJournal Article']
  Year 2013 Publication Climate Dynamics Abbreviated Journal Clim Dyn  
  Volume 41 Issue 11-12 Pages 2797-2815  
  Keywords Ocean heat content; Modulated annual cycle; Empirical mode decomposition; Instantaneous frequency; Instantaneous amplitude; CMIP3  
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  Series Volume Series Issue Edition  
  ISSN 0930-7575 ISBN Medium  
  Area Expedition Conference  
  Funding Approved $loc['no']  
  Call Number COAPS @ mfield @ Serial 209  
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Author Deng, J.; Wu, Z.; Zhang, M.; Huang, N.E.; Wang, S.; Qiao, F. url  doi
openurl 
  Title Using Holo-Hilbert spectral analysis to quantify the modulation of Dansgaard-Oeschger events by obliquity Type $loc['typeJournal Article']
  Year 2018 Publication Quaternary Science Reviews Abbreviated Journal Quaternary Science Reviews  
  Volume 192 Issue Pages 282-299  
  Keywords Pleistocene; Paleoclimatology; Greenland; Antarctica; Data treatment; Data analysis; Dansgaard-oeschger (DO) events; Obliquity forcing; Phase preference; Holo-hilbert spectral analysis; Amplitude modulation; EMPIRICAL MODE DECOMPOSITION; GREENLAND ICE-CORE; NONSTATIONARY TIME-SERIES; ABRUPT CLIMATE-CHANGE; LAST GLACIAL PERIOD; NORTH-ATLANTIC; MILLENNIAL-SCALE; RECORDS; VARIABILITY; CYCLE  
  Abstract Astronomical forcing (obliquity and precession) has been thought to modulate Dansgaard-Oeschger (DO) events, yet the detailed quantification of such modulations has not been examined. In this study, we apply the novel Holo-Hilbert Spectral Analysis (HHSA) to five polar ice core records, quantifying astronomical forcing's time-varying amplitude modulation of DO events and identifying the preferred obliquity phases for large amplitude modulations. The unique advantages of HHSA over the widely used windowed Fourier spectral analysis for quantifying astronomical forcing's nonlinear modulations of DO events is first demonstrated with a synthetic data that closely resembles DO events recorded in Greenland ice cores (NGRIP, GRIP, and GISP2 cores on GICC05 modelext timescale). The analysis of paleoclimatic proxies show that statistically significantly more frequent DO events, with larger amplitude modulation in the Greenland region, tend to occur in the decreasing phase of obliquity, especially from its mean value to its minimum value. In the eastern Antarctic, although statistically significantly more DO events tend to occur in the decreasing obliquity phase in general, the preferred phase of obliquity for large amplitude modulation on DO events is a segment of the increasing phase near the maximum obliquity, implying that the physical mechanisms of DO events may be different for the two polar regions. Additionally, by using cross-spectrum and magnitude-squared analyses, Greenland DO mode at a timescale of about 1400 years leads the Antarctic DO mode at the same timescale by about 1000 years. (C) 2018 Elsevier Ltd. All rights reserved.  
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  Series Volume Series Issue Edition  
  ISSN 0277-3791 ISBN Medium  
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  Funding Approved $loc['no']  
  Call Number COAPS @ user @ Serial 971  
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Author Fu, C.B.; Qian, C.; Wu, Z.H. url  doi
openurl 
  Title Projection of global mean surface air temperature changes in next 40 years: Uncertainties of climate models and an alternative approach Type $loc['typeJournal Article']
  Year 2011 Publication Science China Earth Sciences Abbreviated Journal Sci. China Earth Sci.  
  Volume 54 Issue 9 Pages 1400-1406  
  Keywords decadal prediction; global warming; multi-decadal climate variability; the Ensemble Empirical Mode Decomposition; CMIP3 multi-model  
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  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1674-7313 ISBN Medium  
  Area Expedition Conference  
  Funding Approved $loc['no']  
  Call Number COAPS @ mfield @ Serial 293  
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Author Hou, T.Y.; Yan, M.P.; Wu, Z. url  doi
openurl 
  Title A Variant Of The Emd Method For Multi-Scale Data Type $loc['typeJournal Article']
  Year 2009 Publication Advances in Adaptive Data Analysis Abbreviated Journal Adv. Adapt. Data Anal.  
  Volume 01 Issue 04 Pages 483-516  
  Keywords Empirical Mode Decomposition (EMD); adaptive data analysis; sparse representation  
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  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1793-5369 ISBN Medium  
  Area Expedition Conference  
  Funding Approved $loc['no']  
  Call Number COAPS @ mfield @ Serial 670  
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Author Huang, N.E.; Wu, Z.; Long, S.R.; Arnold, K.C.; Chen, X.; Blank, K. url  doi
openurl 
  Title On Instantaneous Frequency Type $loc['typeJournal Article']
  Year 2009 Publication Advances in Adaptive Data Analysis Abbreviated Journal Adv. Adapt. Data Anal.  
  Volume 01 Issue 02 Pages 177-229  
  Keywords Instantaneous frequency; Hilbert transform; quadrature; empirical mode decomposition; normalized intrinsic mode function; empirical AM/FM decomposition  
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  ISSN 1793-5369 ISBN Medium  
  Area Expedition Conference  
  Funding Approved $loc['no']  
  Call Number COAPS @ mfield @ Serial 668  
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Author Qian, C.; Fu, C.; Wu, Z.; Yan, Z. url  doi
openurl 
  Title The role of changes in the annual cycle in earlier onset of climatic spring in northern China Type $loc['typeJournal Article']
  Year 2011 Publication Advances in Atmospheric Sciences Abbreviated Journal Adv. Atmos. Sci.  
  Volume 28 Issue 2 Pages 284-296  
  Keywords spring onset; Ensemble Empirical Mode Decomposition; modulated annual cycle; Asian winter monsoon; global warming  
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  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0256-1530 ISBN Medium  
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  Funding Approved $loc['no']  
  Call Number COAPS @ mfield @ Serial 309  
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Author Qian, C.; Wu, Z.; Fu, C.; Zhou, T. url  doi
openurl 
  Title On multi-timescale variability of temperature in China in modulated annual cycle reference frame Type $loc['typeJournal Article']
  Year 2010 Publication Advances in Atmospheric Sciences Abbreviated Journal Adv. Atmos. Sci.  
  Volume 27 Issue 5 Pages 1169-1182  
  Keywords modulated annual cycle; the Ensemble Empirical Mode Decomposition; climate anomaly; climate normal; variability of surface air temperature in China  
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  Series Volume Series Issue Edition  
  ISSN 0256-1530 ISBN Medium  
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  Funding Approved $loc['no']  
  Call Number COAPS @ mfield @ Serial 355  
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Author Wu, Z.; Huang, N.E. url  doi
openurl 
  Title Ensemble Empirical Mode Decomposition: A Noise-Assisted Data Analysis Method Type $loc['typeJournal Article']
  Year 2009 Publication Advances in Adaptive Data Analysis Abbreviated Journal Adv. Adapt. Data Anal.  
  Volume 01 Issue 01 Pages 1-41  
  Keywords Empirical Mode Decomposition (EMD); ensemble empirical mode decompositions; noise-assisted data analysis (NADA); Intrinsic Mode Function (IMF); shifting stoppage criteria; end effect reduction Read More: http://www.worldscientific.com/doi/abs/10.1142/S1793536909000047  
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  ISSN 1793-5369 ISBN Medium  
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  Funding Approved $loc['no']  
  Call Number COAPS @ mfield @ Serial 667  
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Author Wu, Z.; Feng, J.; Qiao, F.; Tan, Z.-M. url  doi
openurl 
  Title Fast multidimensional ensemble empirical mode decomposition for the analysis of big spatio-temporal datasets Type $loc['typeJournal Article']
  Year 2016 Publication Philosophical Transactions. Series A, Mathematical, Physical, and Engineering Sciences Abbreviated Journal Philos Trans A Math Phys Eng Sci  
  Volume 374 Issue 2065 Pages 20150197  
  Keywords adaptive and local data analysis; data compression; empirical orthogonal function; fast algorithm; multidimensional ensemble empirical mode decomposition; principal component analysis  
  Abstract In this big data era, it is more urgent than ever to solve two major issues: (i) fast data transmission methods that can facilitate access to data from non-local sources and (ii) fast and efficient data analysis methods that can reveal the key information from the available data for particular purposes. Although approaches in different fields to address these two questions may differ significantly, the common part must involve data compression techniques and a fast algorithm. This paper introduces the recently developed adaptive and spatio-temporally local analysis method, namely the fast multidimensional ensemble empirical mode decomposition (MEEMD), for the analysis of a large spatio-temporal dataset. The original MEEMD uses ensemble empirical mode decomposition to decompose time series at each spatial grid and then pieces together the temporal-spatial evolution of climate variability and change on naturally separated timescales, which is computationally expensive. By taking advantage of the high efficiency of the expression using principal component analysis/empirical orthogonal function analysis for spatio-temporally coherent data, we design a lossy compression method for climate data to facilitate its non-local transmission. We also explain the basic principles behind the fast MEEMD through decomposing principal components instead of original grid-wise time series to speed up computation of MEEMD. Using a typical climate dataset as an example, we demonstrate that our newly designed methods can (i) compress data with a compression rate of one to two orders; and (ii) speed-up the MEEMD algorithm by one to two orders.  
  Address School of Atmospheric Sciences, Nanjing University, Nanjing, Jiangsu Province, People's Republic of China  
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  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1364-503X ISBN Medium  
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  Funding PMID:26953173; PMCID:PMC4792406 Approved $loc['no']  
  Call Number COAPS @ mfield @ Serial 57  
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Author Wu, Z.; Huang, N.E.; Chen, X. url  doi
openurl 
  Title The Multi-Dimensional Ensemble Empirical Mode Decomposition Method Type $loc['typeJournal Article']
  Year 2009 Publication Advances in Adaptive Data Analysis Abbreviated Journal Adv. Adapt. Data Anal.  
  Volume 01 Issue 03 Pages 339-372  
  Keywords Empirical mode decomposition (EMD); ensemble empirical mode decomposition (EEMD); minimal scale principle; pseudo multi-dimensional ensemble empirical mode decomposition; multi-dimensional ensemble empirical mode decomposition  
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  Series Volume Series Issue Edition  
  ISSN 1793-5369 ISBN Medium  
  Area Expedition Conference  
  Funding Approved $loc['no']  
  Call Number COAPS @ mfield @ Serial 669  
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