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Author (up) 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 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 (up) 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  
  Area Expedition Conference  
  Funding Approved $loc['no']  
  Call Number COAPS @ mfield @ Serial 309  
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Author (up) 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 (up) 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 (up) 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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  Series Volume Series Issue Edition  
  ISSN 1793-5369 ISBN Medium  
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  Funding Approved $loc['no']  
  Call Number COAPS @ mfield @ Serial 667  
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Author (up) 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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  ISSN 1793-5369 ISBN Medium  
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  Funding Approved $loc['no']  
  Call Number COAPS @ mfield @ Serial 669  
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Author (up) Wu, Z.; Huang, N.E.; Wallace, J.M.; Smoliak, B.V.; Chen, X. url  doi
openurl 
  Title On the time-varying trend in global-mean surface temperature Type $loc['typeJournal Article']
  Year 2011 Publication Climate Dynamics Abbreviated Journal Clim Dyn  
  Volume 37 Issue 3-4 Pages 759-773  
  Keywords Global warming trend; Multidecadal variability; Ensemble empirical mode decomposition; IPCC AR4  
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  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0930-7575 ISBN Medium  
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  Funding Approved $loc['no']  
  Call Number COAPS @ mfield @ Serial 299  
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Author (up) Zhang, M.; Zhang, Y.; Shu, Q.; Zhao, C.; Wang, G.; Wu, Z.; Qiao, F. url  doi
openurl 
  Title Spatiotemporal evolution of the chlorophyll a trend in the North Atlantic Ocean Type $loc['typeJournal Article']
  Year 2018 Publication The Science of the Total Environment Abbreviated Journal Sci Total Environ  
  Volume 612 Issue Pages 1141-1148  
  Keywords Chlorophyll a; Dipole pattern; Multidimensional ensemble empirical mode decomposition; Propagation; Spatiotemporal evolution; The variable trend  
  Abstract Analyses of the chlorophyll a concentration (chla) from satellite ocean color products have suggested the decadal-scale variability of chla linked to the climate change. The decadal-scale variability in chla is both spatially and temporally non-uniform. We need to understand the spatiotemporal evolution of chla in decadal or multi-decadal timescales to better evaluate its linkage to climate variability. Here, the spatiotemporal evolution of the chla trend in the North Atlantic Ocean for the period 1997-2016 is analyzed using the multidimensional ensemble empirical mode decomposition method. We find that this variable trend signal of chla shows a dipole pattern between the subpolar gyre and along the Gulf Stream path, and propagation along the opposite direction of the North Atlantic Current. This propagation signal has an overlapping variability of approximately twenty years. Our findings suggest that the spatiotemporal evolution of chla during the two most recent decades is part of the multidecadal variations and possibly regulated by the changes of Atlantic Meridional Overturning Circulation, whereas the mechanisms of such evolution patterns still need to be explored.  
  Address First Institute of Oceanography, State Oceanic Administration, Qingdao, China; Laboratory for Regional Oceanography and Numerical Modeling, Qingdao National Laboratory for Marine Science and Technology, Qingdao, China; Key Laboratory of Data Analysis and Applications, State Oceanic Administration, Qingdao, China. Electronic address: qiaofl@fio.org.cn  
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  ISSN 0048-9697 ISBN Medium  
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  Funding PMID:28892858 Approved $loc['no']  
  Call Number COAPS @ mfield @ Serial 363  
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