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Author Qian, C.; Fu, C.; Wu, Z.; Yan, Z.
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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Language Summary Language Original Title
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 Qian, C.; Wu, Z.; Fu, C.; Wang, D.
Title On Changing El Nino: A View from Time-Varying Annual Cycle, Interannual Variability, and Mean State Type $loc['typeJournal Article']
Year 2011 Publication Journal of Climate Abbreviated Journal J. Climate
Volume 24 Issue 24 Pages 6486-6500
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Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0894-8755 ISBN Medium
Area Expedition Conference
Funding Approved $loc['no']
Call Number COAPS @ mfield @ Serial 283
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Author Qian, C.; Wu, Z.; Fu, C.; Zhou, T.
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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Publisher Place of Publication Editor
Language Summary Language Original Title
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 355
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Author Qian, C.; Yan, Z.; Wu, Z.; Fu, C.; Tu, K.
Title Trends in temperature extremes in association with weather-intraseasonal fluctuations in eastern China Type $loc['typeJournal Article']
Year 2011 Publication Advances in Atmospheric Sciences Abbreviated Journal Adv. Atmos. Sci.
Volume 28 Issue 2 Pages 297-309
Keywords climate extremes; EEMD; weather-intraseasonal fluctuations; modulated annual cycle; global warming
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Publisher Place of Publication Editor
Language Summary Language Original Title
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 310
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Author Sun, J.; Wu, Z.
Title Isolating spatiotemporally local mixed Rossby-gravity waves using multi-dimensional ensemble empirical mode decomposition Type $loc['typeJournal Article']
Year 2019 Publication Climate Dynamics Abbreviated Journal Clim Dyn
Volume Issue 3-4 Pages 1383-1405
Keywords
Abstract Tropical waves have relatively large amplitudes in and near convective systems, attenuating as they propagate away from the area where they are generated due to the dissipative nature of the atmosphere. Traditionally, nonlocal analysis methods, such as those based on the Fourier transform, are applied to identify tropical waves. However, these methods have the potential to lead to the misidentification of local wavenumbers and spatial locations of local wave activities. To address this problem, we propose a new method for analyzing tropical waves, with particular focus placed on equatorial mixed Rossby-gravity (MRG) waves. The new tropical wave analysis method is based on the multi-dimensional ensemble empirical mode decomposition and a novel spectral representation based on spatiotemporally local wavenumber, frequency, and amplitude of waves. We first apply this new method to synthetic data to demonstrate the advantages of the method in revealing characteristics of MRG waves. We further apply the method to reanalysis data (1) to identify and isolate the spatiotemporally heterogeneous MRG waves event by event, and (2) to quantify the spatial inhomogeneity of these waves in a wavenumber-frequency-energy diagram. In this way, we reveal the climatology of spatiotemporal inhomogeneity of MRG waves and summarize it in wavenumber-frequency domain: The Indian Ocean is dominated by MRG waves in the period range of 812 days; the western Pacific Ocean consists of almost equal energy distribution of MRG waves in the period ranges of 36 and 812 days, respectively; and the eastern tropical Pacific Ocean and the tropical Atlantic Ocean are dominated by MRG waves in the period range of 36 days. The zonal wavenumbers mostly fall within the band of 415, with Indian Ocean has larger portion of higher wavenumber (smaller wavelength components) MRG waves.
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Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0930-7575 ISBN Medium
Area Expedition Conference
Funding Approved $loc['no']
Call Number COAPS @ user @ Serial 1093
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Author Wdowinski, S.; Bray, R.; Kirtman, B.P.; Wu, Z.
Title Increasing flooding hazard in coastal communities due to rising sea level: Case study of Miami Beach, Florida Type $loc['typeJournal Article']
Year 2016 Publication Ocean & Coastal Management Abbreviated Journal Ocean & Coastal Management
Volume 126 Issue Pages 1-8
Keywords Sea level rise; Flooding hazard; Tide gauge record; EEMD; Southeast Florida
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Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0964-5691 ISBN Medium
Area Expedition Conference
Funding Approved $loc['no']
Call Number COAPS @ mfield @ Serial 56
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Author Wu, Z.; Huang, N.E.
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
Abstract
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Publisher Place of Publication Editor
Language Summary Language Original Title
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 667
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Author Wu, Z.; Chassignet, E.P.; Ji, F.; Huang, J.
Title Reply to 'Spatiotemporal patterns of warming' Type $loc['typeJournal Article']
Year 2014 Publication Nature Climate Change Abbreviated Journal Nature Climate change
Volume 4 Issue 10 Pages 846-848
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Abstract
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Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1758-678X ISBN Medium
Area Expedition Conference
Funding Approved $loc['no']
Call Number COAPS @ mfield @ Serial 151
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Author Wu, Z.; Feng, J.; Qiao, F.; Tan, Z.-M.
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
Corporate Author Thesis
Publisher Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1364-503X ISBN Medium
Area Expedition Conference
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.
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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Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
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 669
Permanent link to this record

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