Introducing an Ogive method for discontinuous data

► An Ogive method which is able to work with discontinuous data is presented. ► The method uses the discontinuous empirical mode decomposition (EMD) algorithm. ► The method allows Ogive curves to be calculated for discontinuous data, without inclusion of artificial data. Empirical mode decomposition...

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Bibliographic Details
Published inAgricultural and forest meteorology Vol. 162-163; pp. 58 - 62
Main Authors Barnhart, B.L., Eichinger, W.E., Prueger, J.H.
Format Journal Article
LanguageEnglish
Published Elsevier B.V 15.09.2012
Subjects
Algorithms
atmosphere
Atmospherics
data analysis
Data gaps
Decomposition
Empirical mode decomposition (EMD)
Mathematical analysis
Matlab
meteorological data
Ogive
Ogives
Spectra
Turbulence
turbulent flow
Empirical mode decomposition (EMD)
Data gaps
Ogive
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Summary:► An Ogive method which is able to work with discontinuous data is presented. ► The method uses the discontinuous empirical mode decomposition (EMD) algorithm. ► The method allows Ogive curves to be calculated for discontinuous data, without inclusion of artificial data. Empirical mode decomposition (EMD) is a spectral decomposition algorithm, which acts as a dyadic filter in the time-domain when extracting periodic components from turbulent atmospheric data. A new development in the algorithm allows it to work with discontinuous data. This investigation uses the discontinuous form of EMD (DEMD) to develop a new Ogive function, or cumulative flux calculation, which may be used with atmospheric data containing data gaps. The method is simple and effective, and will extend the utility of Ogives. The code is written in Matlab and available for use.
Bibliography:http://dx.doi.org/10.1016/j.agrformet.2012.04.003
ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:0168-1923
1873-2240
DOI:10.1016/j.agrformet.2012.04.003