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| Titel |
Empirical Mode Decomposition in 2-D space and time: a tool for space-time rainfall analysis and nowcasting |
| VerfasserIn |
S. Sinclair, G. G. S. Pegram |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1027-5606
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| Digitales Dokument |
URL |
| Erschienen |
In: Hydrology and Earth System Sciences ; 9, no. 3 ; Nr. 9, no. 3 (2005-07-22), S.127-137 |
| Datensatznummer |
250006860
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| Publikation (Nr.) |
 copernicus.org/hess-9-127-2005.pdf |
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| Zusammenfassung |
| A data-driven method for extracting temporally persistent
information, at different spatial scales, from rainfall data (as
measured by radar/satellite) is described, which extends the
Empirical Mode Decomposition (EMD) algorithm into two dimensions.
The EMD technique is used here to decompose spatial rainfall data
into a sequence of high through to low frequency components. This
process is equivalent to the application of successive low-pass
spatial filters, but based on the observed properties of the data
rather than the predetermined basis functions used in traditional
Fourier or Wavelet decompositions. It has been suggested in the
literature that the lower frequency components (those with large
spatial extent) of spatial rainfall data exhibit greater temporal
persistence than the higher frequency ones. This idea is explored
here in the context of Empirical Mode Decomposition. The paper
focuses on the implementation and development of the
two-dimensional extension to the EMD algorithm and it's
application to radar rainfall data, as well as examining temporal
persistence in the data at different spatial scales. |
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