Rainfall Patterns over India: Classification with Fuzzy c-Means Method |
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Authors: | A Kulkarni R H Kripalani |
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Institution: | (1) Indian Institute of Tropical Meteorology, Pune, India, IN |
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Abstract: | Summary Seasonal (June through September) percentage departure from normal rainfall patterns over India for the period 1871–1994
have been classified using Fuzzy c-means method (FCM) to identify the dominant modes of spatio-temporal variability in the
Indian monsoon rainfall. Unlike the hard clustering methods, for example the Map-to-Map (MM) correlation method and the k-means
(KM) clustering method, this method does not force a pattern to get classified into only one cluster but assigns varying membership
to every cluster. Thus marginal patterns get classified into all clusters with different memberships.
Patterns for the 124-year period are represented by the four dominant clusters. The spatial patterns associated with the extreme
(deficient/excess) Indian monsoon rainfall (IMR) get high membership in one of the clusters only, while the patterns associated
with the normal IMR get almost equal membership to all clusters. Even the spatial patterns during the El Ni?o/La Nina episodes
show high preference to a particular cluster. Time variation of each cluster shows that there are epochs where a particular
cluster dominates. Possible dynamic causes leading to the clusters are examined. Merits and demerits of the FCM method are
also discussed.
Received May 14, 1997 Revised July 22, 1997 |
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