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Selection of global climate models for India using cluster analysis

Raju, Srinivasa K and Kumar, Nagesh D (2016) Selection of global climate models for India using cluster analysis. In: JOURNAL OF WATER AND CLIMATE CHANGE, 7 (4). pp. 764-774.

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Official URL: http://dx.doi.org/10.2166/wcc.2016.112


Global climate models (GCMs) are gaining importance due to their capability to ascertain climate variables that will be useful to develop long, medium and short term water resources planning strategies. The applicability of K-Means cluster analysis is explored for grouping 36 GCMs from Coupled Model Intercomparison Project 5 for maximum temperature (MAXT), minimum temperature (MINT) and a combination of maximum and minimum temperature (COMBT) over India. Cluster validation methods, namely the Davies-Bouldin Index (DBI) and F-statistic, are used to obtain an optimal number of clusters of GCMs for India. The indicator chosen for evaluation of GCMs is the probability density function based skill score. It is noticed that the optimal number of clusters for MAXT, MINT and COMBT scenarios are 3, 2 and 2, respectively. Accordingly, suitable ensembles of GCMs are suggested for India for MAXT, MINT and COMBT individually. The suggested methodology can be extended to any number of GCMs and indicators, with minor modifications.

Item Type: Journal Article
Additional Information: Copy right for this article belongs to theIWA PUBLISHING, ALLIANCE HOUSE, 12 CAXTON ST, LONDON SW1H0QS, ENGLAND
Division of Mechanical Sciences > Civil Engineering
Date Deposited: 31 Jan 2017 04:34
Last Modified: 31 Jan 2017 04:34
URI: http://eprints.iisc.ac.in/id/eprint/55973

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