Table of Contents
International Journal of Oceanography
Volume 2009, Article ID 214828, 11 pages
Research Article

The Use of MTM-SVD Technique to Explore the Joint Spatiotemporal Modes of Wind and Sea Surface Variability in the North Indian Ocean during 1993–2005

1Department of Mathematics, Faculty of Science, Burapha University, Chonburi 20131, Thailand
2Center of Excellence in Mathematics, Burapha University, Chonburi 20131, Thailand
3Department of Civil, Environmental, and Architectural Engineering, University of Colorado, Boulder, CO 80309, USA
4Co-Operative Institute for Research in Environmental Sciences, University of Colorado, Boulder, CO 80309, USA
5Department of Aerospace Engineering Sciences, University of Colorado, Boulder, CO 80309, USA

Received 10 November 2008; Accepted 23 March 2009

Academic Editor: William Hsieh

Copyright © 2009 Thaned Rojsiraphisal et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Sea surface height (SSH) and sea surface temperature (SST) in the North Indian Ocean are affected predominantly by the seasonally reversing monsoons and in turn feed back on monsoon variability. In this study, a set of data generated from a data-assimilative ocean model is used to examine coherent spatiotemporal modes of variability of winds and surface parameters using a frequency domain technique, Multiple Taper Method with Singular Value Decomposition (MTM-SVD). The analysis shows significant variability at annual and semiannual frequencies in these fields individually and jointly. The joint variability of winds and SSH is significant at interannual (2-3 years) timescale related to the ENSO mode—with a “/dipole/” like spatial pattern. Joint variability with SST showed similar but somewhat weaker behavior. Winds appear to be the driver of variability in both SSH and SST at these frequency bands. This offers prospects for long-lead projections of the North Indian Ocean climate.