Abstract
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.
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