Sea Surface Height Variability in the Tropical Indian Ocean: Steric Contribution
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Variability of Sea level and its steric contribution in the Tropical Indian Ocean (TIO) was studied based on 15 years (1993–2007) satellite altimeter observations of sea surface height (SSH) anomaly and steric height (STH) anomaly computed using temperature and salinity fields obtained from Simple Ocean Data Assimilation (SODA) product. Complex Empirical Orthogonal Function (CEOF) analysis was carried out to decompose variability of SSH and STH into various modes to examine the coherency between them. It is revealed that both the parameters exhibit variability in all the time scales. First three major modes of CEOF corresponds to 90% and 84% of the total variability of SSH and STH respectively. There exists strong coherence between the respective CEOF modes of SSH and STH. The first mode of CEOF contributes around ~50% of the total signal corresponds to the annual cycle exhibit large variability in the western Arabian Sea along the Somali and Arabia Coast, latitudinal strip between 2 and 10°N extending from Somali-coast to the west coast of India, coastal oceans around India, and the south eastern TIO. The second CEOF with 25% of total signal contains mixed signature of intra-seasonal and inter-annual periodicities. This exhibit large amplitude in the central south TIO, western and eastern parts of Equatorial Indian Ocean (EIO). Computed long term linear growth rate of sea level anomaly suggests that increase of sea level varies from small (1–3 mm yr−1) in the north TIO to large (8 mm yr−1) in the south TIO. Further analysis suggests that SSH trend in the south TIO was mostly governed by steric contribution while the variability of SSH trend in the north TIO could be explained partially by the variability in STH.
KeywordsSatellite altimeter Sea surface height Indian Ocean El Nino Inter-annual variability
This work has been carried out under ISRO-CNES SARAL-ALTIKA science application program. One of the authors, MS is supported by a research fellowship under the program. We acknowledge AVISO and SODA team for making available the Sea Surface Data and SODA for time series T/S profiles of the global ocean.
- Antonov, J. I., Levitus, S., & Boyer, T. P. (2002). Steric sea level variations during 1957–1994: Importance of salinity. Journal of Geophysical Research, 107. doi: 10.1029/2001JC000964.
- AVISO. (1996). AVISO user handbook: Merged TOPEX/Poseidon products, ed. 3.0, AVI-NT-02-101-CN, July 1996, Toulouse, France.Google Scholar
- Fu, L.-L. (2010). Determining ocean circulation and sea level from satellite altimetry: Progress and challenges. In V. Barale, J. F. R. Gower and L. Alberotanza (Eds.), Oceanography from space (pp. 147–163). Springer, Netherlands, 978-90-481-8681-5.Google Scholar
- Gill, A. E. (1982). Atmosphere-Ocean dynamics (p. 662). London: Academic.Google Scholar
- Hannachi, A., Jolliffe, I. T., & Stephenson, D. B. (2010). Empirical orthogonal functions and related techniques in atmospheric science: A review. International Journal of Climatology, 27(1967), 1119–1152.Google Scholar
- Hariharan, H., Gribok, A., Abidi, M. A., & Koschan, A. (2006). Image fusion and enhancement via empirical mode decomposition. Journal of Pattern Recognition Research, 1, 16–32.Google Scholar
- Huang, N. E., Shen, Z., Long, S. R., Wu, M. C., Shih, H. H., Zheng, Q., Yen, N.-C., Tung, C. C., & Liu, H. H. (1998). The empirical mode decomposition and the Hilbert spectrum from nonlinear and non-stationary time series analysis. Proceedings of the Royal Society of London - Series A, 454, 903–995.CrossRefGoogle Scholar
- Jensen, T. G. (1991). Modelling the seasonal under current in the Somali current system. Journal of Geophysical Research, 96, 22 151–22 167.Google Scholar
- Rio, M-H, Schaeffer P., Moreaux G., Lemoine J.-M., Bronner E. (2009). A new mean dynamic topography computed over the global ocean from GRACE data, altimetry and in-situ measurements. Poster communication at OceanObs09 symposium, 21-25 September 2009, Venice.Google Scholar