ON THE RECENT RISING OF SEA LEVEL FROM SATELLITE ALTIMETRY: TRENDS IN GLOBAL AND OCEANIC SCALES

M. HADDAD

Abstract


In this paper, the seasonal and interannual variability of global and oceanic mean sea level variability are studied through a decomposition approach in the framework of the singular spectrum analysis (SSA) of available time series of sea level anomalies that extend back to 1993.The results show that the global mean sea level variability is dominated by an increasing trend. The rate of the global trend as seen by SSA appears to be about 3.36 mm/ year during the period 1993-2015. However, the trends from the different ocean regions show dissimilar patterns. The major contributions to the global sea level rise during 1993–2015 are from the Indian Ocean (3.80 mm/year).


Keywords


Sea level variability; Global and regional trends; Singular spectrum analysis; Seasonal-Trend Decomposition Based on LOESS.

Full Text:

PDF

References


ABLAIN M., CAZENAVE A., VALLADEAU G., GUINEHUT S. (2009). A new assessment of the error budget of global mean sea level rate estimated by satellite altimetry over 1993-2008, Ocean Science, Vol. 5, pp.193-201.

AVISO Altimetry. (2017a). Mean sea level rise and the Greenhouse effect, https://www.aviso.altimetry.fr/en/applications/ocean/mean-sea-level-greenhouse-effect.html, Accessed July 17.

AVISO Altimetry. (2017b). Mean rise in sea level is only part of the story, https://www.aviso.altimetry.fr/en/applications/ocean/mean-sea-level-greenhouse-effect/regional-trends.html. Accessed July 17, 2017

CLEVELAND S.W. (1979). Robust locally weighted regression and smoothing scatterplots, Journal of the American Statistical Association, Vol. 74, n°368, pp.829-836. doi: 10.1080/01621459.1979.10481038.

CLEVELAND W.S., DELVIN S.J. (1988). Locally Weighted Regression: An approach to regression analysis by local fitting, Journal of the American Statistical Association, Vol. 83, n°403, 5pp.96-610, doi: 10.1080/01621459.1988.10478639.

GOLYANDINA N., KOROBEYNIKOV A., SHLEMOV A., USEVICH K. (2015). Multivariate and 2D extensions of Singular Spectrum Analysis with the RSSA Package, Journal of Statistical Software, Vol. 67, Issue 2, pp.1-78. doi: 10.18637/jss.v067.i02.

GOLYANDINA N., NEKRUTKIN V., ZHIGLJAVSKY A. (2001). Analysis of time series structure: SSA and related techniques, Chapman & Hall/CRC Press.

HASSANI H. (2007). Singular Spectrum Analysis: Methodology and comparison, Journal of Data Science, Vol. 5, Issue 2, pp.239-257.

HASSANI H. (2010). A Brief introduction to singular Spectrum analysis. http://www.ssa.cf.ac.uk/a_brief_introduction_to_ssa.pdf

JEVREJEVA S., GRINSTED A., MOORE, J.C., HOLGATE S. (2006). Nonlinear trends and multiyear cycles in sea level records, Journal of Geophysical Research, Vol.111, Issue C9, doi:10.1029/2005JC003229.

MITCHUM G.T. (2000). An improved calibration of satellite altimetric heights using tide gauge sea levels with adjustment for land motion, Marine Geodesy, Vol.23, Issue 3, pp.145-166.

NEREM R.S., CHAMBERS D., CHOE C., MITCHUM G.T. (2010). Estimating Mean Sea Level Change from the TOPEX and Jason Altimeter Missions, Marine Geodesy, Vol. 33, Issue 1, pp.435-446. http://dx.doi.org/10.1080/01490419.2010.491031


Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.