Journal of Climate

Article: pp. 5889–5911 | Full Text | PDF (2.26M)

Decadal Trends in Sea Level Patterns: 1993–2004

Carl Wunsch

Department of Earth, Atmospheric, and Planetary Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts

Rui M. Ponte

Atmospheric and Environmental Research, Lexington, Massachusetts

Patrick Heimbach

Department of Earth, Atmospheric, and Planetary Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts

(Manuscript received 5 January 2007, in final form 8 May 2007)

DOI: 10.1175/2007JCLI1840.1

ABSTRACT

Estimates of regional patterns of global sea level change are obtained from a 1° horizontal resolution general circulation model constrained by least squares to about 100 million ocean observations and many more meteorological estimates during the period 1993–2004. The data include not only altimetric variability, but most of the modern hydrography, Argo float profiles, sea surface temperature, and other observations. Spatial-mean trends in altimetric data are explicitly suppressed to isolate global average long-term changes required by the in situ data alone. On large scales, some regions display strong signals although few individual points have statistically significant trends. In the regional patterns, thermal, salinity, and mass redistribution contributions are all important, showing that regional sea level change is tied directly to the general circulation. Contributions below about 900 m are significant, but not dominant, and are expected to grow with time as the abyssal ocean shifts. Estimates made here produce a global mean of about 1.6 mm yr−1, or about 60% of the pure altimetric estimate, of which about 70% is from the addition of freshwater. Interannual global variations may be dominated by the freshwater changes rather than by heating changes. The widely quoted altimetric global average values may well be correct, but the accuracies being inferred in the literature are not testable by existing in situ observations. Useful estimation of the global averages is extremely difficult given the realities of space–time sampling and model approximations. Systematic errors are likely to dominate most estimates of global average change: published values and error bars should be used very cautiously.

 

 

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