Abstract's details
Sea level budget over 2005-2013: Missing contributions and data errors
CoAuthors
Event: 2015 Ocean Surface Topography Science Team Meeting
Session: Quantifying Errors and Uncertainties in Altimetry data
Presentation type: Type Poster
Contribution: not provided
Abstract:
Based on the sea level budget closure approach, this study investigates the residuals between observed global mean sea level (GMSL) and the sum of components (steric sea level and ocean mass) for the period January 2005 to December 2013. The objective is to identify the impact of errors in one or several components of the sea level budget on the residual time series. This is a key issue if we want to constrain missing contributions such as the contribution to sea level rise from the deep ocean (depths not covered by observations). For that purpose, we use several data sets as processed by different groups: six altimetry products for the GMSL, four Argo products plus the ORAS4 ocean reanalysis for the steric sea level and three GRACE-based ocean mass products. We find that over the study time span, the observed differences in trend of the residuals of the sea level budget equation can be as large as ~0.55 mm/yr (i.e., ~17% of the observed GMSL rate of rise). These trend differences essentially result from differences in trends of the GMSL time series. Using the ORAS4 reanalysis (providing complete geographical coverage of the steric sea level component), we also show that lack of Argo data in the Indonesian region leads to an overestimate of the absolute value of the residual trend by about 0.25 mm/yr. Accounting for this regional contribution leads to closure of the sea level budget, at least for some GMSL products. At short time scale (from sub-seasonal to interannual), residual anomalies are significantly correlated with ocean mass and steric sea level anomalies (depending on the time span), suggesting that the residual anomalies are related to errors in both GRACE-based ocean mass and Argo-based steric data. Efforts are needed to reduce these various sources of errors before using the sea level budget approach to estimate missing contributions such as the deep ocean heat content.