Steric sea level variability (1993–2010) in an ensemble of ocean reanalyses and objective analyses

Abstract

steric sea level changes are estimated and compared from an ensemble of 16 ocean reanalyses and 4 objective analyses. These estimates are initially compared with a satellite-derived (altimetry minus gravimetry) dataset for a short period (2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010). The ensemble mean exhibits a significant high correlation at both global and regional scale, and the ensemble of ocean reanalyses outperforms that of objective analyses, in particular in the Southern Ocean. The reanalysis ensemble mean thus represents a valuable tool for further analyses, although Abstract Quantifying the effect of the seawater density changes on sea level variability is of crucial importance for climate change studies, as the sea level cumulative rise can be regarded as both an important climate change indicator and a possible danger for human activities in coastal areas. In this work, as part of the Ocean Reanalysis Intercomparison Project, the global and regional This paper is a contribution to the special issue on Ocean estimation from an ensemble of global ocean reanalyses.A. Storto et al. 3large uncertainties remain for the inter-annual trends. Within the extended intercomparison period that spans the altimetry era (1993)(1994)(1995)(1996)(1997)(1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010), we find that the ensemble of reanalyses and objective analyses are in good agreement, and both detect a trend of the global steric sea level of 1.0 and 1.1 ± 0.05 mm/year, respectively. However, the spread among the products of the halosteric component trend exceeds the mean trend itself, questioning the reliability of its estimate. This is related to the scarcity of salinity observations before the Argo era. Furthermore, the impact of deep ocean layers is non-negligible on the steric sea level variability (22 and 12 % for the layers below 700 and 1500 m of depth, respectively), although the small deep ocean trends are not significant with respect to the products spread.

An assessment of air–sea heat fluxes from ocean and coupled reanalyses

“…64). These ocean reanalyses (hereafter the ORA-IP products) are examples of ocean data assimilated models that are actively being used either for climate monitoring studies, e.g., ocean heat content (Xue et al 2012;Balmaseda et al 2013b) or steric sea level (Storto et al 2015) variability, or for operational ocean forecasting (Lellouche et al 2013;Blockley et al 2014). Air-sea heat fluxes are made up of short and longwave radiation terms, along with turbulent fluxes for heat (sensible and latent) computed from bulk formulae, with both the outgoing longwave radiation (computed using the StephanBoltzmann Law) and the turbulent fluxes depending sensitively on the sea surface temperature (SST).…”

Regional Sea Level Variability and Trends, 1960–2007: A Comparison of Sea Level Reconstructions and Ocean Syntheses

“…An important question remains whether uncertainties in regional SSH trend estimates contain random errors, and whether an ensemble mean of the existing reconstructions could provide a better estimate. A similar approach is performed in the context of ocean reanalysis (Balmaseda et al, ; Storto et al, ), and with the LEGOS products (Meyssignac et al, ). Testing it here in the context of SSH reconstructions, it appears that averaging the products will improve the performance of the result with respect to the tide gauges, as was seen for the regional trends in Table (MAV columns for TGR mean, ODA mean, and Ensemble mean).…”

“…Köhl and Stammer () and Köhl () applied the ECCO state estimation techniques to estimate regional SSH changes over the last 50 years. Stammer et al () and Storto et al () compared SSH trends estimated by various ocean reanalysis approaches and highlighted differences in SSH trends from those results, especially for halosteric SSH trends. Chepurin et al () compared SSH data from ocean data reanalyses to tide gauges, similar to our approach here, but our goal is to additionally compare these products to the tide gauge reconstructions.…”

Uncertainties in Steric Sea Level Change Estimation During the Satellite Altimeter Era: Concepts and Practices

“…Storto et al (2015) do not provide information on grid box level or time series uncertainty. Rather, they provide as uncertainty estimates the 95 % confidence limits on their trend using a bootstrap (i.e.…”

“…L12 use data to extend the World Ocean Atlas (WOA) from 2009 to the end of 2010. EN3, which forms the input to two of the studies (D08 and Storto et al 2015), comprises WOD05 plus data from GTSPP, Argo and the Arctic Synoptic Basin Wide Oceanography (ASBO) project (Ingleby and Huddleston 2007), CORA comprises data from the Coriolis data centre, comprising European ship observations, XBT and other profiling systems, and Argo data. The data are global from 1990 onwards.…”