Studies of the sea-level budget are a means of assessing our ability to quantify and understand sea-level changes and its causes. Closure of the total sea level budget implies that the observed changes of global mean sea level as determined from satellite altimetry equal the sum of observed (or otherwise assessed) contributions, namely changes in ocean mass and the steric component (mainly thermal expansion). Here, ocean mass changes can be either derived from GRACE satellite gravimetry (since 2002) or from adding up individual contributions from glaciers, ice sheets, land water storage (including snow cover) and atmospheric water content. Estimates of steric sea level are obtained from in situ ocean temperature and salinity measurements with additional inclusion of satellite derived sea surface temperature information. Misclosure of the sea-level budget indicates errors in some of the components or contributions from missing or unassessed elements in the budget.

ESA's Climate Change Initiative (CCI) includes the Sea Level CCI project, the Greenland and Antarctic Ice Sheet CCI projects, the Glaciers CCI project and the Sea Surface Temperature CCI project, all addressing Essential Climate Variables (ECVs) related to sea level. The cross-ECV project CCI Sea Level Budget Closure uses different products for the sea level and its components. These are based on the CCI projects mentioned above in conjunction with in situ data for ocean thermal expansion (e.g., Argo), GRACE-based assessments of ocean mass change, land water and land ice mass change, and model-based data for glaciers and land hydrology. The involvement of the authors of the individual data products facilitated consistency in product definition and analysis (e.g. in terms of spatio-temporal sampling and time-series analysis details) as well as in their uncertainty characterization.

In this contribution we report on the results of the sea-level budget assessment. We focus on two periods: 1993-2016 (the altimetry period) and 2003-2016 (the GRACE / Argo period). For the long-term trend, the budget is closed within uncertainties on the order of 0.3 mm/yr (1 sigma). Moreover, the budget is also closed within uncertainties for interannual variations. We discuss perspectives of future work, including a closer analysis of regional patterns.

Sea level is one of the best indicators of climate change. It combines changes occurring in the Earth’s climate system in response to unforced (or natural) climate variability, as well as natural and anthropogenic forcing factors. These include the net contribution of ocean warming, land ice melt, and changes in water storage in continental river basins. The global mean sea level is now included among the key climate indicators considered by WMO in the annual reports on the state of the global climate. Study of the sea level budget, i.e., comparison between the observed sea level and the sum of components (ocean thermal expansion, glacier and ice sheet melting and land water storage change) informs on missing or poorly known contributions such as the deep ocean warming not sampled by existing observing systems, or still uncertain changes in water storage on land due to human activities. Recent investigations on the global mean sea level budget, e.g., in the context of the WCRP or of the ESA CCI ‘Sea Level Closure Budget’ project, report closure within 0.4 mm/yr over the entire altimetry era, and within 0.3 mm/yr over the GRACE-Argo era. The latter value appears today as a threshold difficult to overcome. In this presentation, we examine the current uncertainties affecting all terms of the budget, including the altimetry-based sea level record. We highlight a number of remaining sources of errors that prevent better closure of the budget. Among them, imperfect knowledge of the Terrestrial Reference Frame (affecting altimetry-based sea level and GRACE-based ocean mass), of the GIA (Glacial Isostatic Adjustment) correction applied to altimetry and GRACE space gravimetry, and of the net land water storage contribution, as well as gaps in Argo coverage, e.g., in the Indonesian seas and in the Arctic, are more specifically addressed.

As the dominant reservoir of heat uptake in the climate system (93% of the total Earth heat uptake is located in the ocean [Levitus et al. 2012]), the ocean provides a critical measure of the Earth energy imbalance at the top of the Atmosphere. The ocean heat uptake can be inferred through the thermal expansion of the ocean estimated either directly from in situ Temperature profiles or indirectly with the sea level budget approach by combining satellite altimetry and GRACE observations. In this study we revisit the sea level budget approach and propose new estimates of the deep ocean warming and the Earth energy imbalance with reduced error bars (compared to previous studies such as Llovel et al. 2014). In previous studies GRACE and satellite altimetry observations have been estimated and combined in a reference frame centered on the center of figure of the Earth (CF). But GRACE and satellite altimeters move around the center of mass of the Earth (CM) and the projection of their observations in reference frames centered on the CF generates significant level of uncertainty in the data. In this study we combine for the first time new satellite altimetry products with new GRACE observations reprocessed with orbits centered on the CM. This approach enables to remove the source of uncertainty related to the projection on the CF and enables to test the sea level budget over the period 2005-2015 with unprecedented accuracy. This improved sea level budget approach indicates a important deep ocean warming of +0.22±0.25 wm-2 (at 1.65 sigma) and large Earth energy imbalance of 0.85±0.26 wm-2 (at 1.65 sigma) over the period 2005-2015.

The sea-level budget describes the partitioning and quantification of sea-level change due to each physical contributor, with the aim of obtaining a closed budget from independent observations. The total absolute sea-level change can be understood as the combination of mass and steric sea-level changes. On the global-scale and over the satellite altimetry era (since 1993), the sea-level budget can be closed when accounting for recently understood instrument error in the early TOPEX A altimetry record. The aim of the ERC-funded GlobalMass project is to close the sea-level budget on the regional to local scale, to better understand the processes involved in past sea-level variability and to improve our understanding to make better projections of sea-level rise at the coast, where communities are affected.

Here, we focus on the period with satellite and in-situ observational systems that offer near-full spatial coverage of the oceans, from January 2005 to December 2015. We combine the ESA SLCCI sea-level fields from satellite altimetry, with 4 global fields of steric sea-level using ARGO data from Scripps, JAMSTEC, the UK Met Office and Ifremer, with GRACE ocean mass estimates from CSR, JPL and GSFC.

Ocean mass change can be derived from GRACE observations, on the global scale either as the sum of land mass (hydrosphere and cryosphere) to ocean exchange, or directly from measurements made over the ocean. The latter observations are more sensitive to the GRACE processing methods than the former. Regional scale studies to-date have used the less sensitive land-cryosphere-ocean mass exchange observations from GRACE and assume a barystatic rise by modelling the gravitational and rotational effects of this mass exchange through the sea-level equation. Here, we attempt to close the sea-level budget on the ocean basin-scale using the direct ocean mass change observed by GRACE. Given the length of data now available, we investigate closing the sea-level budget in terms of linear trend from each observation system, focusing on spatial variability and regional scale budget. We discuss complexities in comparing the spatial pattern of trends from ocean mass change from GRACE with independent steric-corrected altimetry observations, with respect to sampling biases, time series length and completeness, and differences introduced by processing and instrumental corrections. To attempt to account for the heteroskedastic uncertainties in the observation systems, we use a Bayesian Hierarchical Model (BHM) to assess the relationship between the total sea-level trend and its mass and steric components. The BHM provides a probability distribution on the relationships between the processes and probabilistic spatial maps of the total sea-level, mass and steric trends over the period 2005—2015.

Over the past decades, the sea level in the western Pacific rose up to three times faster than the global mean, while its counterpart in the eastern Pacific including U.S. west coast was nearly stationary or decreasing [Moon and Song, 2013]. In fact, the regional seal-level trends have undergone two shifts, during the mid-1970s and in the early 1990s, with an east-west dipole pattern in the tropical Pacific. In each of these phases, the regional sea levels accelerated on one side of the Pacific, but decelerated on the other side. It is puzzling how long this pattern of regional sea level changes has been gone, what is the dynamic cause, and how these can affect deep ocean. These regional sea level changes, when superimposed on the global trend of sea level rise, could have profound implications for coastal communities and the health of marine and estuarial habitats. Combining recently reconstructed long-term sea level data products, upper-ocean measurements, recent satellite data, and a non-Boussinesq ocean circulation model [Song and Colberg, 2011], we will show that (1) the multi-decadal sea-level swings are the consequence of upper-ocean heat changes, closely related to the Pacific Decadal Oscillation (PDO)-induced ocean circulations; (2) the dueling climate cycles, PDO and ENSO, may have intensified the sea level swings in the tropical Pacific since 1980s [Moon et al., 2015]; and (3) differently, the deep ocean has shown a cooling trend in the tropics while a warming trend in the northern Pacific. Their underling dynamic mechanisms will be discussed.
Reference:
Moon, J.-H., Y. T. Song, and H. Lee (2015), PDO and ENSO modulations intensified decadal sea level variability in the tropical Pacific, J. Geophys. Res. Oceans, 120, doi:10.1002/2015JC011139.
Moon, J.-H., Y. T. Song, P. D. Bromirski, and A. J. Miller (2013), Multidecadal regional sea level shifts in the Pacific over 1958–2008, J. Geophys. Res. Oceans, 118, doi:10.1002/2013JC009297.
Moon, J.-H. and Y. T. Song (2013), Sea level and heat content changes in the western North Pacific. J. Geophys. Res. Oceans, 118, 2014-2022, doi:10.1002/jgrc.200.
Song, Y. T. and F. Colberg (2011), Deep ocean warming assessed from altimeters, Gravity Recovery and Climate Experiment, in situ measurements, and a non-Boussinesq ocean general circulation model, J. Geophys. Res., 116, C02020, doi:10.1029/2010JC006601.

Within the ESA supported Optimal Geoid for Modelling Ocean Circulation (OGMOC) project an optimally combined geoid model was derived. It is based on the GOCO05C setup, though the newer DTU15GRA altimetric surface gravity was used in the combination. The OGMOC geoid model was optimized to avoid striations and orange skin like features. Subsequently the model has been augmented using the EIGEN-6C4 coefficients to d/o 2160. Also, a newly updated mean sea surface was used. Compared to the DTU15MSS, the DTU18MSS has been derived by including re-tracked CRYOSAT-2 altimetry also, hence, increasing its resolution. Some issues in the Polar regions have been solved too.
Initially, a new geodetic DTU19MDT was derived using the OGMOC geoid model and the new DTU18MSS mean sea surface. The processing scheme was similar to the one used for the previous geodetic DTU17MDT model. The filtering was re-evaluated by adjusting the quasi-gaussian filter width to optimize the fit to drifter velocities. The results show that the new MDT improves the resolution of the details of the ocean circulation. Subsequently, the drifter velocities were integrated to enhance the resolution of the MDT. As a contribution to the ESA supported GOCE++ project DYCOT a special concern was devoted to the coastal areas to optimize the extrapolation towards the coast and to integrate mean sea levels at tide gauges into that process. The presentation will focus on the coastal zone when assessing the methodology, the data and the final model DTUUH19MDT.