Sea level observed by both tide gauges and altimetry includes both steric and mass contributions. The effects of large natural events such as volcanic eruptions are seen to be significant in the modelled global mean sea level record (Church et al.,
2005), as a sudden increase in aerosols decreases ocean temperatures, affecting the steric component. It is also reported that water storage in dams, which has increased since the 1950s, has decreased global sea levels by up to 30 mm (Chao
et al., 2008).
Several recent global mean sea level studies using both tide gauges and altimetry have trends that generally agree (Church and White, 2011, Holgate and Wood-
worth,2004,Jevrejeva et al.,2006), especially over the more recent, better sampled
period. Global mean sea level trends from altimetry for the period 1993 to 2009 were 3.2 ± 0.4 mm yr−1 (Church et al., 2013). At the time of the IPCC fourth
assessment report it was thought that the global mean sea level trends over this period were made up of around 50% contributions from the steric and mass com- ponents. Willis et al. (2004) concluded that over the 1990s, 1.6 ± 0.3 mm yr−1
was the steric contribution compared with about 3 mm yr−1 from altimetry, while
Lombard et al. (2005) found that the 1993 to 2008 steric trend was 1.7 ±0.4 mm
r−1 compared to 3.2
± 0.2 mm yr−1 from altimetry. ARGO data used in these
studies to determine the steric trend was in its infancy, and the altimetry dataset was only 10 years old. We now know that decadal and longer timescales still retain natural variability and using short trends will not distinguish between this decadal variability and a long term climate change.
More recently, in the IPCC AR5, the contributions to global mean sea level rise have been revised and it is now estimated that steric sea level accounts for 30% of the global sea level budget for 1993 to 2010 (Stocker et al., 2013).
5.3
Data
Satellite altimetry data is used from the Archiving, Validation and Interpretation of Satellite Oceanographic Data (AVISO) from 1993, which is in the format of a 1/3 degree spatially and 7 day temporal resolution. The altimeter products were
produced by Ssalto/Duacs and distributed by AVISO, with support from CNES
http://www.aviso.oceanobs.com/duacs/.
Data is obtained from the satellites TOPEX/Poseidon with follow on missions Jason-1 and Jason-2 (joint United States (NASA) and French (CNES) orbital missions launched in 1992, 2001 and 2008 respectively to track changes in sea level with radar altimeters), and European Remote Sensing satellites (ERS 1 then 2) with the follow on mission Environmental Satellite (Envisat), launched by the European Space Agency (ESA) in 1991, 1995 and 2002 respectively.
The uniform gridded product that we use is derived from (TOPEX/Poseidon or Jason) and (ERS or Envisat) data at all times except for 29 Dec 1993 to 15 Mar 1995 when only Topex/Poseidon data were available.
For the AVISO product that we use, data has been corrected for instrumental er- rors and errors due to atmospheric and ionospheric signal propagation delays and sea state bias, representing a tendency for there to be stronger reflections from wave troughs than from crests. Geophysical corrections are also applied includ- ing the ocean and pole tides, and the precise orbit is determined (Ablain et al.,
2009). These corrections are processed by the Centre Multimissions Altim´etrique, which is part of the Segment Sol Multimissions d’Altim´etrie, d’Orbitographie et de localisation pr´ecise (Ssalto), (http://www.aviso.oceanobs.com/en/data/product- information/ssalto.html). The Centre Multimissions Altim´etrique applies precise quality controls to the geophysical data and monitors for instrumental drift. The data used within this thesis is at level 4, where cross-calibration between multi- satellite missions has been combined to produce gridded data. Data has also been inverse barometer corrected for atmospheric pressure.
The time average of the dynamic topography T (cm) is shown in figure (5.2) as an 18 year mean between the years 1993 to 2010. Satellite altimetry measures the absolute sea level ASL as the height above the ellipsoid. To correct this to dynamic topography, an independent measure of G is required. The AVISO product assumesGto be unchanging, soGchanges due toGIAand other processes remain in the altimeter product.
Figure 5.2: Global 18 year mean dynamic topography from AVISO altimetry for the years 1993 to 2010 (cm).
5.3.1
The global mean dynamic topography
The ocean’s regional dynamic topography is not level, but influenced by a complex combination of processes. The largest contributor to deviation from the mean sea surface is G, where height differences can be ±100 m. Changes in density due to
salinity and temperature differences over long and short times scales set up small and large scale circulation patterns which we term the dynamic topography. The addition of mass to the ocean via freshwater addition also affects the dynamic to- pography. Since satellite altimetry brought near global coverage to measurements of this dynamic topography, our understanding of the structure of the global ocean has increased rapidly.
Figure (5.2) shows the mean dynamic topography between 1993 and 2010, the same 18 year time period that we later use to calculate the regional structure of trends in sea level. Mean dynamic topography is high in tropical and subtropical regions, lower in high latitudes and higher in the Indian and Pacific Oceans when compared to the Atlantic. The highest mean dynamic topography is south east of Japan and the lowest is in the Weddell Sea. Large-scale gyre systems in the subtropics can be distinguished by higher dynamic topography. There is a sharp gradient of dynamic height between the high southern latitudes where the cool fresh circumpolar water of the Antarctic and the warmer tropical water in the southern basins of the Indian, Pacific and Atlantic which are associated with the Antarctic Circumpolar Current.
There are intense boundary currents linked to gradients in dynamic topography, such as the Gulf Stream and the Aghulas Current.
Ocean circulation is determined by the winds and the density structure as well as constrained by the Earth’s rotation. We have analysed the trends in the density structure based on compilations of historical data contributing to steric height in Chapter 4. To minimise trends from wind stress variability, we use 18 year trends in our study to reduce the inter annual variability. Wind stress may indirectly produce longer term variability by changing the density structure of the ocean, but this effect is part of the steric variability.