ECCO Ocean Bottom Pressure

To aid in the interpretation of gravity change data over the oceans, we also provide ocean bottom pressure (OBP), as estimated by the ECCO Project (http://www.ecco-group.org). OBP is the sum of the mass of the atmosphere and ocean in a 'cylinder' above the seafloor.

It must be remembered that GRACE measures gravity, which can be caused by tectonics, for example the Sumatra earthquake of 2004. Furthermore, the ECCO model provided here is made to keep an ocean of constant mass: addition due to glacier melt, for example, are not included in the maps below.

The specifics of the model are described in Kim, Lee and Fukumori (2007); the data assimilation approach was developed by Fukumori (2002). The particular grids available here derive from the version kf66b, which assimilates altimetric heights, XBT profiles, and other ocean in-situ data. Quoting from Kim et al (2007):

" The model used is the parallel version of the primitive equation Massachusetts Institute of Technology (MIT) ocean GCM (Marshall et al. 1997). The spatial domain is nearly global (80°S–80°N). Horizontal grid spacing is 1° globally except within 20° of the equator, in which meridional grid spacing is gradually reduced to 0.3° within 10° of the equator. There are 46 vertical levels with layer thickness of 10 m in the upper 150 m and 21 layers above 300 m. The model employs two advanced mixing schemes: the K-profile parameterization (KPP) vertical mixing (Large et al. 1994) and the Gent–McWilliams (GM) isopycnal mixing (Gent and McWilliams 1990). The model is forced by the National Centers for Environmental Prediction (NCEP) reanalysis products (12-hourly wind stress, daily heat and freshwater air–sea fluxes) with the time means replaced by those of the Comprehensive Ocean–Atmosphere Data Set fluxes (da Silva et al. 1994). In addition to this imposed heat flux, model sea surface temperature (SST) is relaxed to NCEP’s SST analysis with a time scale of 1–2 months using the formulation of Barnier et al. (1995). The model was first spun up for 10 yr from rest using climatological temperature and salinity (Boyer and Levitus 1998) forced by seasonal climatological forcings averaged from 1980 to 1997. Additional descriptions of the model and comparison with various observational data are provided by Lee et al. (2002). An approximate Kalman filter and smoother (Fukumori 2002) are used to assimilate anomalies of sea level and of subsurface temperature obtained from the Ocean Topography Experiment (TOPEX)/Poseidon (T/P) altimeter and the Global Telecommunication System (GTS; D. Behringer 2002, personal communication), respectively. The assimilation procedure corrects the temporal variability of the prior NCEP wind forcing through inversion by the smoother, but does not correct the time-mean wind or, consequently, the model’s time-mean state. An earlier version of this system can be found in Fukumori et al. (1999). The modification of the wind forcing, although small in many regions, is effective in bringing the model closer to the data that are being assimilated. A detailed description of the principle of the Kalman filter and smoother approach can be found in Fukumori (2006). The resultant analysis fields are consistent with the physics of the GCM such that the property budgets (heat, salt, and momentum) are closed."

To the model grids, the following minor additional steps are applied:

- the global area average of each OBP map is removed (the model conserves volume, not mass. In addition, water fluxes are the hardes to obtain).
- the time-average OBP map between Jan 2003 and Dec 2007 is computed and removed from all grids. The resultant maps are departures from this time mean.
- monthly averages are computed from the twice per day ECCO output.
- the units (originally N/m^2) are converted to mbar.

The data can be found here.

When using these data, please cite the two papers listed below. Thank you.

REFERENCES:

Fukumori, I., 2002: A partitioned Kalman filter and smoother.
Mon. Wea. Rev., 130, 1370–1383.

Kim, S.B., T. Lee and I. Fukumori, 2007: Mechanisms Controlling the Interannual Variation of Mixed Layer Temperature Averaged over the Niño-3 Region. J. Climate, vol 20, p 3822-3843 . DOI: 10.1175/JCLI4206.1