The sea-level data from TOPEX/Poseidon (ground tracks from the original mission and the tandem mission phase), Jason-1, and Jason-2 were processed by subtracting a mean sea surface from the corrected sea surface topography measurements, and applying cross-track and along-track gradient corrections. Relative altimeter biases between the three different altimeters were estimated globally with respect to TOPEX then applied to the regional study. The altimeter sea surface topography measurements were corrected for media (ionosphere, dry, and wet troposphere), instrument, and geophysical (solid Earth, pole and ocean tides, sea state bias, and atmosphere barotropic response) conditions.

The altimeter sea-level time series were corrected for dynamic atmosphere response using the AVISO dynamic atmosphere response model (Carrère and Lyard, 2003) and for atmospheric pressure (inverse barometer [IB]) using the European Centre for Medium-Range Weather Forecasts surface pressure model. These corrections were applied to the along-track sea-level data from each altimeter, and the data were averaged around each tide gage site into monthly measurements. The monthly tide gage sea-level data were corrected for IB effects using the National Oceanic and Atmospheric Administration Earth System Research Laboratory (NOAA ESRL) 20th Century Reanalysis V2 (Table B.1).2

Semiannual and annual signals for both the altimetry and tide gage sea-level time series were removed. Removal of these signals improved the correlation between the altimetry and tide gage sea-level data and reduced their root mean square (RMS) differences. Application of the atmosphere correction further reduced the sea-level variability of both the altimetry and tide gage data. The IB corrections had little impact on the linear sea-level trend estimated from the tide gage records, however they slightly reduced the correlation between the tide gage and altimetry sea-level data from 0.79 to 0.64 (Table B.1).

Both the tide gage and the altimetry sea-level data were corrected for GIA, and thus their estimated trends are directly comparable. For the tide gages, the sea-level trend was calculated by subtracting the GIA predicted relative sea-level trend from the tide gage estimated linear trend. The GIA predicted relative sea-level trend (absolute sea-level change minus the height change of the solid earth surface) at the gage benchmark is effectively a predicted vertical land motion estimate, with an opposite sign, if GIA is the only geophysical process. For altimetry, the geocentric sea-level trend was calculated by subtracting the GIA-model predicted absolute sea-level change from the altimeter sea-level trend (Peltier, 2001, Tamisiea, 2011). Table B.2 shows long-term tide gage estimated sea-level trends, corrected using the van der Wal GIA model, and the GIA model corrections from various GIA models.


Figure B.1 shows the GIA-model predicted relative sea-level change (computed by subtracting the crustal uplift from absolute sea-level change) from an ensemble of eight GIA models in western North America. Predicted values differ significantly from one another in Washington and Canada, but are similar along the coast. In the study region where the tide gages are located, the spread of GIA predicted values is between 1 mm yr-1 and 2 mm yr-1, mostly dominated by the difference in the predicted uplift rate of the solid earth.

Figure B.2 shows the tide gage estimated long-term sea-level trends, ~1900–2009, corrected for GIA using an ensemble of 17 models, as a function of latitude. The discrepancy in sea-level trend due to the choice of different GIA models is approximately 1 mm yr-1 for the southern tide gages and up to 2 mm yr-1 for the Washington gages (Figure B.2).

Figure B.3 compares the estimated sea-level trends for both tide gages and satellite altimetry for 1992–2008. Both records were corrected for IB and for GIA using the van der Wal GIA model (van der Wal et al., 2009). The sea-level trend determined from satellite altimetry (background color) and from the tide gages (color-coded circles) is in reasonable agreement along the coast. Figure B.3 shows that the sea-level trend is nonuniform geographically, and that satellite altimetry can measure the sea-level trends much further away from the coastal regions where tide gages reside.


2 The National Centers for Environmental Prediction (NCEP) Reanalysis Derived Data (Kalnay et al., 1996), which is valid for 1948–2011 and has a spatial resolution of 2.5° × 2.5°, can also be used to correct for inverse barometer. Tests showed that the performance of both the NOAA ESRL and NCEP models was almost identical.

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