Results

Computed storage time series are dominated by an annual signal on which is superimposed interannual variability. As a test of the model, we compared the modeled seasonal cycle with that estimated indirectly from observations and, as a primitive index of uncertainty, with corresponding continental-water results from the Interactions between Soil, Biosphere and Atmosphere (ISBA) water-balance model (13, 14). Fig. 1a compares the estimates of sea-level change caused by mass exchange with the continents. This quantity is estimated to have amplitudes of 9.7 mm (maximum on September 1) for LaD and 9.4 mm (maximum on September 21) for ISBA. The small difference in amplitude is probably fortuitous, because model parameters (for example, effective storage capacities) are not known with great accuracy. Fig. 1a also displays an observational estimate of annual sea-level change caused by mass exchange with the continents. It is based on Topex/Poseidon satellite altimetry observations (6) after correcting for thermal expansion of the oceans and subtracting the atmospheric water vapor contribution. The observation-based annual ocean-mass variation has an amplitude of 8.4 mm and a maximum on September 9. (Topex-Poseidon altimetry gives an amplitude of ≈4 mm before correcting for the steric effect. The correction approximately doubles the amplitude, without changing the phase.) The residual signals (observed minus model-derived) obtained from the LaD and ISBA models (Fig. 1a) are similar in amplitude and could reflect model errors or an unaccounted signal. The phase of the LaD residual, in contrast with that of the ISBA simulation, is consistent with the expected timing of an Antarctic mass-storage signal (6); however, the phase of the residual is probably very sensitive to possible errors in the amplitude of the modeled signal. Fig. 1b shows contributions of the three water-storage components to the annual cycle of ocean mass.

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Fig. 1.

(a) Annual sea-level variation (mm) caused by continental mass exchange inferred indirectly from observations (red curve) and from modeled mass exchange with ground water, soil water, and snowpack (solid blue curve, LaD model; solid green curve, ISBA model, both expressed as equivalent sea-level change) as function of time (days). The dashed curves represent the corresponding residuals (observed minus modeled). At the annual time scale, the ocean mass can be derived from Topex/Poseidon satellite altimetry observations after removal of steric effects [density-related sea-level changes associated with thermal expansion and salinity change on the basis of the Levitus et al. climatology (15)]. This ocean-mass change is further adjusted here to remove the change caused by mass exchange with the atmosphere, which is estimated from National Centers for Environmental Prediction surface pressure fields. (Changes in global mean surface pressure are direct indications of changes in global atmospheric water content, because water is the only component of the atmosphere whose mass changes appreciably on this time scale.) Because there is no temporal overlap between the Topex/Poseidon data (1993–2001) and the ISBA data (1987–1988), we compute a mean annual cycle over all available data for each data set (including LaD data). Results for ocean mass and atmospheric water are taken from Cazenave et al. (6). To express land water mass stored on continents in terms of sea-level equivalent, we integrated unit-area water mass values, as given by the model, over the continental areas (excluding Greenland and Antarctica), then divided by water density and ocean area, and changed the sign. (b) Annual sea-level variation (mm) caused by continental mass exchange inferred from LaD-modeled mass exchange with ground water (broken light brown curve), soil water (broken green curve), and snowpack (dark brown curve), as function of time (days). Solid blue curve represents the sum of the other three curves.

Interannual variations of all three water-storage time series from the LaD model (expressed as equivalent global mean sea-level anomalies) exhibit small positive linear trends, corresponding to 18-yr decreases in continental storage, on which are superimposed interannual fluctuations (Fig. 2 a–c). The greatest trend is associated with ground water (0.07 mm/yr), followed by soil water (0.03 mm/yr) and snow (0.015 mm/yr).

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Fig. 2.

Time series of climate-driven changes in continental water mass, expressed as equivalent global sea-level anomalies (mm) for 1981–1998 [ground water (a), soil water (b), snowpack (c), sum of a–c (d)], and time series of CMAP precipitation anomaly over land (e). (Note that a positive trend in each of the first four panels corresponds to a decrease in terrestrial water storage.) For this analysis of interannual variability, we removed the total seasonal (annual and semiannual) signals from each variable and applied a 12-month running-mean smoother to the residuals.

Fig. 2d shows the equivalent sea-level time series associated with all estimated components of continental mass exchange. The positive trend (i.e., sea-level rise, or terrestrial desiccation) amounts to 0.12 mm/yr. This value is a direct estimate of the contribution to interdecadal sea-level rise associated with climate-driven changes in continental ground water, soil water, and snowpack.

For averages over all land, interannual variations in storage are controlled during most of this simulation by interannual variations of precipitation (Fig. 2e). Under a negative anomaly of precipitation, the land is generally drier than normal, hence more water is stored in the oceans. Storage anomalies track precipitation anomalies with little phase lag because residence times of water-storage anomalies on the continents are small. The reversal of this correlation for the first few years of the simulation appears to be associated with snow-storage anomalies, which are driven more by temperature than by precipitation.

Not surprisingly, water-storage trends of the largest magnitude (and either sign) are found in the humid equatorial and mid- to high-latitude zones (Fig. 3), where means and variabilities of precipitation are greatest. Trends of minimal magnitude are found in desert zones. The overall tendency for decreasing trends during the analysis period has regional exceptions in northeastern Asia and Alaska, sub-Saharan Africa, the south-Asian monsoon region, and parts of tropical South America. This pattern corresponds closely to that of trends in precipitation (data not shown).

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Fig. 3.

Geographical distribution of linear trend (1981–1998) in sum of ground water, soil water, and snowpack (mm water equivalent per yr) from the LaD model.

Discussion

The significance of the trend estimated here can be placed in the context of the observed 1.5- to 2-mm/yr rise of global mean sea level during the 20th century (2) and estimates of individual sources of sea-level change (3). For the 1981–1998 period, the ocean water density changes estimated by established methods (1) from global ocean temperature data (16) imply a steric sea-level rise of 0.72 ± 0.1 mm/yr. Our estimate of 0.12 mm/yr sea-level rise associated with mass exchange with ground water, soil water, and snow is considerably smaller than this amount but similar in magnitude to estimates of sea-level rise associated with mass exchange with ice sheets (3). Our results have errors of unknown magnitude and should be augmented by analyses with other land models and better atmospheric-forcing data sets.

The trends in ground water, soil water, and snowpack could be driven by internal variability in the hydrosphere and/or by forced climate change and so cannot be extrapolated beyond either end of the 18-yr analysis period. The controlling downtrend in precipitation during the period is not consistent with the expected global-warming precipitation signal (17) and is more likely a result of internal variability of the climate system. It seems, therefore, that the importance of this eustatic contribution to sea-level change is most significant at interannual to decadal time scales. For example, we find that the magnitude of the trend rises from 0.12 mm/yr for the period 1981–1998 to 0.18 mm/yr for 1990–1998 and to 0.25 mm/yr for 1993–1998 (the period of overlap with Topex/Poseidon observations). It is worth mentioning that the contributions to recent sea-level rise caused by mass loss from Greenland, Antarctica, and mountain glaciers have recently been revised upward (18, 19) (to 0.13 mm/yr, 0.16 mm/yr, and 0.35 mm/yr, respectively). It is unclear whether apparent acceleration of melting is associated with global warming or is at least partially another manifestation of internal variability in the water cycle.