We revisit the nature of the ocean bottom pressure (OBP) seasonal cycle by leveraging the mounting GRACE-based OBP record and its assimilation in the ocean state estimates produced by the project for Estimating the Circulation and Climate of the Ocean (ECCO). We focus on the mean seasonal cycle from both data and ECCO estimates, examining their similarities and differences and exploring the underlying causes. Despite substantial year-to-year variability, the 21-year period studied (2002–2022) provides a relatively robust estimate of the mean seasonal cycle. Results indicate that the OBP annual harmonic tends to dominate but the semi-annual harmonic can also be important (e.g., subpolar North Pacific, Bellingshausen Basin). Amplitudes and short-scale phase variability are enhanced near coasts and continental shelves, emphasizing the importance of bottom topography in shaping the seasonal cycle in OBP. Comparisons of GRACE and ECCO estimates indicate good qualitative agreement, but considerable quantitative differences remain in many areas. The GRACE amplitudes tend to be higher than those of ECCO typically by 10%–50%, and by more than 50% in extensive regions, particularly around continental boundaries. Phase differences of more than 1 (0.5) months for the annual (semiannual) harmonics are also apparent. Larger differences near coastal regions can be related to enhanced GRACE data uncertainties and also to the absence of gravitational attraction and loading effects in ECCO. Improvements in both data and model-based estimates are still needed to narrow present uncertainties in OBP estimates.

Data from tide gauges and satellite altimeters are used to provide an up-to-date assessment of the mean seasonal cycle in sea level (ζ) over most of the global coastal ocean. The tide gauge records, where available, depict a ζ seasonal cycle with complex spatial structure along and across continental boundaries, and an annual oscillation dominating over semiannual variability, except in a few regions (e.g., the northwestern Gulf of Mexico). Comparisons between tide gauge and altimeter data reveal substantial root-mean-square differences and only slight improvements in agreement when using along-track data optimized for coastal applications. Quantification of the uncertainty in the altimeter products, inferred from comparing gridded and along-track estimates, indicate that differences to tide gauges partly reflect short-scale features of the seasonal cycle in proximity to the coasts. We additionally probe the ζ seasonal budget using satellite gravimetry-based manometric estimates and steric terms calculated from the World Ocean Atlas 2023. Focusing on global median values, the sum of the estimated steric and manometric harmonics can explain ~65% (respectively 40%) of the annual (semiannual) variance in the coastal ζ observations. We identify several regions, e.g., the Australian seaboard, where the seasonal ζ budget is not closed and illustrate that such analysis is mainly limited by the coarse spatial resolution of present satellite-derived mass change products. For most regions with a sufficiently tight budget closure, we find that although the importance of the manometric term generally increases with decreasing water depth, steric contributions are non-negligible near coastlines, especially at the annual frequency.

Emerging high-resolution global ocean climate models are expected to improve both hindcasts and forecasts of coastal sea level variability by better resolving ocean turbulence and other small-scale phenomena. To examine this hypothesis, we compare annual to multidecadal coastal sea level variability over the 1993-2018 period, as observed by tide gauges and as simulated by two identically-forced ocean models, at $\sim$1$^{\circ}$ (LR) and $\sim$0.1$^{\circ}$ (HR) horizontal resolution. Differences between HR and LR, and misfits with tide gauges, are spatially coherent at regional alongcoast scales. Resolution-related improvements are largest in, and near, marginal seas. Near attached western boundary currents, sea level variance is several times greater in HR than LR, but correlations with observations may be reduced, due to intrinsic ocean variability. Globally, in HR simulations, intrinsic variability comprises from zero to over 80\% of coastal sea level variance. Outside of eddy-rich regions, simulated coastal sea level variability is generally damped relative to observations. We hypothesize that weak coastal variability is related to large-scale, remotely-forced, variability; in both HR and LR, tropical sea level variance is underestimated by $\sim$50\% relative to satellite altimetric observations. Similar coastal dynamical regimes (e.g., attached western boundary currents) exhibit a consistent sensitivity to horizontal resolution, suggesting that these findings are generalizable to regions with limited coastal observations.

Satellite observations are used to establish the dominant magnitudes, scales, and mechanisms of intraseasonal variability in ocean dynamic sea level (ζ) in the Persian Gulf over 2002-2015. Empirical orthogonal function (EOF) analysis applied to altimetry data reveals a basin-wide, single-signed intraseasonal fluctuation that contributes importantly to ζ variance in the Persian Gulf at monthly to decadal timescales. An EOF analysis of Gravity Recovery and Climate Experiment (GRACE) observations over the same period returns a similar large-scale mode of intraseasonal variability, suggesting that the basin-wide intraseasonal ζ variation has a predominantly barotropic nature. A linear barotropic theory is developed to interpret the data. The theory represents Persian-Gulf-average ζ () in terms of local freshwater flux, barometric pressure, and wind stress forcing, as well as ζ at the boundary in the Gulf of Oman. The theory is tested using a multiple linear regression with these freshwater flux, barometric pressure, wind stress, and boundary ζ quantities as input, and as output. The regression explains 70%+/-9% (95% confidence interval) of the intraseasonal variance. Numerical values of regression coefficients computed empirically from the data are consistent with theoretical expectations from first principles. Results point to a substantial non-isostatic response to surface loading. The Gulf of Oman ζ boundary condition shows lagged correlation with ζ upstream along the Indian Subcontinent, Maritime Continent, and equatorial Indian Ocean, suggesting a large-scale Indian-Ocean influence on intraseasonal variation mediated by coastal and equatorial waves, and hinting at potential predictability. This study highlights the value of GRACE for understanding sea level in an understudied marginal sea.

A dynamic response of the ocean to surface pressure loading by the well-known 5-day Rossby-Haurwitz mode in the atmosphere has been inferred from limited in situ tide gauge and bottom pressure data, but a global characterization of such response, including details at mid and high latitudes, has been lacking. Here we explore two daily data products from the Gravity Recovery and Climate Experiment (GRACE) mission to obtain a first quasi-global look at the associated ocean bottom pressure (OBP) signals at 5-day period. The previously reported in-phase behavior over the Atlantic basin, seesaw between the Atlantic and Pacific, and westward propagation in the Pacific are all seen in the GRACE solutions. Other previously unknown features include relatively strong responses in the Southern Ocean and also some shallow coastal regions (e.g., North Sea, East Siberian shelf, Patagonian shelf). Correlation analysis points to the Rossby-Haurwitz surface pressure wave as the main forcing for the observed large-scale OBP anomalies, while wind-driven signals are more spatially confined. The GRACE observations are found to be consistent with in situ OBP data and also with model simulations of the 5-day ocean variability where no in situ data is available. Inferences on energetics based on data and model results point to decay time scales shorter than the oscillation period, with substantial kinetic energy and dissipation located over a few topographic features in the Southern Ocean. Results illustrate the potential of space gravity measurements for examining large-scale oceanic variability at sub-weekly periods.

Global ocean mean salinity (GMS) is a key indicator of the Earth’s hydrological cycle and the exchanges of freshwater between land and ocean, but its determination remains a challenge. Aside from traditional methods based on gridded salinity fields derived from in situ measurements, we explore estimates of GMS based on liquid freshwater changes derived from space gravimetry data corrected for sea ice effects. For the 2005-2019 period analyzed, the different GMS series show little consistency in seasonal, interannual, and long-term variability. In situ estimates show sensitivity to choice of product and unrealistic variations. A suspiciously large rise in GMS since ~ 2015 is enough to measurably affect halosteric sea level estimates and can explain recent discrepancies in the global mean sea level budget. Gravimetry-based GMS estimates are more realistic, inherently consistent with estimated freshwater contributions to global mean sea level, and provide a way to calibrate the in situ estimates.