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Abstract A dataset consisting of numerically simulated oceanic velocities and sea surface height changes, provided conjointly from Eulerian and Lagrangian points of view, is made available as cloud-optimized archives on a cloud storage platform for unrestricted access. The Eulerian component of the dataset comprises oceanic velocity components at 0 m and 15 m depth, as well as total and steric sea surface height changes, obtained at hourly time steps for one year, with an approximate horizontal resolution of 1/25 degree on an irregular global geographical spatial grid, from the HYbrid Coordinate Ocean Model. The Lagrangian component of the dataset comprises the trajectories of particles advected in the Eulerian velocity field of the model. The particles were advected forward and backward for 30 days from a regular 1/4 degree grid in order to achieve 60-day long trajectories at 0 m and 15 m depths, with start times separated by 30 days, in 11 releases. This integrated dataset may help to link Eulerian and Lagrangian observational perspectives. 

Abstract Internal waves generated by the interaction of the surface tides with topography are known to propagate long distances and lead to observable effects such as sea level variability, ocean currents, and mixing. In an effort to describe and predict these waves, the present work is concerned with using geographically distributed data from satellite altimeters and drifting buoys to estimate and map the baroclinic sea level associated with the M₂, S₂, N₂, K₁, and O₁tides. A new mapping methodology is developed, based on a mixedL₁/L₂-norm optimization, and compared with previously developed methods for tidal estimation from altimeter data. The altimeter and drifter data are considered separately in their roles for estimating tides and for cross-validating estimates obtained with independent data. Estimates obtained from altimetry and drifter data are found to agree remarkably well in regions where the drifter trajectories are spatially dense; however, heterogeneity of the drifter trajectories is a disadvantage when they are considered alone for tidal estimation. When the different data types are combined by using geodetic mission altimetry to cross validate estimates obtained with either exact-repeat altimetry or drifter data, and subsequently averaging the latter estimates, the estimates significantly improve on the previously published HRET8.1 model, as measured by their utility for predicting sea level and surface currents in the open ocean. The methodology has been applied to estimate the annual modulations of M₂, which are found to have much smaller amplitudes compared to those reported in HRET8.1, and suggest that the latter estimates of these tides were not reliable. Significance StatementThe mechanical and thermodynamic forcing of the ocean occurs primarily at very large scales associated with the gravitational perturbations of the sun and moon (tides), atmospheric wind stress, and solar insolation, but the frictional forces within the ocean act on very small scales. This research addresses the question of how the large-scale tidal forcing is transformed into the smaller-scale motion capable of being influenced by friction. The results show where internal waves are generated and how they transport energy across ocean basins to eventually be dissipated by friction. The results are useful to scientists interested in mapping the flows of mechanical energy in the ocean and predicting their influences on marine life, ocean temperature, and ocean currents. 

Abstract The geographical variability, frequency content, and vertical structure of near‐surface oceanic kinetic energy (KE) are important for air‐sea interaction, marine ecosystems, operational oceanography, pollutant tracking, and interpreting remotely sensed velocity measurements. Here, KE in high‐resolution global simulations (HYbrid Coordinate Ocean Model; HYCOM, and Massachusetts Institute of Technology general circulation model; MITgcm), at the sea surface (0 m) and at 15 m, are compared with KE from undrogued and drogued surface drifters, respectively. Global maps and zonal averages are computed for low‐frequency (<0.5 cpd), near‐inertial, diurnal, and semidiurnal bands. Both models exhibit low‐frequency equatorial KE that is low relative to drifter values. HYCOM near‐inertial KE is higher than in MITgcm, and closer to drifter values, probably due to more frequently updated atmospheric forcing. HYCOM semidiurnal KE is lower than in MITgcm, and closer to drifter values, likely due to inclusion of a parameterized topographic internal wave drag. A concurrent tidal harmonic analysis in the diurnal band demonstrates that much of the diurnal flow is nontidal. We compute simple proxies of near‐surface vertical structure—the ratio 0 m KE/(0 m KE + 15 m KE) in model outputs, and the ratio undrogued KE/(undrogued KE + drogued KE) in drifter observations. Over most latitudes and frequency bands, model ratios track the drifter ratios to within error bars. Values of this ratio demonstrate significant vertical structure in all frequency bands except the semidiurnal band. Latitudinal dependence in the ratio is greatest in diurnal and low‐frequency bands. 

Abstract Combining ocean model data and in situ Lagrangian data, I show that an array of surface drifting buoys tracked by a Global Navigation Satellite System (GNSS), such as the Global Drifter Program, could provide estimates of global mean sea level (GMSL) and its changes, including linear decadal trends. For a sustained array of 1,250 globally distributed buoys with a standardized design, I demonstrate that GMSL decadal linear trend estimates with an uncertainty less than 0.3 mm yr⁻¹could be achieved with GNSS daily random error of 1.6 m or less in the vertical direction. This demonstration assumes that controlled vertical position measurements could be acquired from drifting buoys, which is yet to be demonstrated. Development and implementation of such measurements could ultimately provide an independent and resilient observational system to infer natural and anthropogenic sea level changes, augmenting the ongoing tide gauge and satellites records. 

Abstract The surface kinetic energy of a 1/48° global ocean simulation and its distribution as a function of frequency and location are compared with the one estimated from 15,329 globally distributed surface drifter observations at hourly resolution. These distributions follow similar patterns with a dominant low‐frequency component and well‐defined tidal and near‐inertial peaks globally. Quantitative differences are identified with deficits of low‐frequency energy near the equator (factor 2) and at near‐inertial frequencies (factor 3) and an excess of energy at semidiurnal frequencies (factor 4) for the model. Owing to its hourly resolution and its near‐global spatial coverage, the array of surface drifters is an invaluable tool to evaluate the realism of tide‐resolving high‐resolution ocean simulations used in observing system simulation experiments. Sources of bias between model and drifter data are discussed, and associated leads for future work highlighted. 

A combined dataset on the Registry of Open Data on AWS of simulated ocean sea surface height, near-surface velocities, and particle trajectories from a global 1/25th degree HYbrid Coordinate Ocean Model (HYCOM) 1-year run. 

Abstract The accuracy of three data-constrained barotropic ocean tide models is assessed by comparison with data from geodetic mission altimetry and ocean surface drifters, data sources chosen for their independence from the observational data used to develop the tide models. Because these data sources do not provide conventional time series at single locations suitable for harmonic analysis, model performance is evaluated using variance reduction statistics. The results distinguish between shallow and deep-water evaluations of the GOT410, TPXO9A, and FES2014 models; however, a hallmark of the comparisons is strong geographic variability that is not well summarized by global performance statistics. The models exhibit significant regionally coherent differences in performance that should be considered when choosing a model for a particular application. Quantitatively, the differences in explained SSH variance between the models in shallow water are only 1%–2% of the root-mean-square (RMS) tidal signal of about 50 cm, but the differences are larger at high latitudes, more than 10% of 30-cm RMS. Differences with respect to tidal currents variance are strongly influenced by small scales in shallow water and are not well represented by global averages; therefore, maps of model differences are provided. In deep water, the performance of the models is practically indistinguishable from one another using the present data. The foregoing statements apply to the eight dominant astronomical tides M 2 , S 2 , N 2 , K 2 , K 1 , O 1 , P 1 , and Q 1 . Variance reduction statistics for smaller tides are generally not accurate enough to differentiate the models’ performance.