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Abstract The decomposition of oceanic flow into its geostrophically balanced and unbalanced motions carries theoretical and practical significance for the oceanographic community. These two motions have distinct dynamical characteristics and affect the transport of tracers differently from one another. The launch of the Surface Water and Ocean Topography (SWOT) satellite provides a prime opportunity to diagnose the surface balanced and unbalanced motions on a global scale at an unprecedented spatial resolution. Here, we apply dynamic‐mode decomposition (DMD), a linear‐algebraic data‐driven method, to tidally‐forced idealized and realistic numerical simulations at submesoscale‐permitting resolution and one‐day‐repeat SWOT observations of sea‐surface height (SSH) in the Gulf Stream downstream of Cape Hatteras, a region commonly referred to as the separated Gulf Stream. DMD is able to separate out the spatial modes associated with sub‐inertial periods from super‐inertial periods. The sub‐inertial modes of DMD can be used to extract geostrophically balanced motions from SSH fields, which have an imprint of internal gravity waves, so long as the data extends long enough in time. We utilize the statistical relation between relative vorticity and strain rate as the metric to gauge the extraction of geostrophy. 

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 decay of the low‐mode internal tide due to the superharmonic energy cascade is investigated in a realistically forced global Hybrid Coordinate Ocean Model simulation with 1/25° (4 km) horizontal grid spacing. Time‐mean and depth‐integrated supertidal kinetic energy is found to be largest near low‐latitude internal tide generation sites, such as the Bay of Bengal, Amazon Shelf, and Mascarene Ridge. The supertidal kinetic energy can make up to 50% of the total internal tide kinetic energy several hundred kilometers from the generation sites. As opposed to the tidal flux divergence, the supertidal flux divergence does not correlate with the barotropic to baroclinic energy conversion. Instead, the time‐mean and depth‐integrated supertidal flux divergence correlates with the nonlinear kinetic energy transfers from (sub)tidal to supertidal frequency bands as estimated with a novel coarse‐graining approach. The regular spaced banding patterns of the surface‐intensified nonlinear energy transfers are attributed to semidiurnal mode 1 and mode 2 internal waves that interfere constructively at the surface. This causes patches where both surface tidal kinetic energy and nonlinear energy transfers are elevated. The simulated internal tide off the Amazon Shelf steepens significantly near these patches, generating solitary‐like waves in good agreement with Synthetic Aperture Radar imagery. Globally, we find that regions of high supertidal energy flux also show a high correlation with observed instances of internal solitary waves. 

Abstract High-frequency precipitation variance is calculated in 12 different free-running (non-data-assimilative) coupled high resolution atmosphere–ocean model simulations, an assimilative coupled atmosphere–ocean weather forecast model, and an assimilative reanalysis. The results are compared with results from satellite estimates of precipitation and rain gauge observations. An analysis of irregular sub-daily fluctuations, which was applied by Covey et al. (Geophys Res Lett 45:12514–12522, 2018.https://doi.org/10.1029/2018GL078926) to satellite products and low-resolution climate models, is applied here to rain gauges and higher-resolution models. In contrast to lower-resolution climate simulations, which Covey et al. (2018) found to be lacking with respect to variance in irregular sub-daily fluctuations, the highest-resolution simulations examined here display an irregular sub-daily fluctuation variance that lies closer to that found in satellite products. Most of the simulations used here cannot be analyzed via the Covey et al. (2018) technique, because they do not output precipitation at sub-daily intervals. Thus the remainder of the paper focuses on frequency power spectral density of precipitation and on cumulative distribution functions over time scales (2–100 days) that are still relatively “high-frequency” in the context of climate modeling. Refined atmospheric or oceanic model grid spacing is generally found to increase high-frequency precipitation variance in simulations, approaching the values derived from observations. Mesoscale-eddy-rich ocean simulations significantly increase precipitation variance only when the atmosphere grid spacing is sufficiently fine (< 0.5°). Despite the improvements noted above, all of the simulations examined here suffer from the “drizzle effect”, in which precipitation is not temporally intermittent to the extent found in observations. 

The effects of horizontal resolution and wave drag damping on the semidiurnal M2 tidal energetics are studied for two realistically-forced global HYbrid Coordinate Ocean Model (HYCOM) simulations with 41 layers and horizontal resolutions of 8 km (H12) and 4 km (H25). In both simulations, the surface tidal error is minimized by tuning the strength of the linear wave drag, which is a parameterization of the surface-tide energy conversion to the unresolved baroclinic wave modes. In both simulations the M2 surface tide error with TPXO8-atlas, an altimetry constrained model, is 2.6 cm. Compared to H12, the surface tide energy conversion to the resolved vertical modes is increased by 50% in H25. This coincides with an equivalent reduction in the tuned loss of energy from the surface tide to the wave drag. For the configurations studied here, the horizontal and not the vertical resolution is the factor limiting the number of vertical modes that are resolved in most of the global ocean: modes 1–2 in H12 and modes 1–5 in H25. The wave drag also dampens the resolved internal tides. The 40% reduction in wave-drag strength does not result in a proportional increase in the mode-1 energy density in H25. In the higher-resolution simulations, topographic mode-scattering and wave–wave interactions are better resolved. This allows for an energy flux out of mode 1 to the higher modes, mitigating the need for an internal tide damping term. The HYCOM simulations are validated with analytical conversion models and altimetry-inferred sea-surface height, fluxes, and surface tide dissipation. H25 agrees best with these data sets to within 10%. To facilitate the comparison of stationary tide signals extracted from time series with different durations, we successfully apply a spatially-varying correction factor. 

Abstract. With the increase in computational power, ocean models with kilometer-scale resolution have emerged over the last decade. These models have been used for quantifying the energetic exchanges between spatial scales, informing the design of eddy parametrizations, and preparing observing networks. The increase in resolution, however, has drastically increased the size of model outputs, making it difficult to transfer and analyze the data. It remains, nonetheless, of primary importance to assess more systematically the realism of these models. Here, we showcase a cloud-based analysis framework proposed by the Pangeo project that aims to tackle such distribution and analysis challenges. We analyze the output of eight submesoscale-permitting simulations, all on the cloud, for a crossover region of the upcoming Surface Water and Ocean Topography (SWOT) altimeter mission near the Gulf Stream separation. The cloud-based analysis framework (i) minimizes the cost of duplicating and storing ghost copies of data and (ii) allows for seamless sharing of analysis results amongst collaborators. We describe the framework and provide example analyses (e.g., sea-surface height variability, submesoscale vertical buoyancy fluxes, and comparison to predictions from the mixed-layer instability parametrization). Basin- to global-scale, submesoscale-permitting models are still at their early stage of development; their cost and carbon footprints are also rather large. It would, therefore, benefit the community to document the different model configurations for future best practices. We also argue that an emphasis on data analysis strategies would be crucial for improving the models themselves. 

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.