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The system of oceanic flows constituting the Atlantic Meridional Overturning Circulation (AMOC) moves heat and other properties to the subpolar North Atlantic, controlling regional climate, weather, sea levels, and ecosystems. Climate models suggest a potential AMOC slowdown towards the end of this century due to anthropogenic forcing, accelerating coastal sea level rise along the western boundary and dramatically increasing flood risk. While direct observations of the AMOC are still too short to infer long-term trends, we show here that the AMOC-induced changes in gyre-scale heat content, superimposed on the global mean sea level rise, are already influencing the frequency of floods along the United States southeastern seaboard. We find that ocean heat convergence, being the primary driver for interannual sea level changes in the subtropical North Atlantic, has led to an exceptional gyre-scale warming and associated dynamic sea level rise since 2010, accounting for 30-50% of flood days in 2015-2020.

 

Abstract. We have assembled 2 851 702 nearly cloud-free cutout images (sized 144 km × 144 km) of sea surface temperature (SST) data from the entire 2012–2020 Level-2 Visible Infrared Imaging Radiometer Suite (VIIRS) dataset to perform a quantitative comparison to the ocean model output from the MIT General Circulation Model (MITgcm). Specifically, we evaluate outputs from the LLC4320 (LLC, latitude–longitude–polar cap) 148∘ global-ocean simulation for a 1-year period starting on 17 November 2011 but otherwise matched in geography and the day of the year to the VIIRS observations. In lieu of simple (e.g., mean, standard deviation) or complex (e.g., power spectrum) statistics, we analyze the cutouts of SST anomalies with an unsupervised probabilistic autoencoder (PAE) trained to learn the distribution of structures in SST anomaly (SSTa) on ∼ 10–80 km scales (i.e., submesoscale to mesoscale). A principal finding is that the LLC4320 simulation reproduces, over a large fraction of the ocean, the observed distribution of SSTa patterns well, both globally and regionally. Globally, the medians of the structure distributions match to within 2σ for 65 % of the ocean, despite a modest, latitude-dependent offset. Regionally, the model outputs reproduce mesoscale variations in SSTa patterns revealed by the PAE in the VIIRS data, including subtle features imprinted by variations in bathymetry. We also identify significant differences in the distribution of SSTa patterns in several regions: (1) in an equatorial band equatorward of 15∘; (2) in the Antarctic Circumpolar Current (ACC), especially in the eastern half of the Indian Ocean; and (3) in the vicinity of the point at which western boundary currents separate from the continental margin. It is clear that region 3 is a result of premature separation in the simulated western boundary currents. The model output in region 2, the southern Indian Ocean, tends to predict more structure than observed, perhaps arising from a misrepresentation of the mixed layer or of energy dissipation and stirring in the simulation. The differences in region 1, the equatorial band, are also likely due to model errors, perhaps arising from the shortness of the simulation or from the lack of high-frequency and/or wavenumber atmospheric forcing. Although we do not yet know the exact causes for these model–data SSTa differences, we expect that this type of comparison will help guide future developments of high-resolution global-ocean simulations. 

The internal wave (IW) continuum of a regional ocean model is studied in terms of the vertical spectral kinetic energy (KE) fluxes and transfers at high vertical wavenumbers. Previous work has shown that this model permits a partial representation of the IW cascade. In this work, vertical spectral KE flux is decomposed into catalyst, source, and destination vertical modes and frequency bands of nonlinear scattering, a framework that allows for the discernment of different types of nonlinear interactions involving both waves and eddies. Energy transfer within the supertidal IW continuum is found to be strongly dependent on resolution. Specifically, at a horizontal grid spacing of 1/48°, most KE in the supertidal continuum arrives there from lower-frequency modes through a single nonlinear interaction, whereas at 1/384° and with sufficient vertical resolution KE transfers within the supertidal IW continuum are comparable in size to KE transfer from lower-frequency modes. Additionally, comparisons are made with existing theoretical and observational work on energy pathways in the IW continuum. Induced diffusion (ID) is found to be associated with a weak forward frequency transfer within the supertidal IW continuum. ID is also limited to the highest vertical wavenumbers and is more sensitive to resolution relative to spectrally local interactions. At the same time, ID-like processes involving high-vertical-wavenumber near-inertial and tidal waves as well as low-vertical-wavenumber eddy fields are substantial, suggesting that the processes giving rise to a Garrett–Munk-like spectra in the present numerical simulation and perhaps the real ocean may be more varied than in idealized or wave-only frameworks.

 

Surface ocean temperature and velocity anomalies at meso‐ and sub‐meso‐scales induce wind stress anomalies. These wind‐front interactions, referred to as thermal (TFB) and current (CFB) feedbacks, respectively, have been studied in isolation at mesoscale, yet they have rarely been considered in tandem. Here, we assess the combined influence of TFB and CFB and their relative impact on surface wind stress derivatives. Analyses are based on output from two regions of the Southern Ocean in a coupled simulation with local ocean resolution of 2 km. Considering both TFB and CFB shows regimes of interference, which remain mostly linear down to the simulation resolution. The jointly‐generated wind stress curl anomalies approach 10⁻⁵ N m⁻³, ∼20 times stronger than at mesoscale. The synergy of both feedbacks improves the ability to reconstruct wind stress curl magnitude and structure from both surface vorticity and SST gradients by 12%–37% on average, compared with using either feedback alone.

 

Abstract. We introduce a time-dependent, one-dimensional model ofearly diagenesis that we term RADI, an acronym accounting for the mainprocesses included in the model: chemical reactions, advection, molecularand bio-diffusion, and bio-irrigation. RADI is targeted for study ofdeep-sea sediments, in particular those containing calcium carbonates(CaCO3). RADI combines CaCO3 dissolution driven by organic matterdegradation with a diffusive boundary layer and integrates state-of-the-artparameterizations of CaCO3 dissolution kinetics in seawater, thusserving as a link between mechanistic surface reaction modeling andglobal-scale biogeochemical models. RADI also includes CaCO3precipitation, providing a continuum between CaCO3 dissolution andprecipitation. RADI integrates components rather than individual chemicalspecies for accessibility and is straightforward to compare againstmeasurements. RADI is the first diagenetic model implemented in Julia, ahigh-performance programming language that is free and open source, and itis also available in MATLAB/GNU Octave. Here, we first describe thescientific background behind RADI and its implementations. Following this, we evaluateits performance in three selected locations and explore other potentialapplications, such as the influence of tides and seasonality on earlydiagenesis in the deep ocean. RADI is a powerful tool to study thetime-transient and steady-state response of the sedimentary system toenvironmental perturbation, such as deep-sea mining, deoxygenation, oracidification events. 

Abstract. Wind work at the air-sea interface is the transfer of kinetic energy between the ocean and the atmosphere and, as such, is an important part of the ocean-atmosphere coupled system. Wind work is defined as the scalar product of ocean wind stress and surface current, with each of these two variables spanning, in this study, a broad range of spatial and temporal scales, from 10 km to more than 3000 km and hours to months. These characteristics emphasize wind work's multiscale nature. In the absence of appropriate global observations, our study makes use of a new global, coupled ocean-atmosphere simulation, with horizontal grid spacing of 2–5 km for the ocean and 7 km for the atmosphere, analyzed for 12 months.We develop a methodology, both in physical and spectral spaces, to diagnose three different components of wind work that force distinct classes of ocean motions, including high-frequency internal gravity waves, such as near-inertial oscillations, low-frequency currents such as those associated with eddies, and seasonally averaged currents, such as zonal tropical and equatorial jets.The total wind work, integrated globally, has a magnitude close to 5 TW, a value that matches recent estimates. Each of the first two components that force high-frequency and low-frequency currents, accounts for ∼ 28 % of the total wind work and the third one that forces seasonally averaged currents, ∼ 44 %. These three components, when integrated globally, weakly vary with seasons but their spatial distribution over the oceans has strong seasonal and latitudinal variations. In addition, the high-frequency component that forces internal gravity waves, is highly sensitive to the collocation in space and time (at scales of a few hours) of wind stresses and ocean currents. Furthermore, the low-frequency wind work component acts to dampen currents with a size smaller than 250 km and strengthen currents with larger sizes. This emphasizes the need to perform a full kinetic budget involving the wind work and nonlinear advection terms as small and larger-scale low-frequency currents interact through these nonlinear terms.The complex interplay of surface wind stresses and currents revealed by the numerical simulation motivates the need for winds and currents satellite missions to directly observe wind work.

 

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.