Explore the vast range of titles available.

This paper is concerned with a complete asymptotic analysis as These boundary layers, which are the main center of interest of the present paper, exhibit several types of peculiar behaviour. First, the size of the boundary layer on the western and eastern boundary, which had already been computed by several authors, becomes formally very large as one approaches northern and southern portions of the boudary, i.e. pieces of the boundary on which the normal is vertical. This phenomenon is known as geostrophic degeneracy. In order to avoid such singular behaviour, previous studies imposed restrictive assumptions on the domain Moreover, when the domain Eventually, the effect of boundary layers is non-local in several aspects. On the first hand, for algebraic reasons, the boundary layer equation is radically different on the west and east parts of the boundary. As a consequence, the Sverdrup equation is endowed with a Dirichlet condition on the East boundary, and no condition on the West boundary. Therefore western and eastern boundary layers have in fact an influence on the whole domain

This paper is concerned with a complete asymptotic analysis as E \\to 0 of the Munk equation \\partial _x\\psi -E \\Delta ^2 \\psi = \\tau in a domain \\Omega \\subset \\mathbf R^2, supplemented with boundary conditions for \\psi and \\partial _n \\psi . This equation is a simple model for the circulation of currents in closed basins, the variables x and y being respectively the longitude and the latitude. A crude analysis shows that as E \\to 0, the weak limit of \\psi satisfies the so-called Sverdrup transport equation inside the domain, namely \\partial _x \\psi ^0=\\tau , while boundary layers appear in the vicinity of the boundary.

In this paper, we show the existence of the first non trivial family of classical global solutions of the inviscid surface quasi-geostrophic equation.

The Gulf Stream (GS) is known to have a strong influence on climate, for example, by transporting heat from the tropics to higher latitudes. Although the GS transport intensity presents a clear interannual variability, satellite observations reveal its mean path is stable. Numerical models can simulate some characteristics of the mean GS path, but persistent biases keep the GS separation and postseparation unstable and therefore unrealistic. This study investigates how the integration of ocean surface currents into the ocean–atmosphere coupling interface of numerical models impacts the GS. The authors show for the first time that the current feedback, through its eddy killing effect, stabilizes the GS separation and postseparation, resolving long-lasting biases in modeled GS path, at least for the Regional Oceanic Modeling System (ROMS). This key process should therefore be taken into account in oceanic numerical models. Using a set of oceanic and atmospheric coupled and uncoupled simulations, this study shows that the current feedback, by modulating the energy transfer from the atmosphere to the ocean, has two main effects on the ocean. On one hand, by reducing the mean surface stress and thus weakening the mean geostrophic wind work by 30%, the current feedback slows down the whole North Atlantic oceanic gyre, making the GS narrower and its transport weaker. Yet, on the other hand, the current feedback acts as an oceanic eddy killer, reducing the surface eddy kinetic energy by 27%. By inducing a surface stress curl opposite to the current vorticity, it deflects energy from the geostrophic current into the atmosphere and dampens eddies.

Version 2 of the unstructured-mesh Finite-Element Sea ice-Ocean circulation Model (FESOM) is presented. It builds upon FESOM1.4 (Wang et al., 2014) but differs by its dynamical core (finite volumes instead of finite elements), and is formulated using the arbitrary Lagrangian Eulerian (ALE) vertical coordinate, which increases model flexibility. The model inherits the framework and sea ice model from the previous version, which minimizes the efforts needed from a user to switch from one version to the other. The ocean states simulated with FESOM1.4 and FESOM2.0 driven by CORE-II forcing are compared on a mesh used for the CORE-II intercomparison project. Additionally, the performance on an eddy-permitting mesh with uniform resolution is discussed. The new version improves the numerical efficiency of FESOM in terms of CPU time by at least 3 times while retaining its fidelity in simulating sea ice and the ocean. From this it is argued that FESOM2.0 provides a major step forward in establishing unstructured-mesh models as valuable tools in climate research.

The Ocean Model Intercomparison Project (OMIP) focuses on the physics and biogeochemistry of the ocean component of Earth system models participating in the sixth phase of the Coupled Model Intercomparison Project (CMIP6). OMIP aims to provide standard protocols and diagnostics for ocean models, while offering a forum to promote their common assessment and improvement. It also offers to compare solutions of the same ocean models when forced with reanalysis data (OMIP simulations) vs. when integrated within fully coupled Earth system models (CMIP6). Here we detail simulation protocols and diagnostics for OMIP's biogeochemical and inert chemical tracers. These passive-tracer simulations will be coupled to ocean circulation models, initialized with observational data or output from a model spin-up, and forced by repeating the 1948–2009 surface fluxes of heat, fresh water, and momentum. These so-called OMIP-BGC simulations include three inert chemical tracers (CFC-11, CFC-12, SF6) and biogeochemical tracers (e.g., dissolved inorganic carbon, carbon isotopes, alkalinity, nutrients, and oxygen). Modelers will use their preferred prognostic BGC model but should follow common guidelines for gas exchange and carbonate chemistry. Simulations include both natural and total carbon tracers. The required forced simulation (omip1) will be initialized with gridded observational climatologies. An optional forced simulation (omip1-spunup) will be initialized instead with BGC fields from a long model spin-up, preferably for 2000 years or more, and forced by repeating the same 62-year meteorological forcing. That optional run will also include abiotic tracers of total dissolved inorganic carbon and radiocarbon, CTabio and 14CTabio, to assess deep-ocean ventilation and distinguish the role of physics vs. biology. These simulations will be forced by observed atmospheric histories of the three inert gases and CO2 as well as carbon isotope ratios of CO2. OMIP-BGC simulation protocols are founded on those from previous phases of the Ocean Carbon-Cycle Model Intercomparison Project. They have been merged and updated to reflect improvements concerning gas exchange, carbonate chemistry, and new data for initial conditions and atmospheric gas histories. Code is provided to facilitate their implementation.

The Atlantic meridional overturning circulation (AMOC) is pivotal for regional and global climate due to its key role in the uptake and redistribution of heat and carbon. Establishing the causes of historical variability in AMOC strength on different timescales can tell us how the circulation may respond to natural and anthropogenic changes at the ocean surface. However, understanding observed AMOC variability is challenging because the circulation is influenced by multiple factors that co-vary and whose overlapping impacts persist for years. Here we reconstruct and unambiguously attribute intermonthly and interannual AMOC variability at two observational arrays to the recent history of surface wind stress, temperature and salinity. We use a state-of-the-art technique that computes space- and time-varying sensitivity patterns of the AMOC strength with respect to multiple surface properties from a numerical ocean circulation model constrained by observations. While, on interannual timescales, AMOC variability at 26° N is overwhelmingly dominated by a linear response to local wind stress, overturning variability at subpolar latitudes is generated by the combined effects of wind stress and surface buoyancy anomalies. Our analysis provides a quantitative attribution of subpolar AMOC variability to temperature, salinity and wind anomalies at the ocean surface. Wind stress controls annual variations in the Atlantic meridional overturning circulation at mid-latitudes, while surface buoyancy also matters at subpolar latitudes, according to an attribution analysis using a numerical model constrained by observational array data.

Dispersal provides a key mechanism for geographical range shifts in response to changing environmental conditions. For mangroves, which are highly susceptible to climate change, the spatial scale of dispersal remains largely unknown. Here we use a high-resolution, eddy- and tide-resolving numerical ocean model to simulate mangrove propagule dispersal across the global ocean and generate connectivity matrices between mangrove habitats using a range of floating periods. We find high rates of along-coast transport and transoceanic dispersal across the Atlantic, Pacific, and Indian Oceans. No connectivity is observed between populations on either side of the American and African continents. Archipelagos, such as the Galapagos and those found in Polynesia, Micronesia, and Melanesia, act as critical stepping-stones for dispersal across the Pacific Ocean. Direct and reciprocal dispersal routes across the Indian Ocean via the South Equatorial Current and seasonally reversing monsoon currents, respectively, allow connectivity between western Indian Ocean and Indo-West Pacific sites. We demonstrate the isolation of the Hawaii Islands and help explain the presence of mangroves on the latitudinal outlier Bermuda. Finally, we find that dispersal distance and connectivity are highly sensitive to the minimum and maximum floating periods. We anticipate that our findings will guide future research agendas to quantify biophysical factors that determine mangrove dispersal and connectivity, including the influence of ocean surface water properties on metabolic processes and buoyancy behavior, which may determine the potential of viably reaching a suitable habitat. Ultimately, this will lead to a better understanding of global mangrove species distributions and their response to changing climate conditions.

We present a new framework for global ocean–sea-ice model simulations based on phase 2 of the Ocean Model Intercomparison Project (OMIP-2), making use of the surface dataset based on the Japanese 55-year atmospheric reanalysis for driving ocean–sea-ice models (JRA55-do). We motivate the use of OMIP-2 over the framework for the first phase of OMIP (OMIP-1), previously referred to as the Coordinated Ocean–ice Reference Experiments (COREs), via the evaluation of OMIP-1 and OMIP-2 simulations from 11 state-of-the-science global ocean–sea-ice models. In the present evaluation, multi-model ensemble means and spreads are calculated separately for the OMIP-1 and OMIP-2 simulations and overall performance is assessed considering metrics commonly used by ocean modelers. Both OMIP-1 and OMIP-2 multi-model ensemble ranges capture observations in more than 80 % of the time and region for most metrics, with the multi-model ensemble spread greatly exceeding the difference between the means of the two datasets. Many features, including some climatologically relevant ocean circulation indices, are very similar between OMIP-1 and OMIP-2 simulations, and yet we could also identify key qualitative improvements in transitioning from OMIP-1 to OMIP-2. For example, the sea surface temperatures of the OMIP-2 simulations reproduce the observed global warming during the 1980s and 1990s, as well as the warming slowdown in the 2000s and the more recent accelerated warming, which were absent in OMIP-1, noting that the last feature is part of the design of OMIP-2 because OMIP-1 forcing stopped in 2009. A negative bias in the sea-ice concentration in summer of both hemispheres in OMIP-1 is significantly reduced in OMIP-2. The overall reproducibility of both seasonal and interannual variations in sea surface temperature and sea surface height (dynamic sea level) is improved in OMIP-2. These improvements represent a new capability of the OMIP-2 framework for evaluating process-level responses using simulation results. Regarding the sensitivity of individual models to the change in forcing, the models show well-ordered responses for the metrics that are directly forced, while they show less organized responses for those that require complex model adjustments. Many of the remaining common model biases may be attributed either to errors in representing important processes in ocean–sea-ice models, some of which are expected to be reduced by using finer horizontal and/or vertical resolutions, or to shared biases and limitations in the atmospheric forcing. In particular, further efforts are warranted to resolve remaining issues in OMIP-2 such as the warm bias in the upper layer, the mismatch between the observed and simulated variability of heat content and thermosteric sea level before 1990s, and the erroneous representation of deep and bottom water formations and circulations. We suggest that such problems can be resolved through collaboration between those developing models (including parameterizations) and forcing datasets. Overall, the present assessment justifies our recommendation that future model development and analysis studies use the OMIP-2 framework.