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This study addresses the boundary artifacts in machine‐learned (ML) parameterizations for ocean subgrid mesoscale momentum forcing, as identified in the online ML implementation from a previous study (Zhang et al., 2023, https://doi.org/10.1029/2023ms003697). We focus on the boundary condition (BC) treatment within the existing convolutional neural network (CNN) models and aim to mitigate the “out‐of‐sample” errors observed near complex coastal regions without developing new, complex network architectures. Our approach leverages two established strategies for placing BCs in CNN models, namely zero and replicate padding. Offline evaluations revealed that these padding strategies significantly reduce root mean squared error (RMSE) in coastal regions by limiting the dependence on random initialization of weights and restricting the range of out‐of‐sample predictions. Further online evaluations suggest that replicate padding consistently reduces boundary artifacts across various retrained CNN models. In contrast, zero padding sometimes intensifies artifacts in certain retrained models despite both strategies performing similarly in offline evaluations. This study underscores the need for BC treatments in CNN models trained on open water data when predicting near‐coastal subgrid forces in ML parameterizations. The application of replicate padding, in particular, offers a robust strategy to minimize the propagation of extreme values that can contaminate computational models or cause simulations to fail. Our findings provide insights for enhancing the accuracy and stability of ML parameterizations in the online implementation of ocean circulation models with coastlines. Plain Language Summary This study focuses on improving machine learning (ML) models used to predict ocean forces near coastlines, where errors arise because these models lack information in the area. We investigated how boundary conditions are handled in existing convolutional neural network models to reduce these errors without creating complex new architectures. By using two methods, that is, zero padding and replicate padding, we found that replicate padding significantly decreases prediction errors in coastal areas. While zero padding sometimes worsens issues in certain models, our results show that replicate padding is more reliable for effectively minimizing extreme value errors. This work highlights the importance of proper boundary condition treatment in ML models for coastal applications, ultimately aiming to enhance the accuracy and reliability of ocean circulation predictions. Key Points This study validates specialized boundary condition treatments in CNN models to reduce boundary artifacts in ocean parameterizations This approach can be applied directly to already trained CNN models to ensure accurate and stable implementation of mesoscale eddies parameterizations Replicate padding outperforms zero padding by minimizing boundary artifacts and preventing extreme values that compromise simulations

Species distribution models, linked to climate projections, are widely used in extinction-risk assessment and conservation planning. However, the degree of confidence that we can place on future climate-change projections depends on global climate-model performance and involves uncertainties that need to be assessed rigorously via climate-model evaluation. Performance assessments are important because the choice of climate model influences projections of species' range movement and extinction risk. A consensus view from the climate modeling community is that no single climate model is superior in its ability to forecast key climatic features. Despite this, the advantages of using multi-model ensemble-averaged climate forecasts to account for climate-model uncertainties have not been recognized by ecologists. Here we propose a method to use a range of skill and convergence metrics to rank commonly used atmosphere-ocean general circulation models (AOGCMs) according to their skill in reproducing 20-year observed patterns of regional and global climates of interest, and to assess their consistency with other AOGCMs. By eliminating poorly performing models and averaging the remainder with equal weights, we show how downscaled annual multi-climate-model ensemble-averaged forecasts, which have a strong regional focus, can be generated. We demonstrate that: (1) model ranking (match of simulated to observed conditions) differs according to the skill metric used, as well as the climate variable and season considered; (2) although the multi-model averaged result tends to outperform single models at a global scale, at the continental scale at least some models can perform better than the multi-model average; and (3) forecasts for the Australian region, which are often based on a single AOGCM (CSIRO-3.0), show spatial patterns of change that differ noticeably from ensemble-average projections based on a subset of better-performing AOGCMs. Our suggested approach-novel in the ecology discipline-provides a straightforward, consistent, and defensible method for conservation practitioners and natural-resource managers to generate estimates of future climate change at a spatial resolution suitable for biodiversity impact studies.

For endemic benthos inhabiting hydrothermal vent fields, larval recruitment is critical for population maintenance and colonization via migration among separated sites. The vent‐endemic limpet, Lepetodrilus nux, is abundant at deep‐sea hydrothermal vents in the Okinawa Trough, a back‐arc basin in the northwestern Pacific; nonetheless, it is endangered due to deep‐sea mining. This species is associated with many other vent species and is an important successor in these vent ecosystems. However, limpet genetic diversity and connectivity among local populations have not yet been examined. We conducted a population genetics study of L. nux at five hydrothermal vent fields (maximum geographic distance, ~545 km; depths ~700 m to ~1650 m) using 14 polymorphic microsatellite loci previously developed. Genetic diversity has been maintained among these populations. Meanwhile, fine population genetic structure was detected between distant populations, even within this back‐arc basin, reflecting geographic distances between vent fields. There was a significant, positive correlation between genetic differentiation and geographic distance, but no correlation with depth. Contrary to dispersal patterns predicted by an ocean circulation model, genetic migration is not necessarily unidirectional, based on relative migration rates. While ocean circulation contributes to dispersal of L. nux among vent fields in the Okinawa Trough, genetic connectivity may be maintained by complex, bidirectional dispersal processes over multiple generations.

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

Understanding the transport pathways of floating material at the ocean surface is important to improve our knowledge on surface circulation and assessing its environmental impacts. Numerical experiments through Lagrangian particle simulations are widely used to investigate the dispersion of floating material, typically relying on velocity fields from ocean circulation models. However, the contribution of different ocean dynamics (at different temporal and spatial scales) to the net Lagrangian transport remains unclear. Here we focus on tidal forcing, only included in recent ocean models, to explore its effect on particle dispersion at the ocean surface. By comparing a twin simulation with and without tidal forcing, we conclude that tide‐induced dynamics play an important role in horizontal Lagrangian pathways. We focus on the Azores Islands region and find that surface particles travel a longer cumulative distance and a lower total distance with than without tidal forcing. Additionally, tidal forcing leads to higher variability in surface particle accumulation patterns. The differences found in the surface particle accumulation patterns can be greater than 40%. These findings have important implications for virtual particle simulations, suggesting that considering tidal currents alone may not capture the full range of tide‐induced effects. A deeper understanding of the underlying dynamics is essential for accurately analyzing transport properties. Our outcomes can already help improve Lagrangian simulations made to understand the connectivity of marine species and for marine pollution applications, for example, ocean clean‐up strategies for plastics or oil spills, in the Azores Islands and regions with similar dynamics. At the surface of the Ocean we can find a variety of floating material for example, algae, larvae, plastics and oil spills. Accurately modeling their trajectories helps us understand ocean surface dynamics and their ecological, environmental and economic impacts. To simulate these trajectories, ocean currents derived from ocean models are typically used. These ocean models aim to represent different oceanic processes, and recent ones include the effect of tides. In this study, we investigate how tides affect surface particle trajectories in a region south of the Azores Islands. We examine both the distance traveled by the particles and their accumulation patterns. Our results show that tidal forcing influences both transport properties, and that its impact on accumulation patterns depends on the size of the ocean features, for example, whether the eddies are smaller or larger. We conclude that tides play an important role in shaping ocean surface trajectories. This has key applications for studying marine biodiversity and marine pollution forecasts. Twin ocean simulations reveal distinct ocean surface transport patterns, highlighting tides' role in Lagrangian dynamics Absolute distances decrease, but cumulative distances increase with tidal forcing, enhancing dispersion via complex pathways Tides add variability to surface particle accumulation patterns, optimizing simulations of pollution dispersal and marine connectivity

Ocean circulation models do not generally exhibit equatorial deep jets (EDJs), even though EDJs are a recognised feature of the observed ocean circulation along the equator and they are thought to be important for tracer transport along the equator and even equatorial climate. EDJs are nevertheless found in nonlinear primitive equation models with idealised box geometry. Here we analyse several such model runs. We note that the variability of the zonal velocity in the model is dominated by the gravest linear equatorial basin mode for a wide range of baroclinic vertical normal modes and that the EDJs in the model are dominated by energy contained in vertical modes between 10 and 20. The emergence of the EDJs is shown to involve the linear superposition of several such neighbouring basin modes. Furthermore, the phase of these basin modes is set at the start of the model run and, in the case of the reference experiment, the same basin modes can be found in a companion experiment in which the amplitude of the forcing has been reduced by a factor of 1000. We also argue that following the spin-up, energy must be transferred between different vertical modes. This is because the model simulations are dominated by downward phase propagation following the spin-up whereas our reconstructions imply episodes of upward and downward propagation. The transfer of energy between the vertical modes is associated with a decadal modulation of the EDJs.

We document the configuration and emergent simulation features from the Geophysical Fluid Dynamics Laboratory (GFDL) OM4.0 ocean/sea ice model. OM4 serves as the ocean/sea ice component for the GFDL climate and Earth system models. It is also used for climate science research and is contributing to the Coupled Model Intercomparison Project version 6 Ocean Model Intercomparison Project. The ocean component of OM4 uses version 6 of the Modular Ocean Model and the sea ice component uses version 2 of the Sea Ice Simulator, which have identical horizontal grid layouts (Arakawa C‐grid). We follow the Coordinated Ocean‐sea ice Reference Experiments protocol to assess simulation quality across a broad suite of climate‐relevant features. We present results from two versions differing by horizontal grid spacing and physical parameterizations: OM4p5 has nominal 0.5° spacing and includes mesoscale eddy parameterizations and OM4p25 has nominal 0.25° spacing with no mesoscale eddy parameterization. Modular Ocean Model version 6 makes use of a vertical Lagrangian‐remap algorithm that enables general vertical coordinates. We show that use of a hybrid depth‐isopycnal coordinate reduces the middepth ocean warming drift commonly found in pure z* vertical coordinate ocean models. To test the need for the mesoscale eddy parameterization used in OM4p5, we examine the results from a simulation that removes the eddy parameterization. The water mass structure and model drift are physically degraded relative to OM4p5, thus supporting the key role for a mesoscale closure at this resolution. Key Points Documentation is provided for a new generation of NOAA‐GFDL CMIP6/OMIP ocean ice climate models Dynamical core and physical parameterizations are described and key features of interannual CORE simulations are assessed Using hybrid vertical coordinates reduces spurious ocean heat drift

Aim: Test hypotheses that present biodiversity and endemic species richness are related to climatic stability and/or biome persistence. Location: Africa south of 15° S. Methods: Seventy eight HadCM3 general circulation model palaeoclimate experiments spanning the last 140,000 years, plus a pre-industrial experiment, were used to calculate measures of climatic variability for 0.5° grid cells. Models were fitted relating distributions of the nine biomes of South Africa, Lesotho and Swaziland to present climate. These models were used to simulate potential past biome distribution and extent for the 78 palaeoclimate experiments, and three measures of biome persistence. Climatic response surfaces were fitted for 690 bird species regularly breeding in the region and used to simulate present species richness for cells of the 0.5° grid. Species richness was evaluated for residents, mobile species (nomadic or partially/altitudinally migrant within the region), and intra-African migrants, and also separately for endemic/near-endemic (hereafter Endemic') species as a whole and those associated with each biome. Our hypotheses were tested by analysing correlations between species richness and climatic variability or biome persistence. Results: The magnitude of climatic variability showed clear spatial patterns. Marked changes in biome distributions and extents were projected, although limited areas of persistence were projected for some biomes. Overall species richness was not correlated with climatic variability, although richness of mobile species showed a weak negative correlation. Endemic species richness was significantly negatively correlated with climatic variability. Strongest correlations, however, were positive correlations between biome persistence and richness of endemics associated with individual biomes. Main conclusions: Low climatic variability, and especially a degree of stability enabling biome persistence, is strongly correlated with species richness of birds endemic to southern Africa. This probably principally reflects reduced extinction risk for these species where the biome to which they are adapted persisted.

EC-Earth is a newly developed global climate system model. Its core components are the Integrated Forecast System (IFS) of the European Centre for Medium Range Weather Forecasts (ECMWF) as the atmosphere component and the Nucleus for European Modelling of the Ocean (NEMO) developed by Institute Pierre Simon Laplace (IPSL) as the ocean component. Both components are used with a horizontal resolution of roughly one degree. In this paper we describe the performance of NEMO in the coupled system by comparing model output with ocean observations. We concentrate on the surface ocean and mass transports. It appears that in general the model has a cold and fresh bias, but a much too warm Southern Ocean. While sea ice concentration and extent have realistic values, the ice tends to be too thick along the Siberian coast. Transports through important straits have realistic values, but generally are at the lower end of the range of observational estimates. Exceptions are very narrow straits (Gibraltar, Bering) which are too wide due to the limited resolution. Consequently the modelled transports through them are too high. The strength of the Atlantic meridional overturning circulation is also at the lower end of observational estimates. The interannual variability of key variables and correlations between them are realistic in size and pattern. This is especially true for the variability of surface temperature in the tropical Pacific (El Niño). Overall the ocean component of EC-Earth performs well and helps making EC-Earth a reliable climate model.

Understanding of the three-dimensional circulation in the South China Sea (SCS) is crucial for determining the transports of water masses, energy, and biogeochemical substances in the regional and adjacent larger oceans. The circulation’s kinematic and dynamic natures, however, are largely unclear. Results from a three-dimensional numerical ocean circulation model and geostrophic currents, derived from hydrographic data, reveal the existence of a unique, three-layer, cyclonic–anticyclonic–cyclonic (CAC) circulation in the upper (<750 m), middle (750–1500 m), and deep (>1500 m) layers in the SCS with differing seasonality. An inflow–outflow–inflow structure in Luzon Strait largely induces the CAC circulation, which leads to vortex stretching in the SCS basin because of a lateral planetary vorticity flux in each of the respective layers. The formation of joint effects of baroclinicity and relief (JEBAR) is an intrinsic dynamic response to the CAC circulation. The JEBAR arises from the CAC flow–topography interaction in the SCS.