Ocean Model Research Articles

Mechanisms regulating trophic transfer in the Humboldt Upwelling System differ across time scales

Abstract The Humboldt Upwelling System hosts a highly productive ecosystem with central importance for global fisheries, yet with strong seasonal and interannual variability in the planktonic base of the food chain ultimately affecting fish yield. Understanding the variability in energy transfer within the plankton community in the contemporary climate can provide valuable insights for future projections of planktonic dynamics. Therefore, we use a regional physical-biogeochemical ocean model simulation (CROCO-BioEBUS) from 1990 to 2010 to investigate the underlying mechanisms of seasonal and interannual variability of the trophic transfer. Our model simulations suggest that, on an interannual scale, variations in trophic transfer are governed by variations in the offshore surface flow that modulate the plankton cross-shore distribution. Weak offshore surface flow, as simulated during the El Niño period, allows the zooplankton to stay relatively close to the shore, leading to more efficient grazing and trophic transfer compared to years with strong offshore flow. This mechanism differs from the seasonal one, where the mixed layer depth is the primary driver of variations in plankton dynamics, including trophic transfer. Our results highlight that mechanisms controlling plankton trophic transfer differ across time scales, and thus stress that extrapolating solely from seasonal findings to understand long-term trophic transfer changes in the context of climate change may be insufficient.

A Study on the Impact of Vertical Grid Parameter Perturbations in the Regional Ocean Modeling System

In this study, the Regional Ocean Modeling System (ROMS) is employed to construct a three-dimensional barotropic ocean model with a monodirectional upper boundary and homogeneous and steady wind covering the entire computation area. Eight perturbation experiments are designed to determine the vertical grid distribution difference with high resolution at the surface and bottom. Two types are considered in the model, including removing the Coriolis force (type 1) and employing a different Coriolis force (type 2). According to the experiments, the velocity of the current in type 1 yields uncertainty, and wind energy could penetrate the upper ocean and reach the abyss. The surface velocity in type 2 is fundamentally compatible with the empirical relationship constructed by Ekman, and the curved lines of the vertical distribution of horizontal currents nearly match. For type 1, the velocity is very strong from the sea surface to the bottom. When comparing type 1 and type 2 cases, the Coriolis force obstructs the wind energy transfer into the deep ocean. In addition, the European Centre for Medium-Range Weather Forecasts (ECMWF)’s global surface wind distribution indicates that the realistic ocean upper wind boundary is similar to the numerical experiment in the Pacific and Atlantic oceans, where the wind direction is along the latitude line at the equator. In order to make the experimental situation as close as possible to the real ocean, validation experiments are conducted in this study to consider the uncertainty in the current profile at the equator. The simulation results of type 1 differ significantly from the data obtained from the real ocean. This uncertainty may transfer the signal to higher latitudes, causing incorrect simulation results, especially in the critical region. Overall, this research not only makes discoveries in physical ocean theory but also guides predictive and forecasting techniques for ocean modeling.

Split-explicit external mode solver in the finite volume sea ice–ocean model FESOM2

Abstract. A novel split-explicit (SE) external mode solver for the Finite volumE Sea ice–Ocean Model (FESOM2) and its sub-versions is presented. It is compared with the semi-implicit (SI) solver currently used in FESOM2. The split-explicit solver for the external mode utilizes a dissipative asynchronous (forward–backward) time-stepping scheme that does not require additional filtering during the barotropic sub-cycling. Its implementation with arbitrary Lagrangian–Eulerian vertical coordinates like Z star (z*) and Z tilde (z̃) is explored. The comparisons are performed through multiple test cases involving idealized and realistic global simulations. The SE solver demonstrates lower phase errors and dissipation, while maintaining a simulated mean ocean state very similar to the SI solver. The SE solver is also shown to possess better run-time performance and parallel scalability across all workloads tested.

Spurious numerical mixing under strong tidal forcing: a case study in the south-east Asian seas using the Symphonie model (v3.1.2)

Abstract. The role of mixing between layers of different densities is key to how the ocean works and interacts with other components of the Earth's system. Correctly accounting for its effect in numerical simulations is therefore of utmost importance. However, numerical models are still plagued with spurious sources of mixing, originating mostly from the vertical advection schemes in the case of fixed-coordinate models. As the number of phenomena explicitly resolved by models increases, so does the amplitude of resolved vertical motions and the amount of spurious numerical mixing, and regional models are no exception to this. This paper provides a clear illustration of this phenomenon in the context of simulating the south-east Asian (SEA) seas along with a simple way to reduce its impact. This region is known for its particularly strong internal tides and the fundamental role they play in the dynamic of the region. Using the Symphonie ocean model, simulations including and excluding tides and using a pseudo-third-order upwind advection scheme on the vertical are compared to several reference datasets, and the impact on water masses is assessed. The high diffusivity of this advection scheme is demonstrated along with the importance of accounting for tidal mixing for a correct representation of water masses. Simultaneously, we present an improvement in this advection scheme to make it more suitable for use in the vertical. Simulations with the new formulation are added for comparison. We conclude that the use of a higher-order numerical diffusion operator greatly improves the overall performance of the model.

CanESM5-derived ocean wave projections — Considerations for coarse resolution climate models

This study presents the first set of CanESM5-driven wave projections for two emission scenarios (SSP5-8.5 and SSP2-4.5) and two time periods for mid- and end-century. While coarse resolution climate models, like CanESM5, might be less attractive for development of ocean wave projections, their results are needed to explore the full range of inter-model uncertainty in CMIP6 projections. Considering the coarse resolution limitation, wave simulations were obtained with a proposed computationally efficient 2-step bias-correction approach that consists of (i) calibrating the wind-to-wave energy transfer in the ocean wave model to reduce the underestimation of extremes resulting from coarse resolution, and (ii) bias-correcting the surface winds with a multivariate bias-correction to reduce remaining systematic biases. Results showed overall good performance in comparison with state of the art reanalysis and satellite data. Resulting projections provide increased understanding of future changes in wave conditions, confirming previously reported global-scale changes, such as higher waves in the eastern tropical Pacific and lower waves in the North Atlantic. They also provide more detailed information for areas affected by sea ice conditions in comparison to the latest CMIP5-based wave ensembles, which is critical for the Arctic region, a hotspot for ocean wave changes. Moreover, while the largest changes are typically seen by the end-century under SSP5-8.5, this study reveals that for some variables and areas, such as the mean wave period, larger changes occur for lower warming levels as a result of competing driving factors. Finally, the presented projections can contribute to ongoing efforts to generate a large multi-model ensemble of wave projections based on CMIP6.

Quantifying the Effect of Basic Minerals on Acid- and Ligand-Promoted Dissolution Kinetics of Iron in Simulated Dark Atmospheric Aging of Dust and Coal Fly Ash Particles.

The content and multiphase chemistry of iron (Fe) in multicomponent atmospheric aerosols are important to global climate and oceanic models. To date, reported dissolution rates of Fe span orders of magnitude with no quantifiable dependency on the content of basic minerals that coexist with Fe. Here, we report dissolution rates of Fe in simulated dark atmospheric aging of fully characterized multielement particles under acidic conditions (bulk pH 1 or 3) with and without oxalic acid and pyrocatechol. Our main findings are (a) the total amount of Ca and Mg was higher in coal fly ash than in Arizona test dust, (b) Fe dissolution initial rates increased exponentially with %Ca/Al and %Mg/Al below 50%, (c) a reduction in the Fe dissolution initial rate was observed with %Ca/Al higher than 50%, (d) reactive Ca and Mg minerals increased the calculated initial pH at the liquid/solid interface to values higher by only 1.5-2 units than the measured bulk pH, yet interfacial water remained acidic for Fe dissolution to take place, and (e) reactive Ca and Mg minerals enhanced the deprotonation of organics at the interface, aiding in ligand-promoted dissolution of Fe. The impact of these results is discussed within the context of constraining Fe dissolution kinetic models.

Ocean Complexity Shapes Sea Surface Temperature Variability in a CESM2 Coupled Model Hierarchy

Abstract To improve understanding of ocean processes impacting monthly sea surface temperature (SST) variability, we analyze a Community Earth System Model, version 2, hierarchy in which models vary only in their degree of ocean complexity. The most realistic ocean is a dynamical ocean model, as part of a fully coupled model (FCM). The next most realistic ocean, from a mechanically decoupled model (MDM), is like the FCM but excludes anomalous wind stress–driven ocean variability. The simplest ocean is a slab ocean model (SOM). Inclusion of a buoyancy coupled dynamic ocean as in the MDM, which includes temperature advection and vertical mixing absent in the SOM, leads to dampening of SST variance everywhere and reduced persistence of SST anomalies in the high latitudes and equatorial Pacific compared to the SOM. Inclusion of anomalous wind stress–driven ocean dynamics as in the FCM leads to higher SST variance and longer persistence time scales in most regions compared to the MDM. The net role of the dynamic ocean, as an overall dampener or amplifier of anomalous SST variance and persistence, is regionally dependent. Notably, we find that efforts to reduce the complexity of the ocean models in the SOM and MDM configurations result in changes in the magnitude of the thermodynamic forcing of SST variability compared to the FCM. These changes, in part, stem from differences in the seasonally varying mixed layer depth and should be considered when attempting to quantify the relative contribution of certain ocean mechanisms to differences in SST variability between the models.

Summer Chukchi Sea Near-Surface Salinity Variability in Satellite Observations and Ocean Models

Summer Chukchi Sea Near-Surface Salinity Variability in Satellite Observations and Ocean Models

Simulating cross-scale flow dynamics around offshore monopile foundations with a GFD-CFD coupled model

Flow dynamics are complex and undergo significant impact from offshore engineering infrastructures, such as wind turbines, involving interactions across different temporal and spatial scales. Individual numerical models of geophysical fluid dynamics (GFD) or computational fluid dynamics (CFD) face challenges in accurately representing these dynamics. To effectively capture the three-dimensional cross-scale flow around offshore infrastructures, we propose a generalized coupling framework that integrates the unstructured-grid Finite-Volume Community Ocean Model (FVCOM) for GFD and the Open Field Operation and Manipulation (OpenFOAM) for CFD. With the validation against the flume experiment, the common-boundary nesting method was developed to allow an accurate representation of flow dynamics around offshore hydraulic infrastructures. Idealized monopile foundation experiments demonstrate the model's capability to capture the formation of Karman vortex street, rotating horseshoe vortex under realistic astronomical tidal conditions. Application of this coupling framework to the offshore wind farm in Yangjiang, China, reveals flow direction lagging of 15° in the wake of a monopile under diurnal tide. This coupling approach, leveraging the strengths of both CFD and GFD models, provides a universal downscaling methodology in geophysical conditions, for a better understanding of the impact of offshore hydraulic infrastructures on the surrounding environment and further planning offshore engineering projects.

OceanNet: a principled neural operator-based digital twin for regional oceans

While data-driven approaches demonstrate great potential in atmospheric modeling and weather forecasting, ocean modeling poses distinct challenges due to complex bathymetry, land, vertical structure, and flow non-linearity. This study introduces OceanNet, a principled neural operator-based digital twin for regional sea-suface height emulation. OceanNet uses a Fourier neural operator and predictor-evaluate-corrector integration scheme to mitigate autoregressive error growth and enhance stability over extended time scales. A spectral regularizer counteracts spectral bias at smaller scales. OceanNet is applied to the northwest Atlantic Ocean western boundary current (the Gulf Stream), focusing on the task of seasonal prediction for Loop Current eddies and the Gulf Stream meander. Trained using historical sea surface height (SSH) data, OceanNet demonstrates competitive forecast skill compared to a state-of-the-art dynamical ocean model forecast, reducing computation by 500,000 times. These accomplishments demonstrate initial steps for physics-inspired deep neural operators as cost-effective alternatives to high-resolution numerical ocean models.

RIME-CNN-BiLSTM: A novel optimized hybrid enhanced model for significant wave height prediction in the Gulf of Mexico

Accurate prediction of SWH in the ocean is critical to the development of ocean energy technologies. However, existing forecasting models have limitations in accuracy and reliability, which directly affect the efficiency of ocean energy utilization. To address this problem, this paper proposes a new ocean SWH prediction model, RIME-CNN-BiLSTM, for predicting 1, 6, 12, and 24 h SWH at three buoy observing stations in the Gulf of Mexico. The model combines the RIME algorithm, CNN, and BiLSTM to comprehensively capture multiple parameters that affect wave heights, such as sea breeze, waves, barometric pressure, and temperature. The parameters of the CNN-BiLSTM model are optimized by the RIME algorithm, which significantly improves the prediction accuracy and generalization ability. Compared with the traditional model, RIME-CNN-BiLSTM captures the nonlinear features more accurately, has better prediction ability for outliers, and shows stronger generalization performance in different sea areas of the Gulf of Mexico. In terms of predicting the wave height in the next 24 h, the improvements are 7.065%, 3.646% and 5.186%, respectively. The results show that the RIME-CNN-BiLSTM model performs well in all prediction time periods, significantly outperforms other benchmark models, and is able to accurately capture nonlinear features and effectively predict outliers.

Internal‐Wave Dissipation Mechanisms and Vertical Structure in a High‐Resolution Regional Ocean Model

AbstractMotivated by the importance of mixing arising from dissipating internal waves (IWs), vertical profiles of internal‐wave dissipation from a high‐resolution regional ocean model are compared with finestructure estimates made from observations. A horizontal viscosity scheme restricted to only act on horizontally rotational modes (such as eddies) is introduced and tested. At lower resolutions with horizontal grid spacings of 2 km, the modeled IW dissipation from numerical model agrees reasonably well with observations in some cases when the restricted form of horizontal viscosity is used. This suggests the possibility that if restricted forms of horizontal viscosity are adopted by global models with similar resolutions, they could be used to diagnose and map IW dissipation distributions. At higher resolutions with horizontal grid spacings of ∼250 m, the dissipation from vertical shear and horizontal viscosity act much more strongly resulting in dissipation overestimates; however, the vertical‐shear dissipation itself is found to agree well with observations.

The impact of coupling a dynamic ocean in the Hurricane Analysis and Forecast System

Coupling a three-dimensional ocean circulation model to an atmospheric model can significantly improve forecasting of tropical cyclones (TCs). This is particularly true of forecasts for TC intensity (maximum sustained surface wind and minimum central pressure), but also for structure (e.g., surface wind-field sizes). This study seeks to explore the physical mechanisms by which a dynamic ocean influences TC evolution, using an operational TC model. The authors evaluated impacts of ocean-coupling on TC intensity and structure forecasts from NOAA’s Hurricane Analysis and Forecast System v1.0 B (HFSB), which became operational at the NOAA National Weather Service in 2023. The study compared existing HFSB coupled simulations with simulations using an identical model configuration in which the dynamic ocean coupling was replaced by a simple diurnally varying sea surface temperature model. The authors analyzed TCs of interest from the 2020–2022 Atlantic hurricane seasons, selecting forecast cycles with small coupled track-forecast errors for detailed analysis. The results show the link between the dynamic, coupled ocean response to TCs and coincident TC structural changes directly related to changing intensity and surface wind-field size. These results show the importance of coupling in forecasting slower-moving TCs and those with larger surface wind fields. However, there are unexpected instances where coupling impacts the near-TC atmospheric environment (e.g., mid-level moisture intrusion), ultimately affecting intensity forecasts. These results suggest that, even for more rapidly moving and smaller TCs, the influence of the ocean response to the wind field in the near-TC atmospheric environment is important for TC forecasting. The authors also examined cases where coupling degrades forecast performance. Statistical comparisons of coupled versus uncoupled HFSB further show an interesting tendency: high biases in peak surface winds for the uncoupled forecasts contrast with corresponding low biases, contrary to expectations, in coupled forecasts; the coupled forecasts also show a significant negative bias in the radii of 34 kt winds relative to National Hurricane Center best track estimates. By contrast, coupled forecasts show very small bias in minimum central pressure compared with a strong negative bias in uncoupled. Possible explanations for these discrepancies are discussed. The ultimate goal of this work will be to enable better evaluation and forecast improvement of TC models in future work.

Analysis of Nearshore Near-Inertial Oscillations Using Numerical Simulation with Data Assimilation in the Pearl River Estuary of the South China Sea

The High-Frequency (HF) radar network has become an effective method for detecting coastal currents. In this study, we confirmed the effectiveness of the HF radar measurements by comparing with the Acoustic Doppler Current Profiler (ADCP) and explore the possibility of assimilating radar data into a regional coastal ocean model. A regional high-resolution model with resolution of 10 m was first built in the Pearl River Estuary (PRE). However, analysis of the Hovmöller diagrams from the model simulations in this study indicated a significant deficiency in representing Near-Inertial Oscillations (NIOs) in the PRE, particularly in the east–west direction, despite including wind fields in the input data, during the week from 3 to 8 August 2022. To overcome the model deficiency, we conducted a set of assimilation experiments and performed sensitivity analyses. The results of sensitivity experiments indicate that the model exhibits a sufficient capacity to replicate NIOs after assimilation, lasting approximately 5–6 days. To further analyze the reasons for the decay in the magnitude of the NIOs, data from the three ADCP stations were compared with model results by applying the momentum equation. The assimilated vertical diffusion term outperforms the unassimilated model in representing NIOs. These findings highlight the importance of the vertical diffusion term for simulating NIOs and the data assimilation in improving the model’s representation of physical processes.

An Algorithm to Retrieve Range Ocean Current Speed under Tropical Cyclone Conditions from Sentinel-1 Synthetic Aperture Radar Measurements Based on XGBoost

In this study, a novel algorithm to retrieve the current speed along the range direction under extreme sea states is developed from C-band synthetic aperture radar imagery. To this aim, a Sentinel-1 (S-1) dual-polarized synthetic aperture radar (SAR) dataset consisting of 2300 images is collected during 200 tropical cyclones (TCs). The dataset is complemented with collocated wave simulations from the Wavewatch-III (WW3) model and reanalysis currents from the HYbrid Coordinate Ocean Model (HYCOM). The corresponding TC winds are officially released by IFRMER, while the Stokes drift following the wave propagation direction is estimated from the waves simulated by WW3. In this study, first the dependence of wind, Stokes drift, and range current on the Doppler centroid anomaly is investigated, and then the extreme gradient boosting (XGBoost) machine learning model is trained on 87% of the S-1 dataset for range current retrieval purposes. The rest of the dataset is used for testing the retrieval algorithm, showing a root mean square error (RMSE) and a correlation coefficient (r) of 0.11 m/s and 0.97, respectively, with the HYCOM outputs. A validation against measurements collected from two high-frequency (HF) phased-array radars is also performed, resulting in an RMSE and r of 0.12 m/s and 0.75, respectively. Those validation results are better than the 0.22 m/s RMSE and 0.28 r achieved by the empirical CDOP model. Hence, the experimental results confirm the soundness of the XGBoost, exhibiting a certain improvement over the empirical model.

Intraseasonal Variations and Extreme Occurrence in the Local Sea Level Along the Western Coast of India Remotely Controlled by a Basin‐Scale Climate Variability

AbstractThe equatorial Kelvin waves, remotely excited by basin‐scale climate modes, and subsequent coastal trapped waves significantly influence the intraseasonal variations, their low‐frequency modulations, and the frequency of extreme sea level events along the western coast of India. This study demonstrates that the frequency of extreme events are linked to the phase of the Indian Ocean Dipole mode. The temporal changes in the occurrence frequency of extremes are simulated in an eddy‐resolving ocean model consistently with observations. However, a non‐eddying model significantly underestimate the occurrence frequency of extreme sea level events, suggesting the importance of coastal trapped wave propagations regulated by the horizontal scale with the Rossby radius of deformation. This result implies that many state‐of‐the‐art climate models with a one‐degree ocean horizontal resolution may underestimate future coastal sea level variability and the frequency of extreme events under global warming and potential modulations of major internal climate modes.

Effects of Horizontal Resolution on Long‐Range Equatorward Radiation of Near‐Inertial Internal Waves in Ocean General Circulation Models

AbstractWind‐generated near‐inertial internal waves (NIWs) are characterized by dominant long‐range equatorward radiation due to the gradient of the planetary vorticity, known as the β‐refraction effect. In this study, we analyze the effects of horizontal model resolution on the long‐range equatorward radiation of NIWs. In a high‐resolution Community Earth System Model (CESM‐HR) with a 0.1° oceanic resolution, about 25% (15%) of NIW energy flux injected downward the surface boundary layer base poleward of 30°N (30°S) radiates into the lower‐latitude region. This ratio decreases to about 15% (8%) in a low‐resolution CESM (CESM‐LR) with a 1° oceanic resolution. The higher long‐range equatorward radiation efficiency in the CESM‐HR than the CESM‐LR is directly attributed to the faster equatorward group velocity of the NIWs of the first three vertical modes, which reflects the better representation of equatorward propagation and beta‐refraction of smaller scale NIWs in the CESM‐HR. The enhancement of equatorward wavenumber induced by the β‐refraction is inhibited in the CESM‐LR, which underrepresent the long‐range equatorward radiation of NIWs. These results underscore the necessity of high‐resolution ocean models in accurately simulating the spatial variabilities of NIWs and their induced turbulent diapycnal mixing in the global ocean.

Mean‐State and Seasonal Variability in Temperature Structure and Heat Transport in the East Australian Current System From a Multi‐Decadal Regional Ocean Model

AbstractWestern Boundary Currents (WBCs) such as the East Australian Current (EAC) are vital for moving heat from low to high latitudes, controlling regional weather and global climate. Previous EAC System studies have provided a general overview of temperature variability and heat transport, but they lacked spatial and seasonal detail. Using a high‐resolution, 26‐year‐long ocean model simulation, we systematically characterize the seasonal variability and structure in key temperature metrics and heat transport in the EAC System. Our findings reveal a clear seasonal cycle with a poleward expansion of key variables in summer (mean and eddy kinetic energy, upper ocean heat content, heat transport) and contraction equatorward with reductions in winter. We show that the dynamical regime transition, from jet to eddy‐dominated at the EAC separation zone (S), modifies the net meridional heat transport. Upstream of separation, transport is poleward, with some zonal input of heat. Downstream of EAC separation, there is an increase in heat recirculation by mesoscale eddies combined with a smaller zonal export of heat. This study highlights the significance of resolving spatio‐temporal variability in WBC systems driven by mesoscale dynamics, which will have implications for the representation of critical dynamics in future climate models.

Consistent Seasonal Hydrography From Moorings at Northwest Greenland Glacier Fronts

AbstractGreenland's marine‐terminating glaciers connect the ice sheet to the ocean and provide a critical boundary where heat, freshwater, and nutrient exchanges take place. Buoyant freshwater runoff from inland ice sheet melt is discharged at the base of marine‐terminating glaciers, forming vigorous upwelling plumes. It is understood that subglacial plumes modify waters near glacier fronts and increase submarine glacier melt by entraining warm ambient waters at depth. However, ocean observations along Greenland's coastal margins remain biased toward summer months which limits accurate estimation of ocean forcing on glacier retreat and acceleration. Here, we fill a key observational gap in northwest Greenland by describing seasonal hydrographic variation at glacier fronts in Melville Bay using in situ observations from moorings deployed year‐round, CTDs, and profiling floats. We evaluated local and remote forcing using remote sensing and reanalysis data products alongside a high‐resolution ocean model. Analysis of the year‐round hydrographic data revealed consistent above‐sill seasonality in temperature and salinity. The warmest, saltiest waters occurred in spring (April–May) and primed glaciers for enhanced submarine melt in summer when meltwater plumes entrain deep waters. Waters were coldest and freshest in early winter (November–December) after summer melt from sea ice, glacier ice, and icebergs provided cold freshwater along the shelf. Ocean variability was greatest in the summer and fall, coincident with increased freshwater runoff and large wind events before winter sea ice formation. Results increase our mechanistic understanding of Greenland ice‐ocean interactions and enable improvements in ocean model parameterization.

Effects of Mesozooplankton Growth and Reproduction on Plankton and Organic Carbon Dynamics in a Marine Biogeochemical Model

AbstractMarine mesozooplankton play an important role for marine ecosystem functioning and global biogeochemical cycles. Their size structure, varying spatially and temporally, heavily impacts biogeochemical processes and ecosystem services. Mesozooplankton exhibit size changes throughout their life cycle, affecting metabolic rates and functional traits. Despite this variability, many models oversimplify mesozooplankton as a single, unchanging size class, potentially biasing carbon flux estimates. Here, we include mesozooplankton ontogenetic growth and reproduction into a 3‐dimensional global ocean biogeochemical model, PISCES‐MOG, and investigate the subsequent effects on simulated mesozooplankton phenology, plankton distribution, and organic carbon export. Utilizing an ensemble of statistical predictive models calibrated with a global set of observations, we generated monthly climatologies of mesozooplankton biomass to evaluate the simulations of PISCES‐MOG. Our analyses reveal that the model and observation‐based biomass distributions are consistent ( = 0.40, total epipelagic biomass: 137 TgC from observations vs. 232 TgC in the model), with similar seasonality (later bloom as latitude increases poleward). Including ontogenetic growth in the model induced cohort dynamics and variable seasonal dynamics across mesozooplankton size classes and altered the relative contribution of carbon cycling pathways. Younger and smaller mesozooplankton transitioned to microzooplankton in PISCES‐MOG, resulting in a change in particle size distribution, characterized by a decrease in large particulate organic carbon (POC) and an increase in small POC generation. Consequently, carbon export from the surface was reduced by 10%. This study underscores the importance of accounting for ontogenetic growth and reproduction in models, highlighting the interconnectedness between mesozooplankton size, phenology, and their effects on marine carbon cycling.