Nucleus For European Modelling Of The Ocean Research Articles

An overview of the NEMO modelling for the BaySys project

This article is intended as an introduction to discuss the development of a modelling framework to examine simulated climate change and river discharge regulation and their combined impact on marine conditions in the Hudson Bay Complex as a contribution to BaySys, a collaborative project between Manitoba Hydro, Hydro-Quebec, the University of Manitoba, the University of Alberta, Université Laval and Ouranos. In support of this work, a sea ice and oceanographic model was improved and then used to further study the effects of freshwater loading and ice cover on the circulation of Hudson Bay. This modelling perspective is based on the Nucleus for European Modelling of the Ocean (NEMO) ocean general circulation model coupled to version 2 of the Louvain-la-Neuve sea ice model (LIM2). The goal of the modelling was to provide a framework and tool for simulating projected changes in marine state and dynamic variables, while also enabling an integration of observations and numerical analyses. A key aspect of this work was the climate-hydrologic-ocean model integration aspect. The inclusion of a biogeochemical model and explicit tidal forcing to examine the evolution of a Canadian marginal sea with century-long integrations was also a novel aspect of the work. Overall, this work examines the NEMO modelling configuration used in BaySys, how it is set up and the experiments carried out. A broader picture evaluation of the model output is made including the BaySys mooring observations, showing that the modelling framework is suitable to examine the posed questions on the role of climate change and river regulation.

Ensemble analysis and forecast of ecosystem indicators in the North Atlantic using ocean colour observations and prior statistics from a stochastic NEMO–PISCES simulator

Abstract. This study is anchored in the H2020 SEAMLESS project (https://www.seamlessproject.org, last access: 29 January 2024), which aims to develop ensemble assimilation methods to be implemented in Copernicus Marine Service monitoring and forecasting systems, in order to operationally estimate a set of targeted ecosystem indicators in various regions, including uncertainty estimates. In this paper, a simplified approach is introduced to perform a 4D (space–time) ensemble analysis describing the evolution of the ocean ecosystem. An example application is provided, which covers a limited time period in a limited subregion of the North Atlantic (between 31 and 21∘ W, between 44 and 50.5∘ N, between 15 March and 15 June 2019, at a 1/4∘ and a 1 d resolution). The ensemble analysis is based on prior ensemble statistics from a stochastic NEMO (Nucleus for European Modelling of the Ocean)–PISCES simulator. Ocean colour observations are used as constraints to condition the 4D prior probability distribution. As compared to classic data assimilation, the simplification comes from the decoupling between the forward simulation using the complex modelling system and the update of the 4D ensemble to account for the observation constraint. The shortcomings and possible advantages of this approach for biogeochemical applications are discussed in the paper. The results show that it is possible to produce a multivariate ensemble analysis continuous in time and consistent with the observations. Furthermore, we study how the method can be used to extrapolate analyses calculated from past observations into the future. The resulting 4D ensemble statistical forecast is shown to contain valuable information about the evolution of the ecosystem for a few days after the last observation. However, as a result of the short decorrelation timescale in the prior ensemble, the spread of the ensemble forecast increases quickly with time. Throughout the paper, a special emphasis is given to discussing the statistical reliability of the solution. Two different methods have been applied to perform this 4D statistical analysis and forecast: the analysis step of the ensemble transform Kalman filter (with domain localization) and a Monte Carlo Markov chain (MCMC) sampler (with covariance localization), both enhanced by the application of anamorphosis to the original variables. Despite being very different, the two algorithms produce very similar results, thus providing support to each other's estimates. As shown in the paper, the decoupling of the statistical analysis from the dynamical model allows us to restrict the analysis to a few selected variables and, at the same time, to produce estimates of additional ecological indicators (in our example: phenology, trophic efficiency, downward flux of particulate organic matter). This approach can easily be appended to existing operational systems to focus on dedicated users' requirements, at a small additional cost, as long as a reliable prior ensemble simulation is available. It can also serve as a baseline to compare with the dynamical ensemble forecast and as a possible substitute whenever useful.

The Impacts of Air-Sea Fluxes and Model Resolution on Seasonal and Inter-Annual Variability of the Atlantic Meridional Overturning Circulation across the OSNAP West Section

The present study investigates the Atlantic Meridional Overturning Circulation (AMOC) in the sub-polar North Atlantic. Despite the identification of a weaker AMOC across the OSNAP (Overturning in the Subpolar North Atlantic Program) West section, low-resolution models have continuously overestimated the subpolar AMOC link to the Labrador Sea Water mass formation, underscoring the need for a deeper understanding of this process. Nevertheless, strong air-sea gas exchange from the surface to the deep ocean, associated with the ventilation of the subpolar North Atlantic by Labrador Sea Water means the Labrador Sea remains a crucial region to study. To explore the AMOC across OSNAP, we use three configurations of the NEMO (Nucleus for European Modelling of the Ocean) ocean model with varying horizontal and vertical resolutions, including a 1/60th degree Adaptive Grid Refinement In Fortran (AGRIF) nest over the Labrador Sea. The high-resolution configuration best represents the OSNAP estimates of mean AMOC. The modeled mean and seasonal AMOC using the high-resolution configuration are improved by switching to an atmospheric forcing with stronger air-sea heat loss, while showing minimal sensitivity to the Greenland melt freshwater input. The results highlight the impact of the model resolution and representation of atmospheric forcing on the seasonal and interannual variability of subpolar AMOC link to the water mass formation in the Labrador basin.

Subsurface Eddy Detection Optimized with Potential Vorticity from Models in the Arabian Sea

Abstract Coherent ocean vortices, or eddies, are usually tracked on the surface of the ocean. However, tracking subsurface eddies is important for a complete understanding of deep ocean circulation. In this study, we develop an algorithm designed for the detection of subsurface eddies in the Arabian Sea using Nucleus for European Modelling of the Ocean (NEMO) model simulations. We optimize each parameter of our algorithm to achieve favorable results when compared with an algorithm using sea surface height (SSH). When compared to similar methods, we find that using the rescaled isopycnal potential vorticity (PV) is best for subsurface eddy detection. We proceed to demonstrate that our new algorithm can detect eddies successfully between specific isopycnals, such as those that define the Red Sea Water (RSW). In doing so, we showcase how our method can be used to describe the properties of eddies within the RSW and even identify specific long-lived subsurface eddies. We conduct one such case study by discerning the structure of a completely subsurface RSW eddy near the Chagos Archipelago using Lagrangian particle tracking and PV diagnostics. We conclude that our rescaled PV method is an efficient tool for investigating eddy dynamics within the ocean’s interior, and publicly provide our optimization methodology as a way for other researchers to develop their own subsurface detection algorithms with optimized parameters for any spatiotemporal model domain. Significance Statement Eddies are a key part of ocean circulation both at the surface and in the subsurface. The purpose of our study was to design the first detection method comprehensively optimized for subsurface eddy detection from numerical simulations. We demonstrate that potential vorticity (PV) is the best field to use when algorithmically tracking eddies in subsurface water masses, using our new method to identify and track eddies in the Red Sea Water (RSW). Additionally, our method allows us to efficiently evaluate the dynamics of eddies through potential vorticity diagnostics, exemplified with a previously undescribed eddy near the Chagos Archipelago. Our methodology can be used by future researchers to study the eddy dynamics hidden within subsurface water masses around the world.

Analysis of the Model Characteristics in the North Atlantic Simulated by the NEMO Model with Data Assimilation

The main aim of this work is to study the spatial–temporal variability of the model’s physical and spectral characteristics in the process of assimilation of observed ocean surface height data from the AVISO (Archiving, Validating and Interpolation Satellite Observation) archive in combination with the NEMO (Nucleus for European Modeling of the Ocean) ocean circulation model for a period of two months. For data assimilation, the GKF (Generalized Kalman filter) method, previously developed by the authors, is used. The purpose of this work is to study the spatial–temporal structure of the simulated characteristics using decomposition into eigenvalues and eigenvectors (Karhunen–Loeve decomposition method). The feature of the GKF method is the fact that the constructed Kalman weight matrix multiplied by the vector of observational data can be represented as a weighted sum of eigenvectors and eigenvalues (spectral characteristics of the matrix), which describe the spatial and temporal structure of corrections to the model. The main investigations are focused on the North Atlantic. Their variability in time and space is estimated in this study. Calculations of the main ocean characteristics, such as the surface height, temperature, salinity, and the current velocities on the surface and in the depths, both with and without assimilation of observational data, over a time interval of 60 days, were performed by using a high-performance computing system. The calculation results have shown that the main spatial variability of characteristics after data assimilation is consistent with the localization of the currents in the North Atlantic.

Joint observation–model mixed-layer heat and salt budgets in the eastern tropical Atlantic

Abstract. In this study, we use a joint observation–model approach to investigate the mixed-layer heat and salt annual mean as well as seasonal budgets in the eastern tropical Atlantic. The regional PREFCLIM (PREFACE Climatology) observational climatology provides the budget terms with a relatively low spatial and temporal resolution compared to the online NEMO (Nucleus for European Modeling of the Ocean; Madec, G., 2014) model, and this is later resampled as in PREFCLIM climatology. In addition, advection terms are recomputed offline from the model as PREFCLIM gridded advection computation. In the Senegal, Angola, and Benguela regions, the seasonal cycle of mixed-layer temperature is mainly governed by surface heat fluxes; however, it is essentially driven by vertical heat diffusion in the equatorial region. The seasonal cycle of mixed-layer salinity is largely controlled by freshwater flux in the Senegal and Benguela regions; however, it follows the variability of zonal and meridional salt advection in the equatorial and Angola regions, respectively. Our results show that the time-averaged spatial distribution of NEMO offline heat and salt advection terms compares much better to PREFCLIM horizontal advection terms than the online heat and salt advection terms. However, the seasonal cycle of horizontal advection in selected regions shows that NEMO offline terms do not always compare well with PREFCLIM, sometimes less than online terms. Despite this difference, these results suggest the important role of small-scale variability in mixed-layer heat and salt budgets.

Reproducible and relocatable regional ocean modelling: fundamentals and practices

Abstract. In response to an increasing demand for bespoke or tailored regional ocean modelling configurations, we outline fundamental principles and practices that can expedite the process to generate new configurations. The paper develops the principle of reproducibility and advocates adherence by presenting benefits to the community and user. The elements of this principle are reproducible workflows and standardised assessment, with additional effort over existing working practices being balanced against the added value generated. The paper then decomposes the complex build process, for a new regional ocean configuration, into stages and presents guidance, advice and insight for each component. This advice is compiled from across the NEMO (Nucleus for European Modelling of the Ocean) user community and sets out principles and practises that encompass regional ocean modelling with any model. With detailed and region-specific worked examples in Sects. 3 and 4, the linked companion repositories and DOIs all target NEMOv4. The aim of this review and perspective paper is to broaden the user community skill base and to accelerate development of new configurations in order to increase the time available for exploiting the configurations.

Sensitivity of NEMO4.0-SI3 model parameters on sea ice budgets in the Southern Ocean

Abstract. The seasonally dependent Antarctic sea ice concentration (SIC) budget is well observed and synthesizes many important air–sea–ice interaction processes. However, it is rarely well simulated in Earth system models, and means to tune the former are not well understood. In this study, we investigate the sensitivity of 18 key NEMO4.0-SI3 (Nucleus for European Modelling of the Ocean coupled with the Sea Ice Modelling Integrated Initiative) model parameters on modelled SIC and sea ice volume (SIV) budgets in the Southern Ocean based on a total of 449 model runs and two global sensitivity analysis methods. We found that the simulated SIC and SIV budgets are sensitive to ice strength, the thermal conductivity of snow, the number of ice categories, two parameters related to lateral melting, ice–ocean drag coefficient and air–ice drag coefficient. An optimized ice–ocean drag coefficient and air–ice drag coefficient can reduce the root-mean-square error between simulated and observed SIC budgets by about 10 %. This implies that a more accurate calculation of ice velocity is the key to optimizing the SIC budget simulation, which is unlikely to be achieved perfectly by simply tuning the model parameters in the presence of biased atmospheric forcing. Nevertheless, 10 combinations of NEMO4.0-SI3 model parameters were recommended, as they could yield better sea ice extent and SIC budgets than when using the standard values.

Ocean Modeling with Adaptive REsolution (OMARE; version 1.0) – refactoring the NEMO model (version 4.0.1) with the parallel computing framework of JASMIN – Part 1: Adaptive grid refinement in an idealized double-gyre case

Abstract. High-resolution models have become widely available for the study of the ocean's small-scale processes. Although these models simulate more turbulent ocean dynamics and reduce uncertainties of parameterizations, they are not practical for long-term simulations, especially for climate studies. Besides scientific research, there are also growing needs from key applications for multi-resolution, flexible modeling capabilities. In this study we introduce the Ocean Modeling with Adaptive REsolution (OMARE), which is based on refactoring Nucleus for European Modelling of the Ocean (NEMO) with the parallel computing framework of JASMIN (J parallel Adaptive Structured Mesh applications INfrastructure). OMARE supports adaptive mesh refinement (AMR) for the simulation of the multi-scale ocean processes with improved computability. We construct an idealized, double-gyre test case, which simulates a western-boundary current system with seasonally changing atmospheric forcings. This paper (Part 1) focuses on the ocean physics simulated by OMARE at two refinement scenarios: (1) 0.5–0.1∘ static refinement and the transition from laminar to turbulent, eddy-rich ocean, and (2) the short-term 0.1–0.02∘ AMR experiments, which focus on submesoscale processes. Specifically, for the first scenario, we show that the ocean dynamics on the refined, 0.1∘ region is sensitive to the choice of refinement region within the low-resolution, 0.5∘ basin. Furthermore, for the refinement to 0.02∘, we adopt refinement criteria for AMR based on surface velocity and vorticity. Results show that temporally changing features at the ocean's mesoscale, as well as submesoscale process and its seasonality, are captured well through AMR. Related topics and future plans of OMARE, including the upscaling of small-scale processes with AMR, are further discussed for further oceanography studies and applications.

Long-term mean circulation in the Japan Sea as reproduced by multiple eddy-resolving ocean circulation models

The capacity of four eddy-resolving ocean circulation models—HYCOM (HYbrid Coordinate Ocean Model), MRI.COM (Meteorological Research Institute Community Ocean Model), OFES (Ocean General Circulation Model for the Earth Simulator), and NEMO (Nucleus for European Modeling of the Ocean)—to simulate the long-term mean hydrographic conditions and circulation patterns in the Japan Sea is investigated in this study. The assessment of this study includes the evaluation of mean vertical profiles and time series of temperature and salinity at the representative monitoring stations. Different model products from 1993 to 2015 are compared with in situ measurements provided by historical cruises and monitoring stations. After that, we compared the observed and simulated surface current velocities over the basin and volume transports through the key straits in the Japan Sea. Simulated current velocities are validated against 15 years of Acoustic Doppler Current Profiler (ADCP) measurements near the longshore and offshore branches of the East Korea Warm Current (EKWC). Furthermore, the atmospheric forcing data of the four ocean circulation models are validated against the satellite wind product. We found that the vertical profiles and long-term variations of temperature and salinity reproduced by MRI.COM and HYCOM are closer to in situ measurements. All models simulate temperature well in upper ocean, but salinity simulations are of lower quality from OFES and NEMO at several stations. Simulated current velocities predominantly lie within the standard deviation of ADCP measurements at two locations. However, the sea surface currents are underestimated by four models compared with Drifter data. Although simulated hydrographic profiles agree well with in situ observations, the mean circulation patterns greatly differ between the models, which highlight the need for additional evaluation and corrections based on the long-term current measurements. Because of the lack of ocean current measurements, only the baroclinic velocities simulated by each model are reliable. The substantial part of the differences in barotropic velocities among the simulate result of four models is explained by the differing wind velocities from the corresponding atmospheric forcing datasets.

The bulk parameterizations of turbulent air–sea fluxes in NEMO4: the origin of sea surface temperature differences in a global model study

Abstract. Wind stress and turbulent heat fluxes are the major driving forces that modify the ocean dynamics and thermodynamics. In the Nucleus for European Modelling of the Ocean (NEMO) ocean general circulation model, these turbulent air–sea fluxes (TASFs) can critically impact the simulated ocean characteristics. This paper investigates how the various bulk parameterizations used to calculate turbulent air-sea fluxes in NEMOv4 can lead to substantial differences in the estimation of sea surface temperatures (SSTs). Specifically, we study the contributions of different aspects and assumptions of the bulk parameterizations in driving the SST differences in the NEMO global model configuration at 1/4∘ of horizontal resolution. These aspects include the use of the skin temperature instead of the bulk SST in the computation of turbulent heat flux components and the estimation of wind stress and turbulent heat flux components, which vary in each parameterization due to different bulk transfer coefficients. The analysis of a set of short-term sensitivity experiments where the only change is related to one of the aspects of the bulk parameterizations shows that parameterization-related SST differences are primarily sensitive to wind stress differences and to the implementation of skin temperature in the computation of turbulent heat flux components. In addition, in order to highlight the role of SST–turbulent heat flux negative feedback at play in ocean simulations, we compare the TASF differences obtained using the NEMO ocean model with the estimations by Brodeau et al. (2017), who compared the different bulk parameterizations using prescribed SSTs. Our estimations of turbulent heat flux differences between bulk parameterizations are weaker than those found by Brodeau et al. (2017).

Drivers for seasonal variability in sea level around the China seas

Globally variable ocean and atmospheric dynamics lead to spatially complex seasonal cycles in sea level. The China Seas, that is the Bohai, Yellow, East China and the South China seas, is a region with strong seasonal amplitudes, and straddles the transition between tropical and temperature zones, monsoonal and westerlies, shelf and deep ocean zones. Here we investigate the drivers for seasonal variability in sea level from tide gauge records, satellite altimetry along with output from the NEMO (Nucleus for European Modeling of the Ocean) model including sea surface height and ocean bottom pressure along with meteorological data in the China Seas. The seasonal cycle accounts for 37% - 94% of monthly sea level variability in 81 tide gauge records, ranging from 18 to 59 cm. We divided the seasonal cycles into four types: 1) an asymmetric sinusoid; 2) a clearly defined peak on a flat background; 3) a relatively flat signal; 4) a symmetric co-sinusoid. Type 1 is found in northern China and Taiwan, Korea, Japan and The Philippines where Inverse Barometer (IB) effects dominates seasonality along with a steric contribution. The seasonal monsoon associated with barotropic response and freshwater exchange play important roles in type 2, (eastern and southern Chinese coasts), type 3 (East Malaysia) and type 4 (Vietnam and Gulf of Thailand). IB corrected seasonal cycle amplitudes are larger in continental shelf areas than the deep ocean, with a maximum in the Gulf of Thailand, and NEMO underestimates the seasonal amplitude along the coast by nearly 50%.

A new global ocean ensemble system at the Met Office: Assessing the impact of hybrid data assimilation and inflation settings

AbstractWe have developed a global ocean and sea‐ice ensemble forecasting system based on the operational forecasting ocean assimilation model (FOAM) system run at the Met Office. The ocean model Nucleus for European Modelling of the Ocean (NEMO) and the community ice code (CICE) sea‐ice model are run at 1/4 resolution and the system assimilates data using a three‐dimensional variational assimilation (3DVar) version of NEMOVAR. This data assimilation (DA) system can perform hybrid ensemble/variational assimilation. A 36‐member ensemble of hybrid ensemble variational assimilation systems with perturbed observations (values and locations) has been set up, with each member forced at the surface by a separate member of the Met Office Global–Regional Ensemble Prediction System (MOGREPS‐G). The unperturbed member is forced by atmospheric fields from the Met Office operational numerical weather prediction (NWP) deterministic system. The system includes stochastic model perturbations and a relaxation to prior spread (RTPS) inflation scheme. A control run of the system using an ensemble of 3DVars is shown to be generally reliable for Sea‐Level Anomaly (SLA), temperature, and salinity (the ensemble spread being a good representation of the uncertainty in the ensemble mean), although the ensemble is underspread in eddying regions. The ensemble mean gives a 4% reduction in error in SLA compared with the deterministic 3DVar system currently used operationally. The system was tested with different weights for the ensemble component of the hybrid background‐error covariance matrix and different inflation factors. The best results, in terms of short‐range forecast error and ensemble reliability statistics, were obtained with hybrid three‐dimensional ensemble variational DA (3DEnVar). The RTPS inflation scheme is shown to be beneficial in producing an appropriate ensemble spread in response to hybrid DA. 3DEnVar with an ensemble hybrid weight of 0.8 leads to a reduction of 20% (5%) in the ensemble mean error for SLA (profile temperature and salinity) compared with an ensemble of standard 3DVars.

IBI-CCS: a regional high-resolution model to simulate sea level in western Europe

Abstract. Projections of coastal sea level (SL) changes are of great interest for coastal risk assessment and decision making. SL projections are typically produced using global climate models (GCMs), which cannot fully resolve SL changes at the coast due to their coarse resolution and lack of representation of some relevant processes (tides, atmospheric surface pressure forcing, waves). To overcome these limitations and refine projections at regional scales, GCMs can be dynamically downscaled through the implementation of a high-resolution regional climate model (RCM). In this study, we developed the IBI-CCS (Iberian–Biscay–Ireland Climate Change Scenarios) regional ocean model based on a 1/12∘ northeastern Atlantic Nucleus for European Modelling of the Ocean (NEMO) model configuration to dynamically downscale CNRM-CM6-1-HR, a GCM with a 1/4∘ resolution ocean model component participating in the sixth phase of the Coupled Model Intercomparison Project (CMIP6) by the Centre National de Recherches Météorologiques (CNRM). For a more complete representation of the processes driving coastal SL changes, tides and atmospheric surface pressure forcing are explicitly resolved in IBI-CCS in addition to the ocean general circulation. To limit the propagation of climate drifts and biases from the GCM into the regional simulations, several corrections are applied to the GCM fields used to force the RCM. The regional simulations are performed over the 1950 to 2100 period for two climate change scenarios (SSP1-2.6 and SSP5-8.5). To validate the dynamical downscaling method, the RCM and GCM simulations are compared to reanalyses and observations over the 1993–2014 period for a selection of ocean variables including SL. Results indicate that large-scale performance of IBI-CCS is better than that of the GCM thanks to the corrections applied to the RCM. Extreme SLs are also satisfactorily represented in the IBI-CCS historical simulation. Comparison of the RCM and GCM 21st century projections shows a limited impact of increased resolution (1/4 to 1/12∘) on SL changes. Overall, bias corrections have a moderate impact on projected coastal SL changes, except in the Mediterranean Sea, where GCM biases were substantial.

NEMO-Bohai 1.0: a high-resolution ocean and sea ice modelling system for the Bohai Sea, China

Abstract. Severe ice conditions in the Bohai Sea could cause serious harm to maritime traffic, offshore oil exploitation, aquaculture, and other economic activities in the surrounding regions. In addition to providing sea ice forecasts for disaster prevention and risk mitigation, sea ice numerical models could help explain the sea ice variability within the context of climate change in marine ecosystems, such as spotted seals, which are the only ice-dependent animal that breeds in Chinese waters. Here, we developed NEMO-Bohai, an ocean–ice coupled model based on the Nucleus for European Modelling of the Ocean (NEMO) model version 4.0 and Sea Ice Modelling Integrated Initiative (SI3) (NEMO4.0-SI3) for the Bohai Sea. This study will present the scientific design and technical choices of the parameterizations for the NEMO-Bohai model. The model was calibrated and evaluated with in situ and satellite observations of the ocean and sea ice. The model simulations agree with the observations with respect to sea surface height (SSH), temperature (SST), salinity (SSS), currents, and temperature and salinity stratification. The seasonal variation of the sea ice area is well simulated by the model compared to the satellite remote sensing data for the period of 1996–2017. Overall agreement is found for the occurrence dates of the annual maximum sea ice area. The simulated sea ice thickness and volume are in general agreement with the observations with slight overestimations. NEMO-Bohai can simulate seasonal sea ice evolution and long-term interannual variations. Hence, NEMO-Bohai is a valuable tool for long-term ocean and ice simulations and climate change studies.

PARASO, a circum-Antarctic fully coupled ice-sheet–ocean–sea-ice–atmosphere–land model involving f.ETISh1.7, NEMO3.6, LIM3.6, COSMO5.0 and CLM4.5

Abstract. We introduce PARASO, a novel five-component fully coupled regional climate model over an Antarctic circumpolar domain covering the full Southern Ocean. The state-of-the-art models used are the fast Elementary Thermomechanical Ice Sheet model (f.ETISh) v1.7 (ice sheet), the Nucleus for European Modelling of the Ocean (NEMO) v3.6 (ocean), the Louvain-la-Neuve sea-ice model (LIM) v3.6 (sea ice), the COnsortium for Small-scale MOdeling (COSMO) model v5.0 (atmosphere) and its CLimate Mode (CLM) v4.5 (land), which are here run at a horizontal resolution close to 1/4∘. One key feature of this tool resides in a novel two-way coupling interface for representing ocean–ice-sheet interactions, through explicitly resolved ice-shelf cavities. The impact of atmospheric processes on the Antarctic ice sheet is also conveyed through computed COSMO-CLM–f.ETISh surface mass exchange. In this technical paper, we briefly introduce each model's configuration and document the developments that were carried out in order to establish PARASO. The new offline-based NEMO–f.ETISh coupling interface is thoroughly described. Our developments also include a new surface tiling approach to combine open-ocean and sea-ice-covered cells within COSMO, which was required to make this model relevant in the context of coupled simulations in polar regions. We present results from a 2000–2001 coupled 2-year experiment. PARASO is numerically stable and fully operational. The 2-year simulation conducted without fine tuning of the model reproduced the main expected features, although remaining systematic biases provide perspectives for further adjustment and development.

Correction of the model dynamics for the Northern seas using observational altimetry data

The earlier derived data assimilation method called Generalized Kalman filter (GKF) is applied in conjunction with the Nucleus for European Modelling of the Ocean (NEMO) circulation model to the calculation of the dynamics in the North Seas of Russia. By assimilating the satellite altimetry data from archive AVISO (Archiving, validating and interpolating of satellite observations) this method corrects the direct model calculations and improves the ocean state. The model fields, in particular, sea level and sea surface temperature with and without assimilation are constructed and compared with each other. The brief analysis of the results is also performed.

High-Resolution Reanalysis of the Mediterranean Sea Biogeochemistry (1999–2019)

Ocean reanalyses integrate models and observations to provide a continuous and consistent reconstruction of the past physical and biogeochemical ocean states and variability. We present a reanalysis of the Mediterranean Sea biogeochemistry at a 1/24° resolution developed within the Copernicus Marine Environment Monitoring Service (CMEMS) framework. The reanalysis is based on the Biogeochemical Flux Model (BFM) coupled with a variational data assimilation scheme (3DVarBio) and forced by the Nucleus for European Modeling of the Ocean (NEMO)–OceanVar physical reanalysis and European Centre for medium-range weather forecasts (ECMWF) reanalysis ERA5 atmospheric fields. Covering the 1999–2019 period with daily means of 12 published and validated biogeochemical state variables, the reanalysis assimilates surface chlorophyll data and integrates EMODnet data as initial conditions, in addition to considering World Ocean Atlas data at the Atlantic boundary, CO2 atmospheric observations, and yearly estimates of riverine nutrient inputs. With the use of multiple observation sources (remote, in situ, and BGC-Argo), the quality of the biogeochemical reanalysis is qualitatively and quantitatively assessed at three validation levels including the evaluation of 12 state variables and fluxes and several process-oriented metrics. The results indicate an overall good reanalysis skill in simulating basin-wide values and variability in the biogeochemical variables. The uncertainty in reproducing observations at the mesoscale and weekly temporal scale is satisfactory for chlorophyll, nutrient, oxygen, and carbonate system variables in the epipelagic layers, whereas the uncertainty increases for a few variables (i.e., oxygen and ammonium) in the mesopelagic layers. The vertical dynamics of phytoplankton and nitrate are positively evaluated with specific metrics using BGC-Argo data. As a consequence of the continuous increases in temperature and salinity documented in the Mediterranean Sea over the last 20 years and atmospheric CO2 invasion, we observe basin-wide biogeochemical signals indicating surface deoxygenation, increases in alkalinity, and dissolved inorganic carbon concentrations, and decreases in pH at the surface. The new, high-resolution reanalysis, open and freely available from the Copernicus Marine Service, allows users from different communities to investigate the spatial and temporal variability in 12 biogeochemical variables and fluxes at different scales (from the mesoscale to the basin-wide scale and from daily to multiyear scales) and the interaction between physical and biogeochemical processes shaping Mediterranean marine ecosystem functioning.

A High Resolution Reanalysis for the Mediterranean Sea

In order to be able to forecast the weather and estimate future climate changes in the ocean, it is crucial to understand the past and the mechanisms responsible for the ocean variability. This is particularly true in a complex area such as the Mediterranean Sea with diverse dynamics like deep convection and overturning circulation. To this end, effective tools are ocean reanalyses or reconstructions of the past ocean state. Here we present a new physical reanalysis of the Mediterranean Sea at high resolution, developed in the Copernicus Marine Environment Monitoring Service (CMEMS) framework. The hydrodynamic model is based on the Nucleus for European Modelling of the Ocean (NEMO) combined with a variational data assimilation scheme (OceanVar). The model has a horizontal resolution of 1/24° and 141 unevenly distributed vertical z* levels. It provides daily and monthly temperature, salinity, current, sea level and mixed layer depth as well as hourly fields for surface velocities and sea level. ECMWF ERA-5 atmospheric fields force the model and daily boundary conditions in the Atlantic are taken from a global reanalysis. The reanalysis covers the 33 years from 1987 to 2019. Initialized from SeaDataNet climatology in January 1985, it reaches a nominal state after a 2-years spin-up. In-situ data from CTD, ARGO floats and XBT are assimilated into the model in combination with satellite altimetry observations. This reanalysis has been validated and assessed through comparison to in-situ and satellite observations as well as literature climatologies. The results show an overall improvement of the comparison with observations and a better representation of the main dynamics of the region compared to a previous, lower resolution (1/16°), reanalysis. Temperature and salinity RMSD are decreased by respectively 14 and 18%. The salinity biases at depth of the previous version are corrected. Climate signals show continuous increase of the temperature and salinity, confirming estimates from observations and other reanalysis. The new reanalysis will allow the study of physical processes at multi-scales, from the large scale to the transient small mesoscale structures and the selection of climate indicators for the basin.

Creation of a global tide analysis dataset: Application of NEMO and an offline objective analysis scheme

ABSTRACT The accurate prediction of tides is vital for the operation of many industries, early warning of coastal flooding and scientific understanding of ocean processes. In this paper, we describe the creation method of a global dataset of tidal harmonics using NEMO (Nucleus for European Modelling of the Ocean) for the first time and an offline objective analysis scheme. Data are assimilated as part of a post-processing step, reducing the computational resources required. A reduced ensemble of tidal harmonics is generated, where each member is run for a shorter period of time than a central background state. This ensemble is used to estimate a single background covariance state, which is used for analysis. Output is validated using an ensemble of objective analyses. For each ensemble member, random selections of observations are omitted and validation is performed at these locations. Improvements in both Mean Absolute Error (MAE) and correlation coefficients () are seen across all 6 of the largest diurnal and semi-diurnal constituents. MAEs in amplitude and phase are reduced by up to and , respectively, and correlations by as much as 0.14. In addition, the majority of locations (between 70 and 80%) see significant improvement.