A high-resolution ocean and sea-ice modelling system for the Arctic and North Atlantic oceans

Dupont, Frédéric; Higginson, Simon; Bourdallé‐Badie, Romain; Lu, Youyu; Roy, François; Smith, G. C. Moore; Lemieux, Jean‐François; Garric, Gilles; Davidson, Fraser

doi:10.5194/gmd-8-1577-2015

Cited by 73 publications

(85 citation statements)

References 73 publications

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“…2d). The too strong intensity of the modelled sea ice velocity was already shown with NEMO3.1-LIM2 (Dupont et al, 2015). However, the model captures the seasonality of drift speed with higher values in summer, when concentration and thickness are the lowest, and lower values in winter, when concentration and thickness are high.…”

Section: Model Evaluationmentioning

confidence: 99%

Relationships between Arctic sea ice drift and strength modelled by NEMO-LIM3.6

et al. 2017

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Abstract. Sea ice cover and thickness have substantially decreased in the Arctic Ocean since the beginning of the satellite era. As a result, sea ice strength has been reduced, allowing more deformation and fracturing and leading to increased sea ice drift speed. We use the version 3.6 of the global ocean-sea ice NEMO-LIM model (Nucleus for European Modelling of the Ocean coupled to the Louvain-laNeuve sea Ice Model), satellite, buoy and submarine observations, as well as reanalysis data over the period from 1979 to 2013 to study these relationships. Overall, the model agrees well with observations in terms of sea ice extent, concentration and thickness. The seasonal cycle of sea ice drift speed is reasonably well reproduced by the model. NEMO-LIM3.6 is able to capture the relationships between the seasonal cycles of sea ice drift speed, concentration and thickness, with higher drift speed for both lower concentration and lower thickness, in agreement with observations. Model experiments are carried out to test the sensitivity of Arctic sea ice drift speed, thickness and concentration to changes in sea ice strength parameter P * . These show that higher values of P * generally lead to lower sea ice deformation and lower sea ice thickness, and that no single value of P * is the best option for reproducing the observed drift speed and thickness. The methodology proposed in this analysis provides a benchmark for a further model intercomparison related to the relationships between sea ice drift speed and strength, which is especially relevant in the context of the upcoming Coupled Model Intercomparison Project 6 (CMIP6).

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Section: Model Evaluationmentioning

confidence: 99%

Relationships between Arctic sea ice drift and strength modelled by NEMO-LIM3.6

et al. 2017

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“…During the last decade, an extensive effort has been made to simulate eddying ocean, and different models have been implemented in regional, near-global, and fully global domains (e.g. Maltrud and McClean, 2005;Chassignet et al, 2009;Oke et al, 2013;Drakkar Group, 2014;Metzger et al, 2014;Dupont et al, 2015). In this context, we developed a global eddying configuration, where eddying means that the numerical simulation is eddy-resolving in the majority of deep ocean regions, while it is mostly eddy-permitting on the continental shelves or in weakly stratified polar latitudes.…”

Section: Introductionmentioning

confidence: 99%

A 1/16° eddying simulation of the global NEMO sea-ice–ocean system

et al. 2016

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Abstract. Analysis of a global eddy-resolving simulation using the NEMO general circulation model is presented. The model has 1/16 • horizontal spacing at the Equator, employs two displaced poles in the Northern Hemisphere, and uses 98 vertical levels. The simulation was spun up from rest and integrated for 11 model years, using ERA-Interim reanalysis as surface forcing. Primary intent of this hindcast is to test how the model represents upper ocean characteristics and sea ice properties.Analysis of the zonal averaged temperature and salinity, and the mixed layer depth indicate that the model average state is in good agreement with observed fields and that the model successfully represents the variability in the upper ocean and at intermediate depths. Comparisons against observational estimates of mass transports through key straits indicate that most aspects of the model circulation are realistic. As expected, the simulation exhibits turbulent behaviour and the spatial distribution of the sea surface height (SSH) variability from the model is close to the observed pattern. The distribution and volume of the sea ice are, to a large extent, comparable to observed values.Compared with a corresponding eddy-permitting configuration, the performance of the model is significantly improved: reduced temperature and salinity biases, in particular at intermediate depths, improved mass and heat transports, better representation of fluxes through narrow and shallow straits, and increased global-mean eddy kinetic energy (by ∼ 40 %). However, relatively minor weaknesses still exist such as a lower than observed magnitude of the SSH variability. We conclude that the model output is suitable for broader analysis to better understand upper ocean dynamics and ocean variability at global scales. This simulation represents a major step forward in the global ocean modelling at the Euro-Mediterranean Centre on Climate Change and constitutes the groundwork for future applications to short-range ocean forecasting.

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“…The relaxation timescales were set to 1 day for inflow and 15 days for outflow. These values are identical to those used in Dupont et al (2015), but differ from the original NAA configuration (Hu and Myers, 2013). Our preliminary experiments suggested that these changes were needed to prevent salinity drift.…”

Section: Initial and Lateral Boundary Conditions Runoff And Atmosphmentioning

confidence: 65%

CSIB v1: a sea-ice biogeochemical model for the NEMO community ocean modelling framework

Hayashida

Christian

Holdsworth

et al. 2018

Preprint

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Abstract. Numerical models are a useful tool for studying marine ecosystems and associated biogeochemical processes in icecovered regions where observations are scarce. To this end, CSIB v1 (Canadian Sea-ice Biogeochemistry version 1), a new seaice biogeochemical model has been developed and embedded into the Nucleus for European Modelling of the Ocean (NEMO) modelling system. This model consists of a three-compartment (ice algae, nitrate, and ammonium) sea-ice ecosystem and a twocompartment (dimethylsulfoniopropionate and dimethylsulfide) sea-ice sulfur cycle which are coupled to pelagic ecosystem 5 and sulfur-cycle models at the sea ice-ocean interface. In addition to biological and chemical sources and sinks, the model simulates the horizontal transport of biogeochemical state variables within sea ice through a one-way coupling to a dynamicthermodynamic sea-ice model (LIM2). This paper describes technical aspects of implementing sea-ice biogeochemistry into NEMO and provides discussion on the results of several model experiments. Results of the reference simulation were evaluated by comparing the model outputs to observations and previous modelling studies. Additional simulations were conducted to 10 assess the model sensitivity to 1) the temporal resolution of the snowfall forcing data, 2) the representation of light penetration through snow, 3) advective and eddy-diffusive horizontal transport of sea-ice biogeochemical state variables, and 4) light attenuation by ice algae. The sea-ice biogeochemical model has been developed within the generic framework of NEMO to facilitate its use within different configurations and domains, and can be adapted for use with other NEMO-based submodels such as LIM3 and PISCES.

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A high-resolution ocean and sea-ice modelling system for the Arctic and North Atlantic oceans

Cited by 73 publications

References 73 publications

Relationships between Arctic sea ice drift and strength modelled by NEMO-LIM3.6

Relationships between Arctic sea ice drift and strength modelled by NEMO-LIM3.6

A 1/16° eddying simulation of the global NEMO sea-ice–ocean system

CSIB v1: a sea-ice biogeochemical model for the NEMO community ocean modelling framework

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