NEMO on the shelf: assessment of the Iberia–Biscay–Ireland configuration

Maraldi, C.; Chanut, Jérôme; Levier, Bruno; Ayoub, Nadia; Mey, P. De; Reffray, Guillaume; Lyard, Florent; Cailleau, S.; Drévillon, Marie; Fanjul, Enrique Álvarez; Sotillo, Marcos García; Marsaleix, Patrick

doi:10.5194/os-9-745-2013

Cited by 78 publications

(57 citation statements)

References 77 publications

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“…This NEMO2.3 version has already been successfully applied to the IBI (Iberian-BiscayIreland) area (Maraldi et al, 2013). It deals with the addition of high-frequency processes such as tide and the atmospheric pressure forcing.…”

Section: The Nemo Ocean Modelmentioning

confidence: 99%

Evaluation of an operational ocean model configuration at 1/12° spatial resolution for the Indonesian seas (NEMO2.3/INDO12) – Part 1: Ocean physics

et al. 2016

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Abstract. INDO12 is a 1/12 • regional version of the NEMO physical ocean model covering the whole Indonesian EEZ (Exclusive Economic Zone). It has been developed and is now running every week in the framework of the IN-DESO (Infrastructure Development of Space Oceanography) project implemented by the Indonesian Ministry of Marine Affairs and Fisheries.The initial hydrographic conditions as well as openboundary conditions are derived from the operational global ocean forecasting system at 1/4 • operated by Mercator Océan. Atmospheric forcing fields (3-hourly ECMWF (European Centre for Medium-Range Weather Forecast) analyses) are used to force the regional model. INDO12 is also forced by tidal currents and elevations, and by the inverse barometer effect. The turbulent mixing induced by internal tides is taken into account through a specific parameterisation. In this study we evaluate the model skill through comparisons with various data sets including outputs of the parent model, climatologies, in situ temperature and salinity measurements, and satellite data. The biogeochemical model results assessment is presented in a companion paper (Gutknecht et al., 2015).The simulated and altimeter-derived Eddy Kinetic Energy fields display similar patterns and confirm that tides are a dominant forcing in the area. The volume transport of the Indonesian throughflow (ITF) is in good agreement with the INSTANT estimates while the transport through Luzon Strait is, on average, westward but probably too weak. Compared to satellite data, surface salinity and temperature fields display marked biases in the South China Sea. Significant water mass transformation occurs along the main routes of the ITF and compares well with observations. Vertical mixing is able to modify the South and North Pacific subtropical water-salinity maximum as seen in T -S diagrams.In spite of a few weaknesses, INDO12 proves to be able to provide a very realistic simulation of the ocean circulation and water mass transformation through the Indonesian Archipelago. Work is ongoing to reduce or eliminate the remaining problems in the second INDO12 version.

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Section: The Nemo Ocean Modelmentioning

confidence: 99%

Evaluation of an operational ocean model configuration at 1/12° spatial resolution for the Indonesian seas (NEMO2.3/INDO12) – Part 1: Ocean physics

et al. 2016

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“…Adding the flow-dependent Smagorinsky bi-harmonic scheme further reduces the total kinetic energy. In a model of the North Sea at NEMO 1/36°c onfiguration, Maraldi et al (2013) used a smaller biharmonic eddy viscosity of 2.5×10 8 m 4 s −1 to simulate the weaker circulation there. Optimal choice of lateral viscosity needs to be guided by comparisons with observed data.…”

Section: Conclusion and Discussionmentioning

confidence: 99%

High-resolution modeling of the mean flow and meso-scale eddy variability around the Grand Banks of Newfoundland

Zhai

Higginson

et al. 2015

Ocean Dynamics

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The mean flow and meso-scale eddy variability in the region around the Grand Banks of Newfoundland (GBN) are quantified by analyzing surface drifter observations, mean dynamic topography (MDT), along-track satellite altimeter observations, and the solutions of two high-resolution ocean models. By increasing the horizontal resolution from 6.5 km (CREG12) to 2.2 km (GBN36), the modeled mean kinetic energy (MKE) decreases and the eddy kinetic energy (EKE) increases in the study area. GBN36 obtains the MKE of surface geostrophic currents and total currents similar to that derived from MDT and drifter data, whereas CREG12 overestimates these quantities by 40-53 %. CREG12 and GBN36 underestimate the EKE of surface geostrophic currents by 46 and 30 %, respectively, with respect to the EKE derived from along-track altimeter data. The models do not reproduce the strong eddy activity in the Gulf Stream and its downstream region, possibly related to a northward shift of the Gulf Stream position by 0.5°in latitude compared with observations. Both models obtain wavenumber spectra of sea level anomaly in close agreement with the spectrum derived from along-track altimeter data, with a slope of −5 at wavelengths near 100 km on logarithmic spectral density scales.

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“…The friction coefficient was expressed as R = C D u 2 + v 2 + e b , where u and v are the horizontal velocities, C D is the drag coefficient calculated by a logarithmic formulation (Maraldi et al, 2013), and e b is the bottom turbulent kinetic energy due to tides, internal wave breaking and other short timescale currents. Following the Treguier's 1992 experiment and the MFS settings, e b was set to a value of 2.5 × 10 −3 m 2 s −2 (Tréguier, 1992) .…”

Section: Model Settingsmentioning

confidence: 99%

Coastal ocean forecasting with an unstructured grid model in the southern Adriatic and northern Ionian seas

Federico

Pinardi

Coppini

et al. 2017

Nat. Hazards Earth Syst. Sci.

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Abstract. SANIFS (Southern Adriatic Northern Ionian coastal Forecasting System) is a coastal-ocean operational system based on the unstructured grid finite-element threedimensional hydrodynamic SHYFEM model, providing short-term forecasts. The operational chain is based on a downscaling approach starting from the large-scale system for the entire Mediterranean Basin (MFS, Mediterranean Forecasting System), which provides initial and boundary condition fields to the nested system.The model is configured to provide hydrodynamics and active tracer forecasts both in open ocean and coastal waters of southeastern Italy using a variable horizontal resolution from the open sea (3-4 km) to coastal areas (50-500 m).Given that the coastal fields are driven by a combination of both local (also known as coastal) and deep-ocean forcings propagating along the shelf, the performance of SAN-IFS was verified both in forecast and simulation mode, first (i) on the large and shelf-coastal scales by comparing with a large-scale survey CTD (conductivity-temperature-depth) in the Gulf of Taranto and then (ii) on the coastal-harbour scale (Mar Grande of Taranto) by comparison with CTD, ADCP (acoustic doppler current profiler) and tide gauge data.Sensitivity tests were performed on initialization conditions (mainly focused on spin-up procedures) and on surface boundary conditions by assessing the reliability of two alternative datasets at different horizontal resolution (12.5 and 6.5 km).The SANIFS forecasts at a lead time of 1 day were compared with the MFS forecasts, highlighting that SANIFS is able to retain the large-scale dynamics of MFS. The largescale dynamics of MFS are correctly propagated to the shelfcoastal scale, improving the forecast accuracy (+17 % for temperature and +6 % for salinity compared to MFS). Moreover, the added value of SANIFS was assessed on the coastalharbour scale, which is not covered by the coarse resolution of MFS, where the fields forecasted by SANIFS reproduced the observations well (temperature RMSE equal to 0.11 • C).Furthermore, SANIFS simulations were compared with hourly time series of temperature, sea level and velocity measured on the coastal-harbour scale, showing a good agreement. Simulations in the Gulf of Taranto described a circulation mainly characterized by an anticyclonic gyre with the presence of cyclonic vortexes in shelf-coastal areas. A surface water inflow from the open sea to Mar Grande characterizes the coastal-harbour scale.

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NEMO on the shelf: assessment of the Iberia–Biscay–Ireland configuration

Cited by 78 publications

References 77 publications

Evaluation of an operational ocean model configuration at 1/12° spatial resolution for the Indonesian seas (NEMO2.3/INDO12) – Part 1: Ocean physics

Evaluation of an operational ocean model configuration at 1/12° spatial resolution for the Indonesian seas (NEMO2.3/INDO12) – Part 1: Ocean physics

High-resolution modeling of the mean flow and meso-scale eddy variability around the Grand Banks of Newfoundland

Coastal ocean forecasting with an unstructured grid model in the southern Adriatic and northern Ionian seas

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