Articles | Volume 8, issue 10
https://doi.org/10.5194/gmd-8-3071-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/gmd-8-3071-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Model description paper
| Highlight paper
| 
06 Oct 2015
Model description paper | Highlight paper |
| 06 Oct 2015
ECCO version 4: an integrated framework for non-linear inverse modeling and global ocean state estimation
G. Forget
CORRESPONDING AUTHOR
Dept. of Earth, Atmospheric and Planetary Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
J.-M. Campin
Dept. of Earth, Atmospheric and Planetary Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
P. Heimbach
Dept. of Earth, Atmospheric and Planetary Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
Institute for Computational Engineering and Sciences, The University of Texas at Austin, Austin, TX 78712, USA
Jackson School of Geosciences, The University of Texas at Austin, Austin, TX 78712, USA
C. N. Hill
Dept. of Earth, Atmospheric and Planetary Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
R. M. Ponte
Atmospheric and Environmental Research, Inc., Lexington, MA 02421, USA
C. Wunsch
Dept. of Earth and Planetary Sciences, Harvard University, Cambridge, MA 02139, USA
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While biogeochemical models and satellite-derived ocean color data provide unprecedented information, it is problematic to compare them. Here, we present a new approach based on comparing probability density distributions of model and satellite properties to assess model skills. We also introduce Earth mover's distances as a novel and powerful metric to quantify the misfit between models and observations. We find that how 3D chlorophyll fields are aggregated can be a significant source of error.
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The Green's functions methodology offers a systematic, easy-to-implement, computationally cheap, scalable, and extendable method to tune uncertain parameters in models accounting for the dependent response of the model to a change in various parameters. Herein, we successfully show for the first time that long-term errors in earth system models can be considerably reduced using Green's functions methodology. The method can be easily applied to any model containing uncertain parameters.
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G. Forget, D. Ferreira, and X. Liang
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Results from the ECCO v4 ocean state estimate identify the constraint of fitting Argo profiles as an effective observational basis for inverse estimation of regional turbulent transport rates. The estimated parameters' geography is physically plausible and exhibits close connections with the observed upper-ocean stratification. They yield a clear reduction in the model drift away from observations over multi-century-long simulations, including for independent biochemistry variables.
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Data assimilation methods that couple observations with dynamical models are essential for understanding climate change. Here,
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Bror F. Jönsson, Christopher L. Follett, Jacob Bien, Stephanie Dutkiewicz, Sangwon Hyun, Gemma Kulk, Gael L. Forget, Christian Müller, Marie-Fanny Racault, Christopher N. Hill, Thomas Jackson, and Shubha Sathyendranath
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While biogeochemical models and satellite-derived ocean color data provide unprecedented information, it is problematic to compare them. Here, we present a new approach based on comparing probability density distributions of model and satellite properties to assess model skills. We also introduce Earth mover's distances as a novel and powerful metric to quantify the misfit between models and observations. We find that how 3D chlorophyll fields are aggregated can be a significant source of error.
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Ocean Sci., 18, 953–978, https://doi.org/10.5194/os-18-953-2022, https://doi.org/10.5194/os-18-953-2022, 2022
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In 2015, record low temperatures were observed in the North Atlantic. Using an ocean model, we show that surface heat loss in December 2013 caused 75 % of the initial cooling before this "cold blob" was trapped below the surface. The following summer, the cold blob re-emerged due to a strong temperature difference between the surface ocean and below, driving vertical diffusion of heat. Lower than average surface warming then led to the coldest temperature anomalies in August 2015.
Ehud Strobach, Andrea Molod, Donifan Barahona, Atanas Trayanov, Dimitris Menemenlis, and Gael Forget
Geosci. Model Dev., 15, 2309–2324, https://doi.org/10.5194/gmd-15-2309-2022, https://doi.org/10.5194/gmd-15-2309-2022, 2022
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The Green's functions methodology offers a systematic, easy-to-implement, computationally cheap, scalable, and extendable method to tune uncertain parameters in models accounting for the dependent response of the model to a change in various parameters. Herein, we successfully show for the first time that long-term errors in earth system models can be considerably reduced using Green's functions methodology. The method can be easily applied to any model containing uncertain parameters.
Carl Wunsch
Ocean Sci. Discuss., https://doi.org/10.5194/os-2021-113, https://doi.org/10.5194/os-2021-113, 2021
Preprint withdrawn
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Combinations of observations with dynamical, chemical, etc, models are essential tools for understanding of climate change. By "climate" is meant all of the sub-elements including ocean, atmosphere, ice, et al. A common form of combination arises from sequential estimation theory, a methodology susceptible to a variety of errors that can accumulate through time for long records. Using two simple analogues, many of these errors are identified here, with suggestions for accommodating them.
Axel Peytavin, Bruno Sainte-Rose, Gael Forget, and Jean-Michel Campin
Geosci. Model Dev., 14, 4769–4780, https://doi.org/10.5194/gmd-14-4769-2021, https://doi.org/10.5194/gmd-14-4769-2021, 2021
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Carl Wunsch
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C. G. Piecuch and R. M. Ponte
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Sylvain Cailleau, Laurent Bessières, Léonel Chiendje, Flavie Dubost, Guillaume Reffray, Jean-Michel Lellouche, Simon van Gennip, Charly Régnier, Marie Drevillon, Marc Tressol, Matthieu Clavier, Julien Temple-Boyer, and Léo Berline
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In order to improve Sargassum drift forecasting in the Caribbean area, drift models can be forced by higher-resolution ocean currents. To this goal a 3 km resolution regional ocean model has been developed. Its assessment is presented with a particular focus on the reproduction of fine structures representing key features of the Caribbean region dynamics and Sargassum transport. The simulated propagation of a North Brazil Current eddy and its dissipation was found to be quite realistic.
Gaetano Porcile, Anne-Claire Bennis, Martial Boutet, Sophie Le Bot, Franck Dumas, and Swen Jullien
Geosci. Model Dev., 17, 2829–2853, https://doi.org/10.5194/gmd-17-2829-2024, https://doi.org/10.5194/gmd-17-2829-2024, 2024
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Here a new method of modelling the interaction between ocean currents and waves is presented. We developed an advanced coupling of two models, one for ocean currents and one for waves. In previous couplings, some wave-related calculations were based on simplified assumptions. Our method uses more complex calculations to better represent wave–current interactions. We tested it in a macro-tidal coastal area and found that it significantly improves the model accuracy, especially during storms.
Colette Gabrielle Kerry, Moninya Roughan, Shane Keating, David Gwyther, Gary Brassington, Adil Siripatana, and Joao Marcos A. C. Souza
Geosci. Model Dev., 17, 2359–2386, https://doi.org/10.5194/gmd-17-2359-2024, https://doi.org/10.5194/gmd-17-2359-2024, 2024
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Ocean forecasting relies on the combination of numerical models and ocean observations through data assimilation (DA). Here we assess the performance of two DA systems in a dynamic western boundary current, the East Australian Current, across a common modelling and observational framework. We show that the more advanced, time-dependent method outperforms the time-independent method for forecast horizons of 5 d. This advocates the use of advanced methods for highly variable oceanic regions.
Ivan Hernandez, Leidy M. Castro-Rosero, Manuel Espino, and Jose M. Alsina Torrent
Geosci. Model Dev., 17, 2221–2245, https://doi.org/10.5194/gmd-17-2221-2024, https://doi.org/10.5194/gmd-17-2221-2024, 2024
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The LOCATE numerical model was developed to conduct Lagrangian simulations of the transport and dispersion of marine debris at coastal scales. High-resolution hydrodynamic data and a beaching module that used particle distance to the shore for land–water boundary detection were used on a realistic debris discharge scenario comparing hydrodynamic data at various resolutions. Coastal processes and complex geometric structures were resolved when using nested grids and distance-to-shore beaching.
Adrien Garinet, Marine Herrmann, Patrick Marsaleix, and Juliette Pénicaud
EGUsphere, https://doi.org/10.5194/egusphere-2024-613, https://doi.org/10.5194/egusphere-2024-613, 2024
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Mixing is a crucial aspect of the ocean, but its accurate representation in computer simulations is made challenging by errors that result in unwanted mixing and compromise their realism. We illustrate here the spurious effect that tides can have on simulations of South East Asia. Although they play an important role in setting the state of the ocean, they can increase numerical errors and make simulation outputs less realistic. The paper also provides insights on how to reduce these errors.
Ngoc B. Trinh, Marine Herrmann, Caroline Ulses, Patrick Marsaleix, Thomas Duhaut, Thai To Duy, Claude Estournel, and R. Kipp Shearman
Geosci. Model Dev., 17, 1831–1867, https://doi.org/10.5194/gmd-17-1831-2024, https://doi.org/10.5194/gmd-17-1831-2024, 2024
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A high-resolution model was built to study the South China Sea (SCS) water, heat, and salt budgets. Model performance is demonstrated by comparison with observations and simulations. Important discards are observed if calculating offline, instead of online, lateral inflows and outflows of water, heat, and salt. The SCS mainly receives water from the Luzon Strait and releases it through the Mindoro, Taiwan, and Karimata straits. SCS surface interocean water exchanges are driven by monsoon winds.
Louis Thiry, Long Li, Guillaume Roullet, and Etienne Mémin
Geosci. Model Dev., 17, 1749–1764, https://doi.org/10.5194/gmd-17-1749-2024, https://doi.org/10.5194/gmd-17-1749-2024, 2024
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We present a new way of solving the quasi-geostrophic (QG) equations, a simple set of equations describing ocean dynamics. Our method is solely based on the numerical methods used to solve the equations and requires no parameter tuning. Moreover, it can handle non-rectangular geometries, opening the way to study QG equations on realistic domains. We release a PyTorch implementation to ease future machine-learning developments on top of the presented method.
Zheqi Shen, Yihao Chen, Xiaojing Li, and Xunshu Song
Geosci. Model Dev., 17, 1651–1665, https://doi.org/10.5194/gmd-17-1651-2024, https://doi.org/10.5194/gmd-17-1651-2024, 2024
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Parameter estimation is the process that optimizes model parameters using observations, which could reduce model errors and improve forecasting. In this study, we conducted parameter estimation experiments using the CESM and the ensemble adjustment Kalman filter. The obtained initial conditions and parameters are used to perform ensemble forecast experiments for ENSO forecasting. The results revealed that parameter estimation could reduce analysis errors and improve ENSO forecast skills.
Ali Abdolali, Saeideh Banihashemi, Jose Henrique Alves, Aron Roland, Tyler J. Hesser, Mary Anderson Bryant, and Jane McKee Smith
Geosci. Model Dev., 17, 1023–1039, https://doi.org/10.5194/gmd-17-1023-2024, https://doi.org/10.5194/gmd-17-1023-2024, 2024
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This article presents an overview of the development and implementation of Great Lake Wave Unstructured (GLWUv2.0), including the core model and workflow design and development. The validation was conducted against in situ data for the re-forecasted duration for summer and wintertime (ice season). The article describes the limitations and challenges encountered in the operational environment and the path forward for the next generation of wave forecast systems in enclosed basins like the GL.
Jan De Rydt, Nicolas C. Jourdain, Yoshihiro Nakayama, Mathias van Caspel, Ralph Timmermann, Pierre Mathiot, Xylar S. Asay-Davis, Hélène Seroussi, Pierre Dutrieux, Ben Galton-Fenzi, David Holland, and Ronja Reese
EGUsphere, https://doi.org/10.5194/egusphere-2024-95, https://doi.org/10.5194/egusphere-2024-95, 2024
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Global climate models do not reliably simulate sea-level change arising from ice sheet-ocean interactions. We propose a community modelling effort to conduct a series of well-defined experiments to compare models with observations, and study how models respond to a range of perturbations in climate and ice-sheet geometry. The 2nd Marine Ice Sheet Ocean Model Intercomparison Project, will continue to lay the groundwork for including ice sheet-ocean interactions in global scale, IPCC class models.
Qiang Wang, Qi Shu, Alexandra Bozec, Eric P. Chassignet, Pier Giuseppe Fogli, Baylor Fox-Kemper, Andy McC. Hogg, Doroteaciro Iovino, Andrew E. Kiss, Nikolay Koldunov, Julien Le Sommer, Yiwen Li, Pengfei Lin, Hailong Liu, Igor Polyakov, Patrick Scholz, Dmitry Sidorenko, Shizhu Wang, and Xiaobiao Xu
Geosci. Model Dev., 17, 347–379, https://doi.org/10.5194/gmd-17-347-2024, https://doi.org/10.5194/gmd-17-347-2024, 2024
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Increasing resolution improves model skills in simulating the Arctic Ocean, but other factors such as parameterizations and numerics are at least of the same importance for obtaining reliable simulations.
Mohamed Ayache, Jean-Claude Dutay, Anne Mouchet, Kazuyo Tachikawa, Camille Risi, and Gilles Ramstein
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-237, https://doi.org/10.5194/gmd-2023-237, 2024
Revised manuscript accepted for GMD
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Water isotopes (δ18O, δD) are one of the most widely used proxies in ocean climate research. Previous studies using water isotope observations and modelling have highlighted the importance of understanding spatial and temporal isotopic variability for a quantitative interpretation of these tracers. Here we present the first results of a high-resolution regional dynamical model (at 1/12° horizontal resolution) developed for the Mediterranean Sea, one of the hotspots of ongoing climate change.
Qian Wang, Fei Chai, Yang Zhang, Yinglong Joseph Zhang, and Lorenzo Zampieri
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-236, https://doi.org/10.5194/gmd-2023-236, 2024
Revised manuscript accepted for GMD
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We coupled an unstructured hydro model with an advanced column sea ice model to meet the growing demand for increased resolution and complexity in unstructured sea ice models. Additionally, we present a novel tracer transport scheme for the sea ice coupled model, and demonstrate that this scheme fulfills the requirements for conservation, accuracy, efficiency, and monotonicity in an idealized test. Our new coupled model also has good performance in realistic tests.
Andrew C. Ross, Charles A. Stock, Alistair Adcroft, Enrique Curchitser, Robert Hallberg, Matthew J. Harrison, Katherine Hedstrom, Niki Zadeh, Michael Alexander, Wenhao Chen, Elizabeth J. Drenkard, Hubert du Pontavice, Raphael Dussin, Fabian Gomez, Jasmin G. John, Dujuan Kang, Diane Lavoie, Laure Resplandy, Alizée Roobaert, Vincent Saba, Sang-Ik Shin, Samantha Siedlecki, and James Simkins
Geosci. Model Dev., 16, 6943–6985, https://doi.org/10.5194/gmd-16-6943-2023, https://doi.org/10.5194/gmd-16-6943-2023, 2023
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We evaluate a model for northwest Atlantic Ocean dynamics and biogeochemistry that balances high resolution with computational economy by building on the new regional features in the MOM6 ocean model and COBALT biogeochemical model. We test the model's ability to simulate impactful historical variability and find that the model simulates the mean state and variability of most features well, which suggests the model can provide information to inform living-marine-resource applications.
Luca Arpaia, Christian Ferrarin, Marco Bajo, and Georg Umgiesser
Geosci. Model Dev., 16, 6899–6919, https://doi.org/10.5194/gmd-16-6899-2023, https://doi.org/10.5194/gmd-16-6899-2023, 2023
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We propose a discrete multilayer shallow water model based on z-layers which, thanks to the insertion and removal of surface layers, can deal with an arbitrarily large tidal oscillation independently of the vertical resolution. The algorithm is based on a two-step procedure used in numerical simulations with moving boundaries (grid movement followed by a grid topology change, that is, the insertion/removal of surface layers), which avoids the appearance of very thin surface layers.
Lucille Barré, Frédéric Diaz, Thibaut Wagener, France Van Wambeke, Camille Mazoyer, Christophe Yohia, and Christel Pinazo
Geosci. Model Dev., 16, 6701–6739, https://doi.org/10.5194/gmd-16-6701-2023, https://doi.org/10.5194/gmd-16-6701-2023, 2023
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While several studies have shown that mixotrophs play a crucial role in the carbon cycle, the impact of environmental forcings on their dynamics remains poorly investigated. Using a biogeochemical model that considers mixotrophs, we study the impact of light and nutrient concentration on the ecosystem composition in a highly dynamic Mediterranean coastal area: the Bay of Marseille. We show that mixotrophs cope better with oligotrophic conditions compared to strict auto- and heterotrophs.
Trygve Halsne, Kai Håkon Christensen, Gaute Hope, and Øyvind Breivik
Geosci. Model Dev., 16, 6515–6530, https://doi.org/10.5194/gmd-16-6515-2023, https://doi.org/10.5194/gmd-16-6515-2023, 2023
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Surface waves that propagate in oceanic or coastal environments get influenced by their surroundings. Changes in the ambient current or the depth profile affect the wave propagation path, and the change in wave direction is called refraction. Some analytical solutions to the governing equations exist under ideal conditions, but for realistic situations, the equations must be solved numerically. Here we present such a numerical solver under an open-source license.
Jiangyu Li, Shaoqing Zhang, Qingxiang Liu, Xiaolin Yu, and Zhiwei Zhang
Geosci. Model Dev., 16, 6393–6412, https://doi.org/10.5194/gmd-16-6393-2023, https://doi.org/10.5194/gmd-16-6393-2023, 2023
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Ocean surface waves play an important role in the air–sea interface but are rarely activated in high-resolution Earth system simulations due to their expensive computational costs. To alleviate this situation, this paper designs a new wave modeling framework with a multiscale grid system. Evaluations of a series of numerical experiments show that it has good feasibility and applicability in the WAVEWATCH III model, WW3, and can achieve the goals of efficient and high-precision wave simulation.
Doroteaciro Iovino, Pier Giuseppe Fogli, and Simona Masina
Geosci. Model Dev., 16, 6127–6159, https://doi.org/10.5194/gmd-16-6127-2023, https://doi.org/10.5194/gmd-16-6127-2023, 2023
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This paper describes the model performance of three global ocean–sea ice configurations, from non-eddying (1°) to eddy-rich (1/16°) resolutions. Model simulations are obtained following the Ocean Model Intercomparison Project phase 2 (OMIP2) protocol. We compare key global climate variables across the three models and against observations, emphasizing the relative advantages and disadvantages of running forced ocean–sea ice models at higher resolution.
Gloria Pietropolli, Luca Manzoni, and Gianpiero Cossarini
EGUsphere, https://doi.org/10.5194/egusphere-2023-1876, https://doi.org/10.5194/egusphere-2023-1876, 2023
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Harness AI for better ocean insights. BGC-Argo floats collect deep ocean data, yet forecasting vital nutrient levels is a challenge. Our novel AI approach, PPCon, learns from Argo float measurements and provides improved nutrient predictions. This enhances our understanding of ocean dynamics and nutrient distribution.
Johannes Röhrs, Yvonne Gusdal, Edel S. U. Rikardsen, Marina Durán Moro, Jostein Brændshøi, Nils Melsom Kristensen, Sindre Fritzner, Keguang Wang, Ann Kristin Sperrevik, Martina Idžanović, Thomas Lavergne, Jens Boldingh Debernard, and Kai H. Christensen
Geosci. Model Dev., 16, 5401–5426, https://doi.org/10.5194/gmd-16-5401-2023, https://doi.org/10.5194/gmd-16-5401-2023, 2023
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A model to predict ocean currents, temperature, and sea ice is presented, covering the Barents Sea and northern Norway. To quantify forecast uncertainties, the model calculates ensemble forecasts with 24 realizations of ocean and ice conditions. Observations from satellites, buoys, and ships are ingested by the model. The model forecasts are compared with observations, and we show that the ocean model has skill in predicting sea surface temperatures.
Jin-Song von Storch, Eileen Hertwig, Veit Lüschow, Nils Brüggemann, Helmuth Haak, Peter Korn, and Vikram Singh
Geosci. Model Dev., 16, 5179–5196, https://doi.org/10.5194/gmd-16-5179-2023, https://doi.org/10.5194/gmd-16-5179-2023, 2023
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The new ocean general circulation model ICON-O is developed for running experiments at kilometer scales and beyond. One targeted application is to simulate internal tides crucial for ocean mixing. To ensure their realism, which is difficult to assess, we evaluate the barotropic tides that generate internal tides. We show that ICON-O is able to realistically simulate the major aspects of the observed barotropic tides and discuss the aspects that impact the quality of the simulated tides.
Bror F. Jönsson, Christopher L. Follett, Jacob Bien, Stephanie Dutkiewicz, Sangwon Hyun, Gemma Kulk, Gael L. Forget, Christian Müller, Marie-Fanny Racault, Christopher N. Hill, Thomas Jackson, and Shubha Sathyendranath
Geosci. Model Dev., 16, 4639–4657, https://doi.org/10.5194/gmd-16-4639-2023, https://doi.org/10.5194/gmd-16-4639-2023, 2023
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While biogeochemical models and satellite-derived ocean color data provide unprecedented information, it is problematic to compare them. Here, we present a new approach based on comparing probability density distributions of model and satellite properties to assess model skills. We also introduce Earth mover's distances as a novel and powerful metric to quantify the misfit between models and observations. We find that how 3D chlorophyll fields are aggregated can be a significant source of error.
Jan David Zika and Sohail Taimoor
EGUsphere, https://doi.org/10.5194/egusphere-2023-1220, https://doi.org/10.5194/egusphere-2023-1220, 2023
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We describe a method to relate the fluxes of heat and fresh water at the sea surface, to the resulting distribution of sea water among categories such as warm and salty, cold and salty, etc. The method exploits the laws that govern how heat and salt change when water mixes. The method will allow the climate community to improve estimates of how much heat the ocean is absorbing and how rainfall and evaporation are changing across the globe.
Rafael Santana, Helen Macdonald, Joanne O'Callaghan, Brian Powell, Sarah Wakes, and Sutara H. Suanda
Geosci. Model Dev., 16, 3675–3698, https://doi.org/10.5194/gmd-16-3675-2023, https://doi.org/10.5194/gmd-16-3675-2023, 2023
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We show the importance of assimilating subsurface temperature and velocity data in a model of the East Auckland Current. Assimilation of velocity increased the representation of large oceanic vortexes. Assimilation of temperature is needed to correctly simulate temperatures around 100 m depth, which is the most difficult region to simulate in ocean models. Our simulations showed improved results in comparison to the US Navy global model and highlight the importance of regional models.
David Byrne, Jeff Polton, Enda O'Dea, and Joanne Williams
Geosci. Model Dev., 16, 3749–3764, https://doi.org/10.5194/gmd-16-3749-2023, https://doi.org/10.5194/gmd-16-3749-2023, 2023
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Validation is a crucial step during the development of models for ocean simulation. The purpose of validation is to assess how accurate a model is. It is most commonly done by comparing output from a model to actual observations. In this paper, we introduce and demonstrate usage of the COAsT Python package to standardise the validation process for physical ocean models. We also discuss our five guiding principles for standardised validation.
Katherine Hutchinson, Julie Deshayes, Christian Éthé, Clément Rousset, Casimir de Lavergne, Martin Vancoppenolle, Nicolas C. Jourdain, and Pierre Mathiot
Geosci. Model Dev., 16, 3629–3650, https://doi.org/10.5194/gmd-16-3629-2023, https://doi.org/10.5194/gmd-16-3629-2023, 2023
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Bottom Water constitutes the lower half of the ocean’s overturning system and is primarily formed in the Weddell and Ross Sea in the Antarctic due to interactions between the atmosphere, ocean, sea ice and ice shelves. Here we use a global ocean 1° resolution model with explicit representation of the three large ice shelves important for the formation of the parent waters of Bottom Water. We find doing so reduces salt biases, improves water mass realism and gives realistic ice shelf melt rates.
Daniele Bianchi, Daniel McCoy, and Simon Yang
Geosci. Model Dev., 16, 3581–3609, https://doi.org/10.5194/gmd-16-3581-2023, https://doi.org/10.5194/gmd-16-3581-2023, 2023
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We present NitrOMZ, a new model of the oceanic nitrogen cycle that simulates chemical transformations within oxygen minimum zones (OMZs). We describe the model formulation and its implementation in a one-dimensional representation of the water column before evaluating its ability to reproduce observations in the eastern tropical South Pacific. We conclude by describing the model sensitivity to parameter choices and environmental factors and its application to nitrogen cycling in the ocean.
Rui Sun, Alison Cobb, Ana B. Villas Bôas, Sabique Langodan, Aneesh C. Subramanian, Matthew R. Mazloff, Bruce D. Cornuelle, Arthur J. Miller, Raju Pathak, and Ibrahim Hoteit
Geosci. Model Dev., 16, 3435–3458, https://doi.org/10.5194/gmd-16-3435-2023, https://doi.org/10.5194/gmd-16-3435-2023, 2023
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In this work, we integrated the WAVEWATCH III model into the regional coupled model SKRIPS. We then performed a case study using the newly implemented model to study Tropical Cyclone Mekunu, which occurred in the Arabian Sea. We found that the coupled model better simulates the cyclone than the uncoupled model, but the impact of waves on the cyclone is not significant. However, the waves change the sea surface temperature and mixed layer, especially in the cold waves produced due to the cyclone.
Pengcheng Wang and Natacha B. Bernier
Geosci. Model Dev., 16, 3335–3354, https://doi.org/10.5194/gmd-16-3335-2023, https://doi.org/10.5194/gmd-16-3335-2023, 2023
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Effects of sea ice are typically neglected in operational flood forecast systems. In this work, we capture these effects via the addition of a parameterized ice–ocean stress. The parameterization takes advantage of forecast fields from an advanced ice–ocean model and features a novel, consistent representation of the tidal relative ice–ocean velocity. The new parameterization leads to improved forecasts of tides and storm surges in polar regions. Associated physical processes are discussed.
Yue Xu and Xiping Yu
Geosci. Model Dev., 16, 2811–2831, https://doi.org/10.5194/gmd-16-2811-2023, https://doi.org/10.5194/gmd-16-2811-2023, 2023
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An accurate description of the wind energy input into ocean waves is crucial to ocean wave modeling, and a physics-based consideration of the effect of wave breaking is absolutely necessary to obtain such an accurate description, particularly under extreme conditions. This study evaluates the performance of a recently improved formula, taking into account not only the effect of breaking but also the effect of airflow separation on the leeside of steep wave crests in a reasonably consistent way.
Yankun Gong, Xueen Chen, Jiexin Xu, Jieshuo Xie, Zhiwu Chen, Yinghui He, and Shuqun Cai
Geosci. Model Dev., 16, 2851–2871, https://doi.org/10.5194/gmd-16-2851-2023, https://doi.org/10.5194/gmd-16-2851-2023, 2023
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Internal solitary waves (ISWs) play crucial roles in mass transport and ocean mixing in the northern South China Sea. Massive numerical investigations have been conducted in this region, but there was no systematic evaluation of a three-dimensional model about precisely simulating ISWs. Here, an ISW forecasting model is employed to evaluate the roles of resolution, tidal forcing and stratification in accurately reproducing wave properties via comparison to field and remote-sensing observations.
Johannes Bieser, David J. Amptmeijer, Ute Daewel, Joachim Kuss, Anne L. Soerensen, and Corinna Schrum
Geosci. Model Dev., 16, 2649–2688, https://doi.org/10.5194/gmd-16-2649-2023, https://doi.org/10.5194/gmd-16-2649-2023, 2023
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MERCY is a 3D model to study mercury (Hg) cycling in the ocean. Hg is a highly harmful pollutant regulated by the UN Minamata Convention on Mercury due to widespread human emissions. These emissions eventually reach the oceans, where Hg transforms into the even more toxic and bioaccumulative pollutant methylmercury. MERCY predicts the fate of Hg in the ocean and its buildup in the food chain. It is the first model to consider Hg accumulation in fish, a major source of Hg exposure for humans.
Y. Joseph Zhang, Tomas Fernandez-Montblanc, William Pringle, Hao-Cheng Yu, Linlin Cui, and Saeed Moghimi
Geosci. Model Dev., 16, 2565–2581, https://doi.org/10.5194/gmd-16-2565-2023, https://doi.org/10.5194/gmd-16-2565-2023, 2023
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Simulating global ocean from deep basins to coastal areas is a daunting task but is important for disaster mitigation efforts. We present a new 3D global ocean model on flexible mesh to study both tidal and nontidal processes and total water prediction. We demonstrate the potential for
seamlesssimulation, on a single mesh, from the global ocean to a few estuaries along the US West Coast. The model can serve as the backbone of a global tide surge and compound flooding forecasting framework.
Qi Shu, Qiang Wang, Chuncheng Guo, Zhenya Song, Shizhu Wang, Yan He, and Fangli Qiao
Geosci. Model Dev., 16, 2539–2563, https://doi.org/10.5194/gmd-16-2539-2023, https://doi.org/10.5194/gmd-16-2539-2023, 2023
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Ocean models are often used for scientific studies on the Arctic Ocean. Here the Arctic Ocean simulations by state-of-the-art global ocean–sea-ice models participating in the Ocean Model Intercomparison Project (OMIP) were evaluated. The simulations on Arctic Ocean hydrography, freshwater content, stratification, sea surface height, and gateway transports were assessed and the common biases were detected. The simulations forced by different atmospheric forcing were also evaluated.
Manuel Aghito, Loris Calgaro, Knut-Frode Dagestad, Christian Ferrarin, Antonio Marcomini, Øyvind Breivik, and Lars Robert Hole
Geosci. Model Dev., 16, 2477–2494, https://doi.org/10.5194/gmd-16-2477-2023, https://doi.org/10.5194/gmd-16-2477-2023, 2023
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The newly developed ChemicalDrift model can simulate the transport and fate of chemicals in the ocean and in coastal regions. The model combines ocean physics, including transport due to currents, turbulence due to surface winds and the sinking of particles to the sea floor, with ocean chemistry, such as the partitioning, the degradation and the evaporation of chemicals. The model will be utilized for risk assessment of ocean and sea-floor contamination from pollutants emitted from shipping.
Nieves G. Valiente, Andrew Saulter, Breogan Gomez, Christopher Bunney, Jian-Guo Li, Tamzin Palmer, and Christine Pequignet
Geosci. Model Dev., 16, 2515–2538, https://doi.org/10.5194/gmd-16-2515-2023, https://doi.org/10.5194/gmd-16-2515-2023, 2023
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We document the Met Office operational global and regional wave models which provide wave forecasts up to 7 d ahead. Our models present coarser resolution offshore to higher resolution near the coastline. The increased resolution led to replication of the extremes but to some overestimation during modal conditions. If currents are included, wave directions and long period swells near the coast are significantly improved. New developments focus on the optimisation of the models with resolution.
Maxime Beauchamp, Quentin Febvre, Hugo Georgenthum, and Ronan Fablet
Geosci. Model Dev., 16, 2119–2147, https://doi.org/10.5194/gmd-16-2119-2023, https://doi.org/10.5194/gmd-16-2119-2023, 2023
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4DVarNet is a learning-based method based on traditional data assimilation (DA). This new class of algorithms can be used to provide efficient reconstructions of a dynamical system based on single observations. We provide a 4DVarNet application to sea surface height reconstructions based on nadir and future Surface Water and Ocean and Topography data. It outperforms other methods, from optimal interpolation to sophisticated DA algorithms. This work is part of on-going AI Chair Oceanix projects.
Bin Xiao, Fangli Qiao, Qi Shu, Xunqiang Yin, Guansuo Wang, and Shihong Wang
Geosci. Model Dev., 16, 1755–1777, https://doi.org/10.5194/gmd-16-1755-2023, https://doi.org/10.5194/gmd-16-1755-2023, 2023
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A new global surface-wave–tide–circulation coupled ocean model (FIO-COM32) with a resolution of 1/32° × 1/32° is developed and validated. Both the promotion of the horizontal resolution and included physical processes are shown to be important contributors to the significant improvements in FIO-COM32 simulations. It is time to merge these separated model components (surface waves, tidal currents and ocean circulation) and start a new generation of ocean model development.
Cited articles
Adcroft, A. and Campin, J.: Rescaled height coordinates for accurate representation of free-surface flows in ocean circulation models, Ocean Model., 7, 269–284, 2004.
Adcroft, A., Hill, C., and Marshall, J.: A new treatment of the Coriolis terms in C-grid models at both high and low resolutions, Mon. Weather Rev., 127, 1928–1936, 1999.
Adcroft, A., Campin, J.-M., Hill, C., and Marshall, J.: Implementation of an atmosphere-ocean general circulation model on the expanded spherical cube, Mon. Weather Rev., 132, 2845–2863, https://doi.org/10.1175/MWR2823.1, 2004a.
Adcroft, A., Hill, C., Campin, J.-M., Marshall, J., and Heimbach, P.: Overview of the formulation and numerics of the MITGCM, in: Proceedings of the ECMWF Seminar Series on Numerical Methods, Recent Developments in Numerical Methods for Atmosphere and Ocean Modelling, 139–149, ECMWF, available at: http://mitgcm.org/pdfs/ECMWF2004-Adcroft.pdf (last access: 29 April 2015), 2004b.
Andersen, O. B. and Knudsen, P.: DNSC08 mean sea surface and mean dynamic topography models, J. Geophys. Res.-Oceans, 114, C11001, https://doi.org/10.1029/2008JC005179, 2009.
Balmaseda, M. A., Hernandez, F., Storto, A., Palmer, M., Shi, L., Smith, G., Toyoda, T., Valdivieso, M., Alves, O., Barnier, B., Boyer, T., Chang, Y.-S., Chepurin, G. A., Ferry, N., Forget, G., Fujii, Y., Good, S., Guinehut, S., Haines, K., Ishikawa, Y., Keeley, S., Köhl, A., Lee, T., Martin, M., Masina, S., Masuda, S., Meyssignac, B., Mogensen, K., Parent, L., Peterson, D., Yin, Y., Vernieres, G., Wang, X., Waters, J., Wedd, R., Wang, O., Xue, Y., Chevallier, M., Lemieux, J.-F., Dupont, F., Kuragano, T., Kamachi, M., Awaji, T., Cantalbiano, A., Wilmer-Becker, K., and Gaillard, F.: The Ocean Reanalyses Intercomparison Project (ORA-IP), Proceedings of the Institute of Marine Engineering, Science, and Technology, J. Operational Oceanogr., 8, 80–97, https://doi.org/10.1080/1755876X.2015.1022329, 2015.
Barnier, B., Madec, G., Penduff, T., Molines, J.-M., Treguier, A.-M., Le Sommer, J., Beckmann, A., Biastoch, A., Böning, C., Dengg, J., Derval, C., Durand, E., Gulev, S., Remy, E., Talandier, C., Theetten, S., Maltrud, M., McClean, J., and De Cuevas, B.: Impact of partial steps and momentum advection schemes in a global ocean circulation model at eddy-permitting resolution, Ocean Dynam., 56, 543–567, 2006.
Barth, A., Beckers, J.-M., Troupin, C., Alvera-Azcárate, A., and Vandenbulcke, L.: divand-1.0: n-dimensional variational data analysis for ocean observations, Geosci. Model Dev., 7, 225–241, https://doi.org/10.5194/gmd-7-225-2014, 2014.
Blessing, S., Kaminski, T., Lunkeit, F., Matei, I., Giering, R., Köhl, A., Scholze, M., Herrmann, P., Fraedrich, K., and Stammer, D.: Testing variational estimation of process parameters and initial conditions of an earth system model, Tellus A, 66, 22606, https://doi.org/10.3402/tellusa.v66.22606, 2014.
Buckley, M. W., Ponte, R. M., Forget, G., and Heimbach, P.: Low-frequency SST and upper-ocean heat content variability in the North Atlantic, J. Climate, 27, 4996–5018, 2014.
Buckley, M. W., Ponte, R. M., Forget, G., and Heimbach, P.: Determining the origins of advective heat transport convergence variability in the North Atlantic, J. Climate, 28, 3943–3956, 2015.
Campin, J., Adcroft, A., Hill, C., and Marshall, J.: Conservation of properties in a free surface model, Ocean Model., 6, 221–244, 2004.
Campin, J.-M., Marshall, J., and Ferreira, D.: Sea ice–ocean coupling using a rescaled vertical coordinate, Ocean Model., 24, 1–14, 2008.
Chaudhuri, A. H., Ponte, R. M., Forget, G., and Heimbach, P.: A comparison of atmospheric reanalysis surface products over the ocean and implications for uncertainties in air–sea boundary forcing, J. Climate, 26, 153–170, 2013.
Comiso, J.: Bootstrap sea ice concentrations for NIMBUS-7 SMMR and DMSP SSM/I, Digital Media, National Snow and Ice Data Center, https://doi.org/10.5067/J6JQLS9EJ5HU, 1999.
Dail, H. and Wunsch, C.: Dynamical reconstruction of upper-ocean conditions in the Last Glacial Maximum Atlantic, J. Climate, 27, 807–823, https://doi.org/10.1175/JCLI-D-13-00211.1, 2014.
Danabasoglu, G., Yeager, S. G., Bailey, D., Behrens, E., Bentsen, M., Bi, D., Biastoch, A., Böning, C., Bozec, A., Canuto, V. M., Cassou, C., Chassignet, E., Coward, A. C., Danilov, S., Diansky, N., Drange, H., Farneti, R., Fernandez, E., Fogli, P. G., Forget, G., Fujii, Y., Griffies, S. M., Gusev, A., Heimbach, P., Howard, A., Jung, T., Kelley, M., Large, W. G., Leboissetier, A., Lu, J., Madec, G., Marsland, S. J., Masina, S., Navarra, A., Nurser, A. G., Pirani, A., Salas y Mélia, D., Samuels, B. L., Scheinert, M., Sidorenko, D., Treguier, A.-M., Tsujino, H., Uotila, P., Valcke, S., Voldoire, A., and Wang, Q.: North Atlantic simulations in Coordinated Ocean-ice Reference Experiments phase {II} (CORE-II). Part I: Mean states, Ocean Model., 73, 76–107, https://doi.org/10.1016/j.ocemod.2013.10.005, 2014.
Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi, S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P., Bechtold, P., Beljaars, A. C. M., van de Berg, L., Bidlot, J., Bormann, N., Delsol, C., Dragani, R., Fuentes, M., Geer, A. J., Haimberger, L., Healy, S. B., Hersbach, H., Hólm, E. V., Isaksen, L., Kållberg, P., Köhler, M., Matricardi, M., McNally, A. P., Monge-Sanz, B. M., Morcrette, J.-J., Park, B.-K., Peubey, C., de Rosnay, P., Tavolato, C., Thépaut, J.-N., and Vitart, F.: The ERA-Interim reanalysis: configuration and performance of the data assimilation system, Q. J. Roy. Meteor. Soc., 137, 553–597, 2011.
Denham, C. R.: Seagrid orthogonal grid maker for matlab, US Geological Survey, 384, available at: http://woodshole.er.usgs.gov/staffpages/cdenham/public_html/seagrid/seagrid.html (last access: 29 April 2015) 2000.
Duffy, P., Eby, M., and Weaver, A.: Effects of sinking of salt rejected during formation of sea ice on results of an ocean–atmosphere-sea ice climate model, Geophys. Res. Lett., 26, 1739–1742, 1999.
Dutkiewicz, S., Sokolov, A. P., Scott, J., and Stone, P. H.: A Three-Dimensional Ocean-Seaice-Carbon Cycle Model and its Coupling to a Two-Dimensional Atmospheric Model: Uses in Climate Change Studies, MIT Joint Program on the Science and Policy of Global Change, available at: http://hdl.handle.net/1721.1/18091 (last access: 29 April 2015), 2005.
Ekman, V. W.: On the influence of the earth's rotation on ocean currents, Ark. Mat. Astron. Fys., 2, 1–53, 1905.
Fekete, B. M., Vörösmarty, C. J., and Grabs, W.: High-resolution fields of global runoff combining observed river discharge and simulated water balances, Global Biogeochem. Cy., 16, 15.1–15.10, https://doi.org/10.1029/1999GB001254, 2002.
Fenty, I. and Heimbach, P.: Coupled sea ice–ocean-state estimation in the Labrador Sea and Baffin Bay, J. Phys. Oceanogr., 43, 884–904, 2013.
Ferreira, D., Marshall, J., and Heimbach, P.: Estimating eddy stresses by fitting dynamics to observations using a residual-mean ocean circulation model and its adjoint, J. Phys. Oceanogr., 35, 1891–1910, https://doi.org/10.1175/JPO2785.1, 2005.
Ferreira, D., Marshall, J., and Rose, B.: Climate determinism revisited: multiple equilibria in a complex climate model, J. Climate, 24, 992–1012, 2011.
Ferron, B. and Marotzke, J.: Impact of 4D-variational assimilation of WOCE hydrography on the meridional circulation of the Indian Ocean, Deep-Sea Res. Pt. II, 50, 2005–2021, 2003.
Follows, M. J., Dutkiewicz, S., Grant, S., and Chisholm, S. W.: Emergent biogeography of microbial communities in a model ocean, Science, 315, 1843–1846, 2007.
Forget, G.: Mapping ocean observations in a dynamical framework: a 2004–06 ocean atlas, J. Phys. Oceanogr., 40, 1201–1221, 2010.
Forget, G.: The observed abyssal variability puzzle, Geophys. Res. Lett., in preparation, 2015.
Forget, G. and Ponte, R.: The partition of regional sea level variability, Prog. Oceanogr., 137, 173–195, 2015.
Forget, G. and Wunsch, C.: Estimated global hydrographic variability, J. Phys. Oceanogr., 37, 1997–2008, 2007.
Forget, G., Ferron, B., and Mercier, H.: Combining Argo profiles with a general circulation model in the North Atlantic. Part 1: Estimation of hydrographic and circulation anomalies from synthetic profiles, over a year, Ocean Model., 20, 1–16, 2008a.
Forget, G., Mercier, H., and Ferron, B.: Combining Argo profiles with a general circulation model in the North Atlantic. Part 2: Realistic transports and improved hydrography, between spring 2002 and spring 2003, Ocean Model., 20, 17–34, 2008b.
Forget, G., Maze, G., Buckley, M., and Marshall, J.: Estimated seasonal cycle of North Atlantic eighteen degree water volume, J. Phys. Oceanogr., 41, 269–286, 2011.
Forget, G., Ferreira, D., and Liang, X.: On the observability of turbulent transport rates by Argo: supporting evidence from an inversion experiment, Ocean Sci. Discuss., 12, 1107–1143, https://doi.org/10.5194/osd-12-1107-2015, 2015.
Fukumori, I.: A partitioned Kalman filter and smoother, Mon. Weather Rev., 130, 1370–1383, 2002.
Fukumori, I., Menemenlis, D., and Lee, T.: A near-uniform basin-wide sea level fluctuation of the Mediterranean Sea, J. Phys. Oceanogr., 37, 338–358, 2007.
Fukumori, I., Wang, O., Llovel, W., Fenty, I., and Forget, G.: A near-uniform fluctuation of ocean bottom pressure and sea level across the deep ocean basins of the Arctic Ocean and the Nordic Seas, Prog. Oceanogr., 134, 152–172, 2015.
Gaspar, P., Grégoris, Y., and Lefevre, J.-M.: A simple eddy kinetic energy model for simulations of the oceanic vertical mixing: tests at station papa and long-term upper ocean study site, J. Geophys. Res., 95, 16179–16193, 1990.
Gent, P. and Mcwilliams, J.: Isopycnal mixing in ocean circulation models, J. Phys. Oceanogr., 20, 150–155, 1990.
Giering, R. and Kaminski, T.: Recipes for adjoint code construction, ACM T. Math. Software, 24, 437–474, 1998.
Giering, R., Kaminski, T., and Slawig, T.: Generating efficient derivative code with TAF: adjoint and tangent linear Euler flow around an airfoil, Future Gener. Comp. Sy., 21, 1345–1355, 2005.
Goldberg, D. N. and Heimbach, P.: Parameter and state estimation with a time-dependent adjoint marine ice sheet model, The Cryosphere, 7, 1659–1678, https://doi.org/10.5194/tc-7-1659-2013, 2013.
Griewank, A.: Achieving logarithmic growth of temporal and spatial complexity in reverse automatic differentiation, Optim. Method. Softw., 1, 35–54, 1992.
Griewank, A. and Walther, A.: Evaluating Derivatives: Principles and Techniques of Algorithmic Differentiation, Society for Industrial and Applied Mathematics, Philadelphia, PA, https://doi.org/10.1137/1.9780898717761, 2008.
Griffies, S. and Greatbatch, R.: Physical processes that impact the evolution of global mean sea level in ocean climate models, J. Marine Syst., 51, 37–72, 2012.
Hansen, P. C.: Analysis of discrete ill-posed problems by means of the L-curve, SIAM Rev., 34, 561–580, 1992.
Hascoët, L. and Pascual, V.: The Tapenade automatic differentiation tool: p}rinciples, model, and specification, {ACM T. Math. Software, 39, 20.1–20.43, https://doi.org/10.1145/2450153.2450158, 2013.
Heimbach, P., Hill, C., and Giering, R.: Automatic generation of efficient adjoint code for a parallel Navier–Stokes solver, in: Computational Science – ICCS 2002, Springer, 1019–1028, 2002.
Heimbach, P., Hill, C., and Giering, R.: An efficient exact adjoint of the parallel MIT general circulation model, generated via automatic differentiation, Future Gener. Comp. Sy., 21, 1356–1371, 2005.
Heimbach, P., Forget, G., Ponte, R., Wunsch, C., Balmaseda, M., Awaji, T., Baehr, J., Behringer, D., Carton, J., Ferry, N., Fischer, A., Fukumori, I., Giese, B., Haines, K., Harrison, E., Hernandez, F., Kamachi, M., Keppenne, C., Köhl, A., Lee, T., Menemenlis, D., Oke, P., Remy, E., Rienecker, M., Rosati, A., Smith, D., Speer, K., Stammer, D., and Weaver, A.: Observational requirements for global-scale ocean climate analysis: lessons from ocean state estimation, in: Proceedings of the OceanObs09 Conference: Sustained Ocean Observations and Information for Society, Venice, Italy, Vol. 2, https://doi.org/10.5270/OceanObs09.cwp.42, 2009.
Heimbach, P., Menemenlis, D., Losch, M., Campin, J.-M., and Hill, C.: On the formulation of sea-ice models. Part 2: Lessons from multi-year adjoint sea-ice export sensitivities through the Canadian Arctic Archipelago, Ocean Model., 33, 145–158, 2010.
Heimbach, P., Wunsch, C., Ponte, R. M., Forget, G., Hill, C., and Utke, J.: Timescales and regions of the sensitivity of Atlantic meridional volume and heat transport: toward observing system design, Deep-Sea Res. Pt. II, 58, 1858–1879, 2011.
Holland, W. R. and Malanotte-Rizzoli, P.: Assimilation of altimeter data into an ocean circulation model: space versus time resolution studies, J. Phys. Oceanogr., 19, 1507–1534, 1989.
Hoppe, C. M., Elbern, H., and Schwinger, J.: A variational data assimilation system for soil–atmosphere flux estimates for the Community Land Model (CLM3.5), Geosci. Model Dev., 7, 1025–1036, https://doi.org/10.5194/gmd-7-1025-2014, 2014.
Hoteit, I., Cornuelle, B., Köhl, A., and Stammer, D.: Treating strong adjoint sensitivities in tropical eddy-permitting variational data assimilation, Q. J. Roy. Meteor. Soc., 131, 3659–3682, 2005.
Hoteit, I., Cornuelle, B., Kim, S., Forget, G., Köhl, A., and Terrill, E.: Assessing 4D-VAR for dynamical mapping of coastal high-frequency radar in San Diego, Dynam. Atmos. Oceans, 48, 175–197, 2009.
Hoteit, I., Hoar, T., Gopalakrishnan, G., Collins, N., Anderson, J., Cornuelle, B., Köhl, A., and Heimbach, P.: A MITgcm/DART ensemble analysis and prediction system with application to the Gulf of Mexico, Dynam. Atmos. Oceans, 63, 1–23, 2013.
Ives, D. C. and Zacharias, R. M.: Conformal mapping and orthogonal grid generation, J. Propul. Power, 5, 327–333, 1989.
Jackett, D. R. and McDougall, T. J.: Minimal adjustment of hydrographic profiles to achieve static stability, J. Atmos. Ocean. Tech., 12, 381–389, 1995.
Jiang, Z., Hui, W., and Kamachi, M.: The improvement made by a modified TLM in 4DVAR with a geophysical boundary layer model, Adv. Atmos. Sci., 19, 563–582, 2002.
Kalmikov, A. G. and Heimbach, P.: A Hessian-based method for uncertainty quantification in global ocean state estimation, SIAM J. Sci. Comput., 36, S267–S295, 2014.
Köhl, A.: Evaluation of the GECCO2 ocean synthesis: transports of volume, heat and freshwater in the Atlantic, Q. J. Roy. Meteor. Soc., 141, 166–181, https://doi.org/10.1002/qj.2347, 2014.
Köhl, A. and Stammer, D.: Optimal observations for variational data assimilation, J. Phys. Oceanogr., 34, 529–542, 2004.
Köhl, A. and Stammer, D.: Decadal sea level changes in the 50-Year GECCO Ocean Synthesis, J. Climate, 21, 1876–1890, https://doi.org/10.1175/2007JCLI2081.1, 2008.
Köhl, A., Stammer, D., and Cornuelle, B.: Interannual to decadal changes in the ECCO global synthesis., J. Phys. Oceanogr., 37, 529–542, https://doi.org/10.1175/2513.1, 2007.
Köhl, A., Siegismund, F., and Stammer, D.: Impact of assimilating bottom pressure anomalies from GRACE on ocean circulation estimates, J. Geophys. Res., 117, C04032, https://doi.org/10.1029/2011JC007623, 2012.
Large, W. and Yeager, S.: Diurnal to decadal global forcing for ocean and sea-ice models: the data sets and flux climatologies, Technical Report TN-460+STR, NCAR, 2004.
Large, W., McWilliams, J., and Doney, S.: Oceanic vertical mixing: a review and a model with a nonlocal boundary layer parameterization, Rev. Geophys., 32, 363–403, 1994.
Liang, X., Wunsch, C., Heimbach, P., and Forget, G.: Vertical redistribution of oceanic heat content, J. Climate, 28, 3821–3833, https://doi.org/10.1175/JCLI-D-14-00550.1, 2015.
Liu, C., Köhl, A., and Stammer, D.: Adjoint-based estimation of eddy-induced tracer mixing parameters in the global ocean, J. Phys. Oceanogr., 42, 1186–1206, 2012.
Llovel, W., Willis, J., Landerer, F., and Fukumori, I.: Deep-ocean contribution to sea level and energy budget not detectable over the past decade, Nature Climate Change, 4, 1031–1035, 2014.
Locarnini, R., Mishonov, A., Antonov, J., Boyer, T., Garcia, H., and Levitus, S.: World Ocean Atlas 2005 Volume 1: Temperature, NOAA Atlas NESDIS, S. Levitus, Ed. NOAA Atlas NESDIS 61, US Gov. Printing Office, Wash., D.C., 182 pp., 2006.
Losch, M., Menemenlis, D., Campin, J.-M., Heimbach, P., and Hill, C.: On the formulation of sea-ice models. Part 1: Effects of different solver implementations and parameterizations, Ocean Model., 33, 129–144, 2010.
Losch, M., Strass, V., Cisewski, B., Klaas, C., and Bellerby, R. G.: Ocean state estimation from hydrography and velocity observations during EIFEX with a regional biogeochemical ocean circulation model, J. Marine Syst., 129, 437–451, 2014.
Lyman, J. and Johnson, G.: Estimating global ocean heat content changes in the upper 1800 m since 1950 and the influence of climatology choice, J. Climate, 27, 1945–1957, 2014.
Marotzke, J., Giering, R., Zhang, K. Q., Stammer, D., Hill, C., and Lee, T.: Construction of the adjoint MIT ocean general circulation model and application to Atlantic heat transport sensitivity, J. Geophys. Res.-Oceans, 104, 29529–29547, 1999.
Marshall, J., Adcroft, A., Hill, C., Perelman, L., and Heisey, C.: A finite-volume, incompressible Navier Stokes model for studies of the ocean on parallel computers, J. Geophys. Res., 102, 5753–5766, 1997.
Marshall, J., Ferreira, D., Campin, J., and Enderton, D.: Mean climate and variability of the atmosphere and ocean on an aquaplanet, J. Atmos. Sci., 64, 4270–4286, 2007a.
Marshall, J., Ferreira, D., Campin, J.-M., and Enderton, D.: Mean climate and variability of the atmosphere and ocean on an aqua-planet, J. Atmos. Sci., 64, 4270–4286, 2007b.
Marshall, J., Anderson, A., Dewar, W., Doney, S., Edson, J., Ferrari, R., Forget, G., Fratantoni, D., Gregg, M., Joyce, T., Kelly, K., Lozier, S., Lumpkin, R., Maze, G., Paster, J., Samelson, R., Silverthorne, K., Skyllingstad, E., Straneo, F., Talley, L., Thomas, L., Toole, J., and Weller, R.: Observing the cycle of convection and restratification over the Gulf Stream and the subtropical gyre of the North Atlantic Ocean: preliminary results from the CLIMODE field campaign, B. Am. Meteorol. Soc., 90, 1337–1350, 2009.
Marshall, J., Armour, K. C., Scott, J. R., Kostov, Y., Hausmann, U., Ferreira, D., Shepherd, T. G., and Bitz, C. M.: The ocean's role in polar climate change: asymmetric Arctic and Antarctic responses to greenhouse gas and ozone forcing, Philos. T. R. Soc. A, 372, 20130040, https://doi.org/10.1098/rsta.2013.0040, 2014.
Marzocchi, W. and Jordan, T. H.: Testing for ontological errors in probabilistic forecasting models of natural systems, P. Natl. Acad. Sci. USA, 111, 11973–11978, 2014.
Maze, G., Forget, G., Buckley, M., Marshall, J., and Cerovecki, I.: Using transformation and formation maps to study the role of air–sea heat fluxes in North Atlantic Eighteen Degree Water formation, J. Phys. Oceanogr., 39, 1818–1835, 2009.
Mazloff, M. R., Heimbach, P., and Wunsch, C.: An eddy-permitting Southern Ocean state estimate, J. Phys. Oceanogr., 40, 880–899, 2010.
McCaffrey, K., Fox-Kemper, B., and Forget, G.: Estimates of ocean macro-turbulence: structure function and spectral slope from Argo profiling floats, J. Phys. Oceanogr., 45, 1773–1793, https://doi.org/10.1175/JPO-D-14-0023.1, 2015.
Menemenlis, D., Hill, C., Adcroft, A., Campin, J., Cheng, B., Ciotti, B., Fukumori, I., Koehl, A., Heimbach, P., Henze, C., Lee, T., Stammer, D., Taft, J., and Zhang, J.: NASA supercomputer improves prospects for ocean climate research, EOS T. Am. Geophys. Un., 86–96, https://doi.org/10.1029/2005EO090002, 2005.
Mercier, H.: Determining the general circulation of the ocean: a nonlinear inverse problem, J. Geophys. Res.-Oceans, 91, 5103–5109, 1986.
MITgcm Group: MITgcm Release 1 Manual, Technical report, available at: http://mitgcm.org/public/sealion/ (last access: 29 April 2015), Massachusetts Institute of Technology, Cambridge, MA 02139, USA, 346 pp., 2002.
Moore, A. M., Arango, H. G., Broquet, G., Powell, B. S., Weaver, A. T., and Zavala-Garay, J.: The Regional Ocean Modeling System (ROMS) 4-dimensional variational data assimilation systems: Part I – System overview and formulation, Prog. Oceanogr., 91, 34–49, https://doi.org/10.1016/j.pocean.2011.05.004, 2011.
Munk, W. H.: Abyssal recipes, in: Deep Sea Research and Oceanographic, Vol. 13, Elsevier, 707–730, https://doi.org/10.1016/0011-7471(66)90602-4, 1966.
Myers, G. J., Sandler, C., and Badgett, T.: The art of software testing, John Wiley & Sons, 2011.
Nguyen, A., Menemenlis, D., and Kwok, R.: Improved modeling of the Arctic halocline with a subgrid-scale brine rejection parameterization, J. Geophys. Res.-Oceans, 114, C11014, https://doi.org/10.1029/2008JC005121, 2009.
Olbers, D., Wenzel, M., and Willebrand, J.: The inference of North Atlantic circulation patterns from climatological hydrographic data, Rev. Geophys., 23, 313–356, 1985.
Pavlis, N. K., Holmes, S. A., Kenyon, S. C., and Factor, J. K.: The development and evaluation of the Earth Gravitational Model 2008 (EGM2008), J. Geophys. Res.-Sol. Ea., 117, B04406, https://doi.org/10.1029/2011JB008916, 2012.
Piecuch, C., Ponte, R., Heimbach, H., and Forget, G.: Sensitivity of Ocean-Model Estimates of Contemporary Global and Regional Sea-Level Changes to Geothermal Heat Flow, Ocean Model., under review, 2015.
Ponte, R. M.: Oceanic response to surface loading effects neglected in volume-conserving models, J. Phys. Oceanogr., 36, 426–434, https://doi.org/10.1175/JPO2843.1, 2006.
Ponte, R. M., Wunsch, C., and Stammer, D.: Spatial mapping of time-variable errors in Jason-1 and TOPEX/Poseidon sea surface height measurements, J. Atmos. Ocean. Tech., 24, 1078–1085, 2007.
Prinn, R. G., Heimbach, P., Rigby, M., Dutkiewicz, S., Melillo, J. M., Reilly, J. M., Kicklighter, D. W., and Waugh, C.: A Strategy for a Global Observing System for Verification of National Greenhouse Gas Emissions, Tech. rep., MIT Joint Program on the Science and Policy of Global Change, 2011.
Purkey, S. G. and Johnson, G. C.: Warming of global abyssal and deep Southern Ocean waters between the 1990s and 2000s: contributions to global heat and sea level rise budgets*, J. Climate, 23, 6336–6351, 2010.
Purser, R. and Rančić, M.: Smooth quasi-homogeneous gridding of the sphere, Q. J. Roy. Meteor. Soc., 124, 637–647, 1998.
Quinn, K. J. and Ponte, R. M.: Estimating weights for the use of time-dependent gravity recovery and climate experiment data in constraining ocean models, J. Geophys. Res., 113, C12013, https://doi.org/10.1029/2008JC004903, 2008.
Quinn, K. J. and Ponte, R.: Uncertainty in ocean mass trends from GRACE, Geophys. J. Int., 181, 762–768, https://doi.org/10.1111/j.1365-246X.2010.04508.x, 2010.
Rančić, M., Purser, R., and Mesinger, F.: A global shallow-water model using an expanded spherical cube: gnomonic versus conformal coordinates, Q. J. Roy. Meteor. Soc., 122, 959–982, 1996.
Redi, M. H.: Oceanic isopycnal mixing by coordinate rotation, J. Phys. Oceanogr., 12, 1154–1158, 1982.
Reynolds, R. W., Rayner, N. A., Smith, T. M., Stokes, D. C., and Wang, W.: An improved in situ and satellite SST analysis for climate, J. Climate, 15, 1609–1625, 2002.
Risien, C. and Chelton, D.: A global climatology of surface wind and wind stress fields from eight years of QuikSCAT scatterometer data, J. Phys. Oceanogr., 38, 2379–2413, 2008.
Roquet, F., Charrassin, J.-B., Marchand, S., Boehme, L., Fedak, M., Reverdin, G., and Guinet, C.: Delayed-mode calibration of hydrographic data obtained from animal-borne satellite relay data loggers, J. Atmos. Ocean. Tech., 28, 787–801, 2011.
Ryskin, G. and Leal, L.: Orthogonal mapping, J. Comput. Phys., 50, 71–100, 1983.
Scharroo, R., Lillibridge, J., Smith, W., and Schrama, E.: Cross-calibration and long-term monitoring of the microwave radiometers of ERS, TOPEX, GFO, Jason, and Envisat, Mar. Geod., 27, 279–297, https://doi.org/10.1080/01490410490465265, 2004.
Schott, F. and Zantopp, R.: On the effect of vertical mixing on the determination of absolute currents by the beta spiral method, Deep-Sea Res., 27, 173–180, 1980.
Shchepetkin, A. F. and McWilliams, J. C.: The regional oceanic modeling system (ROMS): a split-explicit, free-surface topography-following-coordinate ocean model, Ocean Model., 9, 347–404, 2005.
Speer, K. and Forget, G.: Chapter 9 – Global distribution and formation of mode waters, in: Ocean Circulation and Climate: a 21st Century Perspective, 211–226, https://doi.org/10.1016/B978-0-12-391851-2.00009-X, 2013.
Stammer, D.: Adjusting internal model errors through ocean state estimation, J. Phys. Oceanogr., 35, 1143–1153, https://doi.org/10.1175/JPO2733.1, 2005.
Stammer, D., Wunsch, C., Giering, R., Eckert, C., Heimbach, P., Marotzke, J., Adcroft, A., Hill, C., and Marshall, J.: The Global ocean circulation during 1992–1997, estimated from ocean observations and a general circulation model, J. Geophys. Res.-Oceans, 107, 1.1–1.27, https://doi.org/10.1029/2001JC000888, 2002.
Stammer, D., Ueyoshi, K., Köhl, A., Large, W., Josey, S., and Wunsch, C.: Estimating air–sea fluxes of heat, freshwater, and momentum through global ocean data assimilation, J. Geophys. Res, 109, 8691–8702, 2004.
Steele, M., Morley, R., and Ermold, W.: PHC: a global ocean hydrography with a high-quality Arctic Ocean, J. Climate, 14, 2079–2087, 2001.
Stommel, H.: The delicate interplay between wind-stress and buoyancy input in ocean circulation: the Goldsbrough variations*, Tellus A, 36, 111–119, 1984.
Sverdrup, H. U.: Wind-driven currents in a baroclinic ocean; with application to the equatorial currents of the eastern Pacific, P. Natl. Acad. Sci. USA, 33, 318–326, 1947.
Thacker, W. C. and Long, R. B.: Fitting dynamics to data, J. Geophys. Res.-Oceans, 93, 1227–1240, 1988.
Toole, J., Krishfield, R., Timmermans, M.-L., and Proshutinsky, A.: The ice-tethered profiler: Argo of the Arctic, Oceanography, 24, 126–135, 2011.
Trefethen, L.: SCPACK user's guide, Tech. rep., Technical Report 89-2, MIT Numerical Analysis Report, 1989.
Tziperman, E. and Thacker, W. C.: An optimal-control/adjoint-equations approach to studying the oceanic general circulation, J. Phys. Oceanogr., 19, 1471–1485, 1989.
Tziperman, E., Thacker, W. C., Long, R. B., and Hwang, S.-M.: Oceanic data analysis using a general circulation model. Part I: Simulations, J. Phys. Oceanogr., 22, 1434–1457, 1992a.
Tziperman, E., Thacker, W. C., Long, R. B., Hwang, S.-M., and Rintoul, S. R.: Oceanic data analysis using a general circulation model. Part II: A North Atlantic model, J. Phys. Oceanogr., 22, 1458–1485, 1992b.
Utke, J., Naumann, U., Fagan, M., Tallent, N., Strout, M., Heimbach, P., Hill, C., and Wunsch, C.: OpenAD/F: a modular open-source tool for automatic differentiation of Fortran codes, ACM T. Math. Software, 34, 18, https://doi.org/10.1145/1377596.1377598, 2008.
Verdy, A., Mazloff, M. R., Cornuelle, B. D., and Kim, S. Y.: Wind-driven sea level variability on the California coast: an adjoint sensitivity analysis, J. Phys. Oceanogr., 44, 297–318, 2014.
Weaver, A. and Courtier, P.: Correlation modelling on the sphere using a generalized diffusion equation, Q. J. Roy. Meteor. Soc., 127, 1815–1846, 2001.
Wells, D.: Prime Numbers: the Most Mysterious Figures in Math, John Wiley & Sons, Hoboken, NJ, 2011.
Wilkin, J. and Hedström, K.: User's manual for an orthogonal curvilinear grid-generation package, Institute of Marine and Coastal Sciences, Rutgers University, available at: http://www.marine.rutgers.edu/po/tools/gridpak/grid_manual.ps.gz (last access: 29 April 2015), 1998.
Wilson, C., Chipperfield, M. P., Gloor, M., and Chevallier, F.: Development of a variational flux inversion system (INVICAT v1.0) using the TOMCAT chemical transport model, Geosci. Model Dev., 7, 2485–2500, https://doi.org/10.5194/gmd-7-2485-2014, 2014.
Wunsch, C.: Determining the general circulation of the oceans: a preliminary discussion, Science, 196, 871–875, 1977.
Wunsch, C.: Acoustic tomography and other answers, in: It's the water that makes you drunk. A celebration in Geophysics and Oceanography – 1982. In honor of Walter Munk on his 65th birthday, Scripps Institution of Oceanography Reference Series 84-5, Scripps Institution of Oceanography of California, San Diego, La Jolla, CA, 47–62, 1984.
Wunsch, C.: Discrete Inverse and State Estimation Problems: with Geophysical Fluid Applications, Cambridge University Press, 2006.
Wunsch, C. and Heimbach, P.: Practical global oceanic state estimation, Physica D, 230, 197–208, 2007.
Wunsch, C. and Heimbach, P.: The global zonally integrated ocean circulation, 1992–2006: seasonal and decadal variability, J. Phys. Oceanogr., 39, 351–368, https://doi.org/10.1175/2008JPO4012.1, 2009.
Wunsch, C. and Heimbach, P.: Dynamically and kinematically consistent global ocean circulation and ice state estimates, in: Ocean Circulation and Climate: a 21st Century Perspective, 103, 553–579, https://doi.org/10.1016/B978-0-12-391851-2.00021-0, 2013a.
Wunsch, C. and Heimbach, P.: Two decades of the Atlantic meridional overturning circulation: anatomy, variations, extremes, prediction, and overcoming its limitations, J. Climate, 26, 7167–7186, 2013b.
Wunsch, C. and Heimbach, P.: Bidecadal thermal changes in the Abyssal Ocean, J. Phys. Oceanogr., 44, 2013–2030, 2014.
Wunsch, C. and Minster, J.-F.: Methods for box models and ocean circulation tracers: mathematical programing and nonlinear inverse theory, J. Geophys. Res.-Oceans, 87, 5647–5662, 1982.
Wunsch, C., Ponte, R., and Heimbach, P.: Decadal trends in sea level patterns: 1993–2004, J. Climate, 20, 5889–5911, 2007.
Yu, L. and Weller, R. A.: Objectively analyzed air–sea heat fluxes for the global ice-free oceans (1981–2005), B. Am. Meteorol. Soc., 88, 527–539, 2007.
Zanna, L., Heimbach, P., Moore, A. M., and Tziperman, E.: Optimal excitation of interannual Atlantic meridional overturning circulation variability, J. Climate, 24, 413–427, 2011.
Short summary
The ECCO v4 non-linear inverse modeling framework and its reference solution are made publicly available. The inverse estimate of ocean physics and atmospheric forcing yields a dynamically consistent and global state estimate without unidentified sources of heat and salt that closely fits in situ and satellite data. Any user can reproduce it accurately. Parametric and external model uncertainties are of comparable magnitudes and generally exceed structural model uncertainties.
The ECCO v4 non-linear inverse modeling framework and its reference solution are made publicly...
