Articles | Volume 14, issue 3
Development and technical paper 01 Apr 2021
Development and technical paper | 01 Apr 2021
Improved representation of river runoff in Estimating the Circulation and Climate of the Ocean Version 4 (ECCOv4) simulations: implementation, evaluation, and impacts to coastal plume regions
Yang Feng et al.
No articles found.
Yoshihiro Nakayama, Dimitris Menemenlis, Ou Wang, Hong Zhang, Ian Fenty, and An T. Nguyen
Geosci. Model Dev. Discuss.,
Preprint under review for GMDShort summary
High ice-shelf melting in the Amundsen Sea attracted many observational campaigns in the past decade. One method to combine observations with numerical models is the adjoint method. After 20 iterations, the cost function, defined as a sum of weighted model-data difference, is reduced by 65 % by adjusting initial conditions, atmospheric forcing, and vertical diffusivity. This study is a demonstration of adjoint-method optimization with explicit representation of ice-shelf cavity circulation.
Junjie Liu, Latha Baskaran, Kevin Bowman, David Schimel, A. Anthony Bloom, Nicholas C. Parazoo, Tomohiro Oda, Dustin Carroll, Dimitris Menemenlis, Joanna Joiner, Roisin Commane, Bruce Daube, Lucianna V. Gatti, Kathryn McKain, John Miller, Britton B. Stephens, Colm Sweeney, and Steven Wofsy
Earth Syst. Sci. Data, 13, 299–330,Short summary
On average, the terrestrial biosphere carbon sink is equivalent to ~ 20 % of fossil fuel emissions. Understanding where and why the terrestrial biosphere absorbs carbon from the atmosphere is pivotal to any mitigation policy. Here we present a regionally resolved satellite-constrained net biosphere exchange (NBE) dataset with corresponding uncertainties between 2010–2018: CMS-Flux NBE 2020. The dataset provides a unique perspective on monitoring regional contributions to the CO2 growth rate.
Fei Chai, Yuntao Wang, Xiaogang Xing, Yunwei Yan, Huijie Xue, Mark Wells, and Emmanuel Boss
Biogeosciences, 18, 849–859,Short summary
The unique observations by a Biogeochemical Argo float in the NW Pacific Ocean captured the impact of a super typhoon on upper-ocean physical and biological processes. Our result reveals typhoons can increase the surface chlorophyll through strong vertical mixing without bringing nutrients upward from the depth. The vertical redistribution of chlorophyll contributes little to enhance the primary production, which is contradictory to many former satellite-based studies related to this topic.
Jianrong Zhu, Xinyue Cheng, Linjiang Li, Hui Wu, Jinghua Gu, and Hanghang Lyu
Hydrol. Earth Syst. Sci., 24, 5043–5056,Short summary
An extremely severe saltwater intrusion event occurred in February 2014 in the Changjiang estuary and seriously influenced the water intake of the reservoir. For the event cause and for freshwater safety, the dynamic mechanism was studied with observed data and a numerical model. The results indicated that this event was caused by a persistent and strong northerly wind, which formed a horizontal estuarine circulation, surpassed seaward runoff and drove highly saline water into the estuary.
Mark J. Hopwood, Dustin Carroll, Thorben Dunse, Andy Hodson, Johnna M. Holding, José L. Iriarte, Sofia Ribeiro, Eric P. Achterberg, Carolina Cantoni, Daniel F. Carlson, Melissa Chierici, Jennifer S. Clarke, Stefano Cozzi, Agneta Fransson, Thomas Juul-Pedersen, Mie H. S. Winding, and Lorenz Meire
The Cryosphere, 14, 1347–1383,Short summary
Here we compare and contrast results from five well-studied Arctic field sites in order to understand how glaciers affect marine biogeochemistry and marine primary production. The key questions are listed as follows. Where and when does glacial freshwater discharge promote or reduce marine primary production? How does spatio-temporal variability in glacial discharge affect marine primary production? And how far-reaching are the effects of glacial discharge on marine biogeochemistry?
S. Zheng, Y. Du, J. Li, and X. Cheng
Ocean Sci., 11, 361–371,Short summary
Eddies in the South Indian Ocean (SIO) were statistically investigated based on 2082 surface drifters, and 19252 eddies were identified with 60% anticyclonic eddies. Mesoscale and submesoscale eddies show different spatial distributions. Large eddies mainly appear in regions with large eddy kinetic energy. The submesoscale anticyclonic eddies are densely distributed in the subtropical basin in the central SIO. The number of mesoscale eddies shows statistically significant seasonal variability.
A. Wang, Y. Du, W. Zhuang, and Y. Qi
Ocean Sci., 11, 305–312,Short summary
Here, we investigated the seasonal variability of subsurface high-salinity water (SHSW) in the northern South China Sea (SCS) and its relationship with the North Equatorial Current-Kuroshio circulation system. Results give new insight into water exchange through the Luzon Strait (LS). The changes in western Pacific large-scale circulation modulate the water exchange in the LS, and thus influence the SHSW in the interior SCS basin.
Related subject area
OceanographyTowards multiscale modeling of ocean surface turbulent mixing using coupled MPAS-Ocean v6.3 and PALM v5.0The Regional Ice Ocean Prediction System v2: a pan-Canadian ocean analysis system using an online tidal harmonic analysisGlobal storm tide modeling with ADCIRC v55: unstructured mesh design and performanceDevelopment of a MetUM (v 11.1) and NEMO (v 3.6) coupled operational forecast model for the Maritime Continent – Part 1: Evaluation of ocean forecastsAdvanced parallel implementation of the coupled ocean–ice model FEMAO (version 2.0) with load balancingThe Meridionally Averaged Model of Eastern Boundary Upwelling Systems (MAMEBUSv1.0)Model-driven optimization of coastal sea observatories through data assimilation in a finite element hydrodynamic model (SHYFEM v. 7_5_65)A simplified atmospheric boundary layer model for an improved representation of air–sea interactions in eddying oceanic models: implementation and first evaluation in NEMO (4.0)Performance of offline passive tracer advection in the Regional Ocean Modeling System (ROMS; v3.6, revision 904)Implementation and assessment of a carbonate system model (Eco3M-CarbOx v1.1) in a highly dynamic Mediterranean coastal site (Bay of Marseille, France)MESMO 3: Flexible phytoplankton stoichiometry and refractory DOMNumerical integrators for Lagrangian oceanographyA Mechanistic Analysis of Tropical Pacific Dynamic Sea Level in GFDL-OM4 under OMIP-I and OMIP-II ForcingsMulti-grid algorithm for passive tracer transport in the NEMO ocean circulation model: a case study with the NEMO OGCM (version 3.6)HIDRA 1.0: Deep-Learning-Based Ensemble Sea Level Forecasting in the Northern AdriaticIntroducing LAB60: A 1∕60° NEMO 3.6 numerical simulation of the Labrador SeaImpact of horizontal resolution on global ocean–sea ice model simulations based on the experimental protocols of the Ocean Model Intercomparison Project phase 2 (OMIP-2)CSIRO Environmental Modelling Suite (EMS): scientific description of the optical and biogeochemical models (vB3p0)Constraining the response of phytoplankton to zooplankton grazing and photo-acclimation in a temperate shelf sea with a 1-D model – towards S2P3 v8.0Comparison of ocean vertical mixing schemes in the Max Plank Institute Earth System Model (MPI-ESM1.2)Doppio – a ROMS (v3.6)-based circulation model for the Mid-Atlantic Bight and Gulf of Maine: configuration and comparison to integrated coastal observing network observationsEvaluation of global ocean–sea-ice model simulations based on the experimental protocols of the Ocean Model Intercomparison Project phase 2 (OMIP-2)Representation of the Denmark Strait overflow in a z-coordinate eddying configuration of the NEMO (v3.6) ocean model: resolution and parameter impactsA global eddying hindcast ocean simulation with OFES2BFM17 v1.0: Reduced-Order Biogeochemical Flux Model for Upper Ocean Biophysical SimulationsTracking water masses using passive-tracer transport in NEMO v3.4 with NEMOTAM: application to North Atlantic Deep Water and North Atlantic Subtropical Mode WaterSensitivity study on the main tidal constituents of the Gulf of Tonkin by using the frequency-domain tidal solver in T-UGOmDINCAE 1.0: a convolutional neural network with error estimates to reconstruct sea surface temperature satellite observationsMitigation of model bias influences on wave data assimilation with multiple assimilation systems using WaveWatch III v5.16 and SWAN v41.20MOMSO 1.0 – an eddying Southern Ocean model configuration with fairly equilibrated natural carbonSimulating barrier island response to sea level rise with the barrier island and inlet environment (BRIE) model v1.0Dealing with discontinuous meteorological forcing in operational ocean modelling: a case study using ECMWF-IFS and GETM (v2.5)The Parcels v2.0 Lagrangian framework: new field interpolation schemesThe INALT family – a set of high-resolution nests for the Agulhas Current system within global NEMO ocean/sea-ice configurationsSensitivity of deep ocean biases to horizontal resolution in prototype CMIP6 simulations with AWI-CM1.0OceanMesh2D 1.0: MATLAB-based software for two-dimensional unstructured mesh generation in coastal ocean modelingOcean carbon and nitrogen isotopes in CSIRO Mk3L-COAL version 1.0: a tool for palaeoceanographic researchA high-resolution biogeochemical model (ROMS 3.4 + bio_Fennel) of the East Australian Current systemNemo-Nordic 1.0: a NEMO-based ocean model for the Baltic and North seas – research and operational applicationsEcological ReGional Ocean Model with vertically resolved sediments (ERGOM SED 1.0): coupling benthic and pelagic biogeochemistry of the south-western Baltic SeaReanalysis of the PacIOOS Hawaiian Island Ocean Forecast System, an implementation of the Regional Ocean Modeling System v3.6Thetis coastal ocean model: discontinuous Galerkin discretization for the three-dimensional hydrostatic equationsData assimilation cycle length and observation impact in mesoscale ocean forecastingVerification of the mixed layer depth in the OceanMAPS operational forecast model for Austral autumnA global scavenging and circulation ocean model of thorium-230 and protactinium-231 with improved particle dynamics (NEMO–ProThorP 0.1)Veros v0.1 – a fast and versatile ocean simulator in pure PythonCohesive and mixed sediment in the Regional Ocean Modeling System (ROMS v3.6) implemented in the Coupled Ocean–Atmosphere–Wave–Sediment Transport Modeling System (COAWST r1234)OpenDrift v1.0: a generic framework for trajectory modellingA 4.5 km resolution Arctic Ocean simulation with the global multi-resolution model FESOM 1.4AMM15: a new high-resolution NEMO configuration for operational simulation of the European north-west shelf
Qing Li and Luke Van Roekel
Geosci. Model Dev., 14, 2011–2028,Short summary
Physical processes in the ocean span multiple spatial and temporal scales. Simultaneously resolving all these in a simulation is computationally challenging. Here we develop a more efficient technique to better study the interactions across scales, particularly focusing on the ocean surface turbulent mixing, by coupling a global ocean circulation model MPAS-Ocean and a large eddy simulation model PALM. The latter is customized and ported on a GPU to further accelerate the computation.
Gregory C. Smith, Yimin Liu, Mounir Benkiran, Kamel Chikhar, Dorina Surcel Colan, Audrey-Anne Gauthier, Charles-Emmanuel Testut, Frederic Dupont, Ji Lei, François Roy, Jean-François Lemieux, and Fraser Davidson
Geosci. Model Dev., 14, 1445–1467,Short summary
Canada's coastlines include diverse ocean environments. In response to the strong need to support marine activities and security, we present the first pan-Canadian operational regional ocean analysis system. A novel online tidal harmonic analysis method is introduced that uses a sliding-window approach. Innovations are compared to those from the Canadian global analysis system. Particular improvements are found near the Gulf Stream due to the higher model grid resolution.
William J. Pringle, Damrongsak Wirasaet, Keith J. Roberts, and Joannes J. Westerink
Geosci. Model Dev., 14, 1125–1145,Short summary
We improve and test a computer model that simulates tides and storm surge over all of Earth's oceans and seas. The model varies mesh resolution (triangular element sizes) freely so that coastal areas, especially storm landfall locations, are well-described. We develop systematic tests of the resolution in order to suggest good mesh design criteria that balance computational efficiency with accuracy for both global astronomical tides and coastal storm tides under extreme weather forcing.
Bijoy Thompson, Claudio Sanchez, Boon Chong Peter Heng, Rajesh Kumar, Jianyu Liu, Xiang-Yu Huang, and Pavel Tkalich
Geosci. Model Dev., 14, 1081–1100,Short summary
This article describes the development and ocean forecast evaluation of an atmosphere–ocean coupled prediction system for the Maritime Continent domain, which includes the eastern Indian and western Pacific oceans. The coupled system comprises regional configurations of the atmospheric model MetUM and ocean model NEMO, coupled using the OASIS3-MCT libraries. The model forecast deviation of selected fields relative to observations is within acceptable error limits of operational forecast models.
Pavel Perezhogin, Ilya Chernov, and Nikolay Iakovlev
Geosci. Model Dev., 14, 843–857,Short summary
We describe the parallel implementation of the FEMAO model for an ice-covered sea with 2D Hilbert-curve domain decomposition. Load balancing is crucial because performance depends on the local depth. We propose, compare, and discuss four approaches to load balancing. The parallel library allowed us to modify the original sequential algorithm as little as possible. The performance increases almost linearly (tested with up to 996 CPU cores) for the model of the shallow White Sea.
Jordyn E. Moscoso, Andrew L. Stewart, Daniele Bianchi, and James C. McWilliams
Geosci. Model Dev., 14, 763–794,Short summary
This project was created to understand the across-shore distribution of plankton in the California Current System. To complete this study, we used a quasi-2-D dynamical model coupled to an ecosystem model. This paper is a preliminary study to test and validate the model against data collected by the California Cooperative Oceanic Fisheries Investigations (CalCOFI). We show the solution of our model solution compares well to the data and discuss our model as a tool for further model development.
Christian Ferrarin, Marco Bajo, and Georg Umgiesser
Geosci. Model Dev., 14, 645–659,Short summary
The problem of the optimization of ocean monitoring networks is tackled through the implementation of data assimilation techniques in a numerical model. The methodology has been applied to the tide gauge network in the Lagoon of Venice (Italy). The data assimilation methods allow identifying the minimum number of stations and their distribution that correctly represent the lagoon's dynamics. The methodology is easily exportable to other environments and can be extended to other variables.
Florian Lemarié, Guillaume Samson, Jean-Luc Redelsperger, Hervé Giordani, Théo Brivoal, and Gurvan Madec
Geosci. Model Dev., 14, 543–572,Short summary
A simplified model of the atmospheric boundary layer (ABL) of intermediate complexity between a bulk parameterization and a full three-dimensional atmospheric model has been developed and integrated to the NEMO ocean model. An objective in the derivation of such a simplified model is to reach an apt representation of ocean-only numerical simulations of some of the key processes associated with air–sea interactions at the characteristic scales of the oceanic mesoscale.
Kristen M. Thyng, Daijiro Kobashi, Veronica Ruiz-Xomchuk, Lixin Qu, Xu Chen, and Robert D. Hetland
Geosci. Model Dev., 14, 391–407,Short summary
We modified the ROMS model to run in offline mode so that previously run fields of sea surface height and velocity fields are input to calculate tracer advection without running the full model with a larger time step; thus, it is faster. The code was tested with two advection schemes, and both are robust with over 99 % accuracy of the offline to online run after 14 simulation days. This allows for ROMS users to maximize use of new or existing output to quickly run additional tracer simulations.
Katixa Lajaunie-Salla, Frédéric Diaz, Cathy Wimart-Rousseau, Thibaut Wagener, Dominique Lefèvre, Christophe Yohia, Irène Xueref-Remy, Brian Nathan, Alexandre Armengaud, and Christel Pinazo
Geosci. Model Dev., 14, 295–321,Short summary
A biogeochemical model of planktonic food webs including a carbonate balance module is applied in the Bay of Marseille (France) to represent the carbon marine cycle expected to change in the future owing to significant increases in anthropogenic emissions of CO2. The model correctly simulates the ranges and seasonal dynamics of most variables of the carbonate system (pH). This study shows that external physical forcings have an important impact on the carbonate equilibrium in this coastal area.
Katsumi Matsumoto, Tatsuro Tanioka, and Jacob Zahn
Geosci. Model Dev. Discuss.,
Revised manuscript accepted for GMDShort summary
MESMO is a mathematical model that represents the essential components of Earth such as the global ocean, atmosphere, and sea ice. It is used to study the global climate and the global carbon cycle. We describe the third version of MESMO. A novel feature of the new version has mathematical representations of the chemical composition of marine phytoplankton and the marine dissolved organic matter, which are both recognized as important for the global ocean carbon cycle.
Tor Nordam and Rodrigo Duran
Geosci. Model Dev., 13, 5935–5957,Short summary
In applied oceanography, a common task is to calculate the trajectory of objects floating at the sea surface or submerged in the water. We have investigated different numerical methods for doing such calculations and discuss the benefits and challenges of some common methods. We then propose a small change to some common methods that make them more efficient for this particular application. This will allow researchers to obtain more accurate answers with fewer computer resources.
Chia-Wei Hsu, Jianjun Yin, Stephen M. Griffies, and Raphael Dussin
Geosci. Model Dev. Discuss.,
Revised manuscript accepted for GMDShort summary
The new surface forcing from JRA55-do (OMIP II) significantly improved the underestimated sea level trend across the entire Pacific ocean along 10° N in the simulation forced by CORE (OMIP I). We summarize and list out the reasons for the existing sea level biases across all studied time scales as a reference for improving the sea level simulation in the future. This study about the evaluation and improvement of ocean climate models should be of broad interest to a large modeling community.
Clément Bricaud, Julien Le Sommer, Gurvan Madec, Christophe Calone, Julie Deshayes, Christian Ethe, Jérôme Chanut, and Marina Levy
Geosci. Model Dev., 13, 5465–5483,Short summary
In order to reduce the cost of ocean biogeochemical models, a multi-grid approach where ocean dynamics and tracer transport are computed with different spatial resolution has been developed in the NEMO v3.6 OGCM. Different experiments confirm that the spatial resolution of hydrodynamical fields can be coarsened without significantly affecting the resolved passive tracer fields. This approach leads to a factor of 7 reduction of the overhead associated with running a full biogeochemical model.
Lojze Žust, Anja Fettich, Matej Kristan, and Matjaž Ličer
Geosci. Model Dev. Discuss.,
Revised manuscript accepted for GMDShort summary
Adriatic basin sea level modeling is a challenging problem due to the interplay between terrain, weather, tides and seiches. Current state-of-the-art numerical models (e.g. NEMO) require large computational resources to produce reliable forecasts. In this study we propose HIDRA, a novel deep learning approach for sea level modeling, which drastically reduces the numerical cost while demonstrating predictive capabilities comparable to that of the NEMO model, outperforming it in many instances.
Clark Pennelly and Paul G. Myers
Geosci. Model Dev., 13, 4959–4975,Short summary
A high-resolution ocean simulation was carried out within the Labrador Sea, a region that low-resolution climate simulations may misrepresent. We show that small-scale eddies and their associated transport are better resolved at higher resolution than at lower resolution. These eddies transport important properties to the interior of the Labrador Sea, impacting the stratification and reducing the convection extent so that it is far more accurate when compared to what observations suggest.
Eric P. Chassignet, Stephen G. Yeager, Baylor Fox-Kemper, Alexandra Bozec, Frederic Castruccio, Gokhan Danabasoglu, Christopher Horvat, Who M. Kim, Nikolay Koldunov, Yiwen Li, Pengfei Lin, Hailong Liu, Dmitry V. Sein, Dmitry Sidorenko, Qiang Wang, and Xiaobiao Xu
Geosci. Model Dev., 13, 4595–4637,Short summary
This paper presents global comparisons of fundamental global climate variables from a suite of four pairs of matched low- and high-resolution ocean and sea ice simulations to assess the robustness of climate-relevant improvements in ocean simulations associated with moving from coarse (∼1°) to eddy-resolving (∼0.1°) horizontal resolutions. Despite significant improvements, greatly enhanced horizontal resolution does not deliver unambiguous bias reduction in all regions for all models.
Mark E. Baird, Karen A. Wild-Allen, John Parslow, Mathieu Mongin, Barbara Robson, Jennifer Skerratt, Farhan Rizwi, Monika Soja-Woźniak, Emlyn Jones, Mike Herzfeld, Nugzar Margvelashvili, John Andrewartha, Clothilde Langlais, Matthew P. Adams, Nagur Cherukuru, Malin Gustafsson, Scott Hadley, Peter J. Ralph, Uwe Rosebrock, Thomas Schroeder, Leonardo Laiolo, Daniel Harrison, and Andrew D. L. Steven
Geosci. Model Dev., 13, 4503–4553,Short summary
For 20+ years, the Commonwealth Science Industry and Research Organisation (CSIRO) has been developing a biogeochemical (BGC) model for coupling with a hydrodynamic and sediment model for application in estuaries, coastal waters and shelf seas. This paper provides a full mathematical description (equations, parameters), model evaluation and access to the numerical code. The model is particularly suited to applications in shallow waters where benthic processes are critical to ecosystem function.
Angela A. Bahamondes Dominguez, Anna E. Hickman, Robert Marsh, and C. Mark Moore
Geosci. Model Dev., 13, 4019–4040,Short summary
The central Celtic Sea has previously been studied with a 1-D model called S2P3, showing discrepancies between observations and the model results due to poor representation of some processes. Therefore, the S2P3 model was developed to include zooplankton and phytoplankton cells' adaptation to changes in irradiance. Results demonstrate that better agreement with biological observations can be achieved when the model includes these processes and is adequately constrained.
Oliver Gutjahr, Nils Brüggemann, Helmuth Haak, Johann H. Jungclaus, Dian A. Putrasahan, Katja Lohmann, and Jin-Song von Storch
Geosci. Model Dev. Discuss.,
Revised manuscript accepted for GMDShort summary
We compare four ocean vertical mixing schemes in 100-year long coupled simulations with the Max Planck Institute Earth System Model (MPI-ESM1.2) and analyse their model biases. Overall, the mixing schemes modify biases in the ocean interior that vary with region and variable, but produce a similar global bias pattern. We therefore cannot classify any scheme as superior, but conclude that the chosen mixing scheme may be important for regional biases.
Alexander G. López, John L. Wilkin, and Julia C. Levin
Geosci. Model Dev., 13, 3709–3729,Short summary
This article describes a regional circulation model, Doppio, for the Mid-Atlantic Bight and the Gulf of Maine. The model demonstrates useful skill in comparison to a comprehensive suite of observations. Development focused on achieving a model configuration that allows decadal-scale simulations of physical ocean circulation that can underpin studies of ecosystems and biogeochemistry. Doppio captures the temperature and salinity stratification well, along with the large-scale mean circulation.
Hiroyuki Tsujino, L. Shogo Urakawa, Stephen M. Griffies, Gokhan Danabasoglu, Alistair J. Adcroft, Arthur E. Amaral, Thomas Arsouze, Mats Bentsen, Raffaele Bernardello, Claus W. Böning, Alexandra Bozec, Eric P. Chassignet, Sergey Danilov, Raphael Dussin, Eleftheria Exarchou, Pier Giuseppe Fogli, Baylor Fox-Kemper, Chuncheng Guo, Mehmet Ilicak, Doroteaciro Iovino, Who M. Kim, Nikolay Koldunov, Vladimir Lapin, Yiwen Li, Pengfei Lin, Keith Lindsay, Hailong Liu, Matthew C. Long, Yoshiki Komuro, Simon J. Marsland, Simona Masina, Aleksi Nummelin, Jan Klaus Rieck, Yohan Ruprich-Robert, Markus Scheinert, Valentina Sicardi, Dmitry Sidorenko, Tatsuo Suzuki, Hiroaki Tatebe, Qiang Wang, Stephen G. Yeager, and Zipeng Yu
Geosci. Model Dev., 13, 3643–3708,Short summary
The OMIP-2 framework for global ocean–sea-ice model simulations is assessed by comparing multi-model means from 11 CMIP6-class global ocean–sea-ice models calculated separately for the OMIP-1 and OMIP-2 simulations. Many features are very similar between OMIP-1 and OMIP-2 simulations, and yet key improvements in transitioning from OMIP-1 to OMIP-2 are also identified. Thus, the present assessment justifies that future ocean–sea-ice model development and analysis studies use the OMIP-2 framework.
Pedro Colombo, Bernard Barnier, Thierry Penduff, Jérôme Chanut, Julie Deshayes, Jean-Marc Molines, Julien Le Sommer, Polina Verezemskaya, Sergey Gulev, and Anne-Marie Treguier
Geosci. Model Dev., 13, 3347–3371,Short summary
In the ocean circulation model NEMO, the representation of the overflow of dense Arctic waters through the Denmark Strait is investigated. In this z-coordinate context, sensitivity tests show that the mixing parameterizations preferably act along the model grid slope. Thus, the representation of the overflow is more sensitive to resolution than to parameterization and is best when the numerical grid matches the local topographic slope.
Hideharu Sasaki, Shinichiro Kida, Ryo Furue, Hidenori Aiki, Nobumasa Komori, Yukio Masumoto, Toru Miyama, Masami Nonaka, Yoshikazu Sasai, and Bunmei Taguchi
Geosci. Model Dev., 13, 3319–3336,Short summary
A quasi-global eddying ocean hindcast simulation using a new version of our model, called OFES2, was conducted to overcome several issues in its previous version. OFES2 simulated oceanic fields from 1958 to 2016 with improved global sea surface temperature and salinity, water mass properties in the Indonesian and Arabian seas, and Niño3.4 and Indian Ocean Dipole indexes. The output from OFES2 will be useful in studying various oceanic phenomena with broad spatiotemporal scales.
Katherine M. Smith, Skyler Kern, Peter E. Hamlington, Marco Zavatarelli, Nadia Pinardi, Emily F. Klee, and Kyle E. Niemeyer
Geosci. Model Dev. Discuss.,
Revised manuscript accepted for GMDShort summary
We present a newly developed reduced-order biogeochemical flux model that is complex and flexible enough to capture open-ocean ecosystem dynamics, but reduced enough to incorporate into highly resolved numerical simulations with limited additional computational cost. The model provides improved correlations between model output and field data, indicating that significant improvements in the reproduction of real-world data can be achieved with a small number of variables.
Dafydd Stephenson, Simon A. Müller, and Florian Sévellec
Geosci. Model Dev., 13, 2031–2050,Short summary
Different water types are created at the sea surface with a signature based on the local conditions of the atmosphere. They then take these conditions with them into the deeper ocean, and so their journey is an important climate process to understand. In this study, we modify and repurpose a specialised model which simulates the ocean forward and backward in time to determine where new ocean water goes, where at the surface existing water comes from, and how old it is, by tracking it as a dye.
Violaine Piton, Marine Herrmann, Florent Lyard, Patrick Marsaleix, Thomas Duhaut, Damien Allain, and Sylvain Ouillon
Geosci. Model Dev., 13, 1583–1607,Short summary
Consequences of tidal dynamics on hydro-sedimentary processes are a recurrent issue in estuarine and coastal processes studies, and accurate tidal solutions are a prerequisite for modeling sediment transport. This study presents the implementation and optimization of a model configuration in terms of bathymetry and bottom friction and assess the influence of these parameters on tidal solutions, in a macro-tidal environment: the Gulf of Tonkin (Vietnam).
Alexander Barth, Aida Alvera-Azcárate, Matjaz Licer, and Jean-Marie Beckers
Geosci. Model Dev., 13, 1609–1622,Short summary
DINCAE is a method for reconstructing missing data in satellite datasets using a neural network. Satellite observations working in the optical and infrared bands are affected by clouds, which obscure part of the ocean underneath. In this paper, a neural network with the structure of a convolutional auto-encoder is developed to reconstruct the missing data based on the available cloud-free pixels in satellite images.
Jiangyu Li and Shaoqing Zhang
Geosci. Model Dev., 13, 1035–1054,Short summary
Two assimilation systems developed using two nearly independent wave models are used to study the influences of various error sources including mode bias on wave data assimilation; a statistical method is explored to make full use of the merits of individual assimilation systems for bias correction, thus improving wave analysis greatly. This study opens a door to further our understanding of physical processes in waves and associated air–sea interactions for improving wave modeling.
Heiner Dietze, Ulrike Löptien, and Julia Getzlaff
Geosci. Model Dev., 13, 71–97,Short summary
We present a new near-global coupled biogeochemical ocean-circulation model configuration of the Southern Ocean. The configuration features both a relatively equilibrated oceanic carbon inventory and an explicit representation of mesoscale eddies. In this paper, we document the model configuration and showcase its potential to tackle research questions such as the Southern Ocean carbon uptake dynamics on decadal timescales.
Jaap H. Nienhuis and Jorge Lorenzo-Trueba
Geosci. Model Dev., 12, 4013–4030,Short summary
The response of barrier islands to sea level rise depends on their ability to move landward through the transport of sediment from the beach to the back barrier. The BRIE model simulates these processes and the resulting landward movement of barrier islands. The novelty of the BRIE model is the incorporation of tidal inlets (gaps between barrier islands) that can transport sediment landward and therefore help keep barrier islands above sea level.
Geosci. Model Dev., 12, 3915–3922,Short summary
Operational forecasting of the ocean state – e.g. used for ship route planning, sea rescue, and oil spill drift models – relies on data (forcing) obtained from weather forecasting. Unfortunately, the so-called meteorological analysis step introduces a discontinuity, which affects the ocean models adversely. In the present paper, a straightforward method to deal with the issue is introduced. Practical examples are given to illuminate the scale of the problem.
Philippe Delandmeter and Erik van Sebille
Geosci. Model Dev., 12, 3571–3584,Short summary
Parcels is a framework to compute how ocean currents transport
stuffsuch as plankton and plastic around. In the latest version 2.0 of Parcels, we focus on more accurate interpolation schemes and implement methods to seamlessly combine data from different sources (such as winds and currents, possibly in different regions). We show that this framework is very efficient for tracking how microplastic is transported through the North Sea into the Arctic.
Franziska U. Schwarzkopf, Arne Biastoch, Claus W. Böning, Jérôme Chanut, Jonathan V. Durgadoo, Klaus Getzlaff, Jan Harlaß, Jan K. Rieck, Christina Roth, Markus M. Scheinert, and René Schubert
Geosci. Model Dev., 12, 3329–3355,Short summary
A family of nested global ocean general circulation model configurations, the INALT family, has been established with resolutions of 1/10°, 1/20° and 1/60° in the South Atlantic and western Indian oceans, covering the greater Agulhas Current (AC) system. The INALT family provides a consistent set of configurations that allows to address eddy dynamics in the AC system and their impact on the large-scale ocean circulation.
Thomas Rackow, Dmitry V. Sein, Tido Semmler, Sergey Danilov, Nikolay V. Koldunov, Dmitry Sidorenko, Qiang Wang, and Thomas Jung
Geosci. Model Dev., 12, 2635–2656,Short summary
Current climate models show errors in the deep ocean that are larger than the level of natural variability and the response to enhanced greenhouse gas concentrations. These errors are larger than the signals we aim to predict. With the AWI Climate Model, we show that increasing resolution to resolve eddies can lead to major reductions in deep ocean errors. AWI's next-generation (CMIP6) model configuration will thus use locally eddy-resolving computational grids for projecting climate change.
Keith J. Roberts, William J. Pringle, and Joannes J. Westerink
Geosci. Model Dev., 12, 1847–1868,Short summary
Computer simulations can be used to reproduce the dynamics of the ocean near the coast. These simulations often use a mesh of triangles to represent the domain since they can be orientated and disparately sized in such a way to accurately fit the coastline shape. This paper describes a software package (OceanMesh2D v1.0) that has been developed in order to automatically and objectively design triangular meshes based on geospatial data inputs that represent the coastline and ocean depths.
Pearse J. Buchanan, Richard J. Matear, Zanna Chase, Steven J. Phipps, and Nathan L. Bindoff
Geosci. Model Dev., 12, 1491–1523,Short summary
Oceanic sediment cores are commonly used to understand past climates. The composition of the sediments changes with the ocean above it. An understanding of oceanographic conditions that existed many thousands of years ago, in some cases many millions of years ago, can therefore be extracted from sediment cores. We simulate two chemical signatures (13C and 15N) of sediment cores in a model. This study assesses the model before it is applied to reinterpret the sedimentary record.
Carlos Rocha, Christopher A. Edwards, Moninya Roughan, Paulina Cetina-Heredia, and Colette Kerry
Geosci. Model Dev., 12, 441–456,Short summary
Off southeast Australia, the East Australian Current (EAC) moves warm nutrient-poor waters towards the pole. In this region, the EAC and a large number of vortices pinching off it strongly affect phytoplankton’s access to nutrients and light. To study these dynamics, we created a numerical model that is able to solve the ocean conditions and how they modulate the foundation of the region’s ecosystem. We validated model results against available data and this showed that the model performs well.
Robinson Hordoir, Lars Axell, Anders Höglund, Christian Dieterich, Filippa Fransner, Matthias Gröger, Ye Liu, Per Pemberton, Semjon Schimanke, Helen Andersson, Patrik Ljungemyr, Petter Nygren, Saeed Falahat, Adam Nord, Anette Jönsson, Iréne Lake, Kristofer Döös, Magnus Hieronymus, Heiner Dietze, Ulrike Löptien, Ivan Kuznetsov, Antti Westerlund, Laura Tuomi, and Jari Haapala
Geosci. Model Dev., 12, 363–386,Short summary
Nemo-Nordic is a regional ocean model based on a community code (NEMO). It covers the Baltic and the North Sea area and is used as a forecast model by the Swedish Meteorological and Hydrological Institute. It is also used as a research tool by scientists of several countries to study, for example, the effects of climate change on the Baltic and North seas. Using such a model permits us to understand key processes in this coastal ecosystem and how such processes will change in a future climate.
Hagen Radtke, Marko Lipka, Dennis Bunke, Claudia Morys, Jana Woelfel, Bronwyn Cahill, Michael E. Böttcher, Stefan Forster, Thomas Leipe, Gregor Rehder, and Thomas Neumann
Geosci. Model Dev., 12, 275–320,Short summary
This paper describes a coupled benthic–pelagic biogeochemical model, ERGOM-SED. We demonstrate its use in a one-dimensional physical model, which is horizontally integrated and vertically resolved. We describe the application of the model to seven stations in the south-western Baltic Sea. The model was calibrated using pore water profiles from these stations. We compare the model results to these and to measured sediment compositions, benthopelagic fluxes and bioturbation intensities.
Dale Partridge, Tobias Friedrich, and Brian S. Powell
Geosci. Model Dev., 12, 195–213,Short summary
This paper demonstrates the improvements made to an operational ocean forecast model around the Hawaiian Islands by performing a reanalysis of the model over a 10-year period. Using a number of different measurements we show the role a variety of observations play in producing the forecast, in particular the contribution of high-frequency radar.
Tuomas Kärnä, Stephan C. Kramer, Lawrence Mitchell, David A. Ham, Matthew D. Piggott, and António M. Baptista
Geosci. Model Dev., 11, 4359–4382,Short summary
Unstructured meshes are attractive for coastal ocean modeling, as they allow more accurate representation of complex coastal topography. Unstructured mesh models are, however, often perceived as slow and inaccurate. We present a novel discontinuous Galerkin ocean model: Thetis. We demonstrate that the model is able to simulate baroclinic ocean flows with high accuracy on a triangular prismatic mesh. This work paves the way for highly accurate and efficient three-dimensional coastal ocean models.
Geosci. Model Dev., 11, 4011–4019,Short summary
This article compares global mesoscale ocean forecasts with different data assimilation cycle lengths. Mean absolute increment is used to quantify differences in the overall impact of observations. Greater observation impact does not necessarily improve a forecast system. Experiments show a 1-day cycle generates improved 7-day forecasts when compared to a 3-day cycle. Cycle length is an important choice that influences system bias and predictability.
Daniel Boettger, Robin Robertson, and Gary B. Brassington
Geosci. Model Dev., 11, 3795–3805,Short summary
This study focuses on the impact of the model vertical mixing parameterisation on the representation of the mixed layer depth (MLD) in ocean forecast models. We compare data from two recent versions of the OceanMAPS forecast system, and find that while there were large improvements in the later version of the model, the skill of each parameterisation varies with spatial location.
Marco van Hulten, Jean-Claude Dutay, and Matthieu Roy-Barman
Geosci. Model Dev., 11, 3537–3556,Short summary
We present an ocean model of the natural radioactive isotopes thorium-230 and protactinium-231. These isotopes are often used to investigate past ocean circulation and particle transport. They are removed by particles produced by plankton and from uplifted desert dust that is deposited into the ocean. We approach observed dissolved and adsorbed Th-230 and Pa-231 activities. The Pa-231 / Th-230 sedimentation ratio is reproduced as well; this quantity can be used as a proxy for ocean circulation.
Dion Häfner, René Løwe Jacobsen, Carsten Eden, Mads R. B. Kristensen, Markus Jochum, Roman Nuterman, and Brian Vinter
Geosci. Model Dev., 11, 3299–3312,Short summary
Well-performing, easy-to-use ocean models are a central ingredient to further the understanding of our Earth and climate. Veros, the versatile ocean simulator, is the first full-blown ocean model entirely written in the high-level programming language Python. It is considerably more approachable than traditional Fortran models and leverages modern best practices; at the same time, thanks to the Bohrium framework, Veros is about half as fast as a reference implementation in Fortran 90.
Christopher R. Sherwood, Alfredo L. Aretxabaleta, Courtney K. Harris, J. Paul Rinehimer, Romaric Verney, and Bénédicte Ferré
Geosci. Model Dev., 11, 1849–1871,Short summary
Cohesive sediment (mud) is ubiquitous in the world's coastal regions, but its behavior is complicated and often oversimplified by computer models. This paper describes extensions to a widely used open-source coastal ocean model that allow users to simulate important components of cohesive sediment transport.
Knut-Frode Dagestad, Johannes Röhrs, Øyvind Breivik, and Bjørn Ådlandsvik
Geosci. Model Dev., 11, 1405–1420,Short summary
We have developed a computer code with ability to predict how various substances and objects drift in the ocean. This may be used to, e.g. predict the drift of oil to aid cleanup operations, the drift of man-over-board or lifeboats to aid search and rescue operations, or the drift of fish eggs and larvae to understand and manage fish stocks. This new code merges all such applications into one software tool, allowing to optimise and channel any available resources and developments.
Qiang Wang, Claudia Wekerle, Sergey Danilov, Xuezhu Wang, and Thomas Jung
Geosci. Model Dev., 11, 1229–1255,Short summary
For developing a system for Arctic research, we evaluate the Arctic Ocean simulated by FESOM. We use two global meshes differing in the horizontal resolution only in the Arctic Ocean (24 vs. 4.5 km). The high resolution significantly improves the model's representation of the Arctic Ocean. The most pronounced improvement is in the Arctic intermediate layer. The high resolution also improves the ocean surface circulation, mainly through a better representation of the Canadian Arctic Archipelago.
Jennifer A. Graham, Enda O'Dea, Jason Holt, Jeff Polton, Helene T. Hewitt, Rachel Furner, Karen Guihou, Ashley Brereton, Alex Arnold, Sarah Wakelin, Juan Manuel Castillo Sanchez, and C. Gabriela Mayorga Adame
Geosci. Model Dev., 11, 681–696,Short summary
This paper describes the next-generation ocean forecast model for the European NW shelf, AMM15 (Atlantic Margin Model, 1.5 km resolution). The current forecast system has a resolution of 7 km. While this is sufficient to represent large-scale circulation, many dynamical features (such as eddies, frontal jets, and internal tides) can only begin to be resolved at 0–1 km resolution. Here we introduce AMM15 and demonstrate its ability to represent the mean state and variability of the region.
Adcroft, A. and Campin, J.-M.: Rescaled height coordinates for accurate representation of free-surface flows in ocean circulation models, Ocean Model., 7, 269–284, https://doi.org/10.1016/j.ocemod.2003.09.003, 2004.
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, 2004.
Banas, N. S., MacCready, P., and Hickey, B. M.: The Columbia River plume as cross-shelf exporter and along-coast barrier, Cont. Shelf Res., 2, 292–301, https://doi.org/10.1016/j.csr.2008.03.011, 2009.
Barichivich, J., Gloor, E., Peylin, P., Brienen, R. J. W., Schöngart, J., Espinoza, J. C., and Pattnayak, K. C.: Recent intensification of Amazon flooding extremes driven by strengthened Walker circulation, Sci. Adv., 4, eaat8785, https://doi.org/10.1126/sciadv.aat8785, 2018.
Bentsen, M., Bethke, I., Debernard, J. B., Iversen, T., Kirkevåg, A., Seland, Ø., Drange, H., Roelandt, C., Seierstad, I. A., Hoose, C., and Kristjánsson, J. E.: The Norwegian Earth System Model, NorESM1-M – Part 1: Description and basic evaluation of the physical climate, Geosci. Model Dev., 6, 687–720, https://doi.org/10.5194/gmd-6-687-2013, 2013.
Bourgeois, T., Orr, J. C., Resplandy, L., Terhaar, J., Ethé, C., Gehlen, M., and Bopp, L.: Coastal-ocean uptake of anthropogenic carbon, Biogeosciences, 13, 4167–4185, https://doi.org/10.5194/bg-13-4167-2016, 2016.
Campin, J.-M., Marshall, J., and Ferreira, D.: Sea ice–ocean coupling using a rescaled vertical coordinate z∗, Ocean Model., 24, 1–14, https://doi.org/10.1016/j.ocemod.2008.05.005, 2008.
Carroll, D., Menemenlis, Adkins, J. F., Bowman, K. W., Brix, H., Dutkiewicz, S., Gierach, M. M., Hill, C., Jahn, O., Landschützer, P., Lauderdale, J. Liu, J. M., Naviaux, J. D., Manizza, M., Rödenbeck, C., Schimel, D. S., Van der Stocken, T., and Zhang, H.: The ECCO‐Darwin data‐assimilative global ocean biogeochemistry model: Estimates of seasonal to multidecadal surface ocean pCO2 and air‐sea CO2 flux, J. Adv. Model. Earth Sy., 12, e2019MS001888, https://doi.org/10.1029/2019MS001888, 2020.
Chao, S.-Y.: River-forced estuarine plumes, J. Phys. Oceanogr., 18, 72–88, https://doi.org/10.1175/1520-0485(1988)018<0072:RFEP>2.0.CO;2, 1988a.
Chao, S.-Y.: Wind-driven motion of estuarine plumes, J. Phys. Oceanogr., 18, 1144–1166, https://doi.org/10.1175/1520-0485(1988)018<1144:WDMOEP>2.0.CO;2; 1988b.
Cione, J. J. and Uhlhorn, E. W.: Sea surface temperature variability in hurricanes: Implications with respect to intensity change, Mon. Weather Rev., 131, 1783–1796, https://doi.org/10.1175//2562.1, 2003.
de Boyer Montégut, C., Madec, G., Fischer, A. S., Lazar, A., and Ludicone, D.: Mixed layer depth over the global ocean: An examination of profile data and a profile-based climatology, J. Geophys. Res.-Oceans, 109, C12003, https://doi.org/10.1029/2004jc002378, 2004.
Denamiel, C., Budgell, W. P., and Toumi, R.: The Congo River plume: Impact of the forcing on the far-field and near-field dynamics, J. Geophys. Res.-Oceans, 118, 964–989, https://doi.org/10.1002/jgrc.20062, 2013.
Du, Y. and Zhang, Y.: Satellite and Argo Observed Surface Salinity Variations in the Tropical Indian Ocean and Their Association with the Indian Ocean Dipole Mode, J. Climate, 28, 695–713, https://doi.org/10.1175/JCLI-D-14-00435.1, 2015.
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, 15-11–15-10, https://doi.org/10.1029/1999gb001254, 2002.
Feng, Y.: Improved representation of river runoff in ECCOv4 simulations: implementation, evaluation and impacts to coastal plume regions, Zenodo, https://doi.org/10.5281/zenodo.4106405, 2020.
Feng, Y., DiMarco, S. F., Balaguru, K., and Xue, H.: Seasonal and interannual variability of areal extent of the Gulf of Mexico hypoxia from a coupled physical-biogeochemical model: A new implication for management practice, J. Geophys. Res.-Biogeo., 124, 1939–1960, https://doi.org/10.1029/2018JG004745, 2019.
Fennel, K., Alin, S., Barbero, L., Evans, W., Bourgeois, T., Cooley, S., Dunne, J., Feely, R. A., Hernandez-Ayon, J. M., Hu, X., Lohrenz, S., Muller-Karger, F., Najjar, R., Robbins, L., Shadwick, E., Siedlecki, S., Steiner, N., Sutton, A., Turk, D., Vlahos, P., and Wang, Z. A.: Carbon cycling in the North American coastal ocean: a synthesis, Biogeosciences, 16, 1281–1304, https://doi.org/10.5194/bg-16-1281-2019, 2019.
Fong, D. A. and Geyer, W. R.: Response of a river plume during an upwelling favorable wind event, J. Geophys. Res.-Oceans, 106, 1067–1084, https://doi.org/10.1029/2000jc900134, 2001.
Fong, D. A. and Geyer, W. R.: The Alongshore Transport of Freshwater in a Surface-Trapped River Plume, J. Phys. Oceanogr., 32, 957–972, https://doi.org/10.1175/1520-0485(2002)032<0957:TATOFI>2.0.CO;2, 2002.
Forget, G., Campin, J.-M., Heimbach, P., Hill, C. N., Ponte, R. M., and Wunsch, C.: ECCO version 4: an integrated framework for non-linear inverse modeling and global ocean state estimation, Geosci. Model Dev., 8, 3071–3104, https://doi.org/10.5194/gmd-8-3071-2015, 2015.
Fournier, S., Reager, J. T., Lee, T., Vazquez-Cuervo, J., David, C. H., and Gierach, M. M.: SMAP observes flooding from land to sea: The Texas event of 2015, Geophys. Res. Lett. 43, L070821, https://doi.org/10.1002/2016GL070821, 2016a.
Fournier, S., Vialard, J., Lengaigne, M., Lee, T., Gierach, M. M., and Chaitanya, A. V. S.: Modulation of the Ganges-Brahmaputra river plume by the Indian Ocean dipole and eddies inferred from satellite observations, J. Geophys. Res.-Oceans, 122, 9591–9604, https://doi.org/10.1002/2017JC013333, 2017a.
Fournier, S., Vandemark, D., Gaultier, L., Lee, T., Jonsson, B., and Gierach, M. M.: Interannual variation in offshore advection of Amazon-Orinoco plume waters: Observations, forcing mechanisms, and impacts, J. Geophys. Res.-Oceans, 122, 8966–8982, https://doi.org/10.1002/2017JC013103, 2017b.
Friedlingstein, P., Jones, M. W., O'Sullivan, M., Andrew, R. M., Hauck, J., Peters, G. P., Peters, W., Pongratz, J., Sitch, S., Le Quéré, C., Bakker, D. C. E., Canadell, J. G., Ciais, P., Jackson, R. B., Anthoni, P., Barbero, L., Bastos, A., Bastrikov, V., Becker, M., Bopp, L., Buitenhuis, E., Chandra, N., Chevallier, F., Chini, L. P., Currie, K. I., Feely, R. A., Gehlen, M., Gilfillan, D., Gkritzalis, T., Goll, D. S., Gruber, N., Gutekunst, S., Harris, I., Haverd, V., Houghton, R. A., Hurtt, G., Ilyina, T., Jain, A. K., Joetzjer, E., Kaplan, J. O., Kato, E., Klein Goldewijk, K., Korsbakken, J. I., Landschützer, P., Lauvset, S. K., Lefèvre, N., Lenton, A., Lienert, S., Lombardozzi, D., Marland, G., McGuire, P. C., Melton, J. R., Metzl, N., Munro, D. R., Nabel, J. E. M. S., Nakaoka, S.-I., Neill, C., Omar, A. M., Ono, T., Peregon, A., Pierrot, D., Poulter, B., Rehder, G., Resplandy, L., Robertson, E., Rödenbeck, C., Séférian, R., Schwinger, J., Smith, N., Tans, P. P., Tian, H., Tilbrook, B., Tubiello, F. N., van der Werf, G. R., Wiltshire, A. J., and Zaehle, S.: Global Carbon Budget 2019, Earth Syst. Sci. Data, 11, 1783–1838, https://doi.org/10.5194/essd-11-1783-2019, 2019.
García Berdeal, I., Hickey, B. M., and Kawase, M.: Influence of wind stress and ambient flow on a high discharge river plume, J. Geophys. Res.-Oceans, 107, 13-11–13-24, https://doi.org/10.1029/2001jc000932, 2002.
Garvine, R. W.: Penetration of buoyant coastal discharge onto the continental shelf: a numerical model experiment, J. Phys. Oceanogr., 29, 1892–1909, https://doi.org/10.1175/1520-0485(1999)029<1892:POBCDO>2.0.CO;2, 1999.
Garvine, R. W.: The impact of model configuration in studies of buoyant coastal discharge, J. Marine Resh., 59, 193–225, https://doi.org/10.1357/002224001762882637, 2001.
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.-Oceans, 95, 16179–16193, https://doi.org/10.1029/JC095iC09p16179, 1990.
Gierach, M. M., Vazquez-Cuervo, J., Lee, T., and Tsontos, V. M.: Aquarius and SMOS detect effects of an extreme Mississippi River flooding event in the Gulf of Mexico, Geophys. Res. Lett., 40, L50995, https://doi.org/10.1002/grl.50995, 2013.
Griffies, S. M., Gnanadesikan, A., Dixon, K. W., Dunne, J. P., Gerdes, R., Harrison, M. J., Rosati, A., Russell, J. L., Samuels, B. L., Spelman, M. J., Winton, M., and Zhang, R.: Formulation of an ocean model for global climate simulations, Ocean Sci., 1, 45–79, https://doi.org/10.5194/os-1-45-2005, 2005.
Halliwell, G. R.: Evaluation of vertical coordinate and vertical mixing algorithms in the HYbrid-Coordinate Ocean Model (HYCOM), Ocean Model., 7, 285–322, https://doi.org/10.1016/j.ocemod.2003.10.002, 2004.
Herzfeld, M.: Methods for freshwater riverine input into regional ocean models, Ocean Model., 90, 1–15, https://doi.org/10.1016/j.ocemod.2015.04.001, 2015.
Huang, R. X.: Real Freshwater Flux as a Natural Boundary Condition for the Salinity Balance and Thermohaline Circulation Forced by Evaporation and Precipitation, J. Phys. Oceanogr., 23, 2428–2446, https://doi.org/10.1175/1520-0485(1993)023<2428:RFFAAN>2.0.CO;2, 1993.
IPCC: Summary for Policymakers, in: Climate Change and Land: an IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems, edited by: Shukla, P. R., Skea, J., Calvo Buendia, E., Masson-Delmotte, V., Pörtner, H.-O., Roberts, D. C., Zhai, P., Slade, R., Connors, S., van Diemen, R., Ferrat, M., Haughey, E., Luz, S., Neogi, S., Pathak, M., Petzold, J., Portugal Pereira, J., Vyas, P., Huntley, E., Kissick, K., Belkacemi, M., and Malley, J., in press, 2021.
Jolliff, J. K., Kindle, J. C., Shulman, I., Penta, B., Friedrichs, M. A. M., Helber, R., and Arnone, R. A.: Summary diagrams for coupled hydrodynamic-ecosystem model skill assessment, J. Marine Syst., 76, 64–82, https://doi.org/10.1016/j.jmarsys.2008.05.014, 2009.
Kourafalou, V. H., Oey, L.-Y., Wang, J. D., and Lee, T. N.: The fate of river discharge on the continental shelf: 1. Modeling the river plume and the inner shelf coastal current, J. Geophys. Res., 101, 3415–3434, https://doi.org/10.1029/95JC03024, 1996.
Lacroix, F., Ilyina, T., and Hartmann, J.: Oceanic CO2 outgassing and biological production hotspots induced by pre-industrial river loads of nutrients and carbon in a global modeling approach, Biogeosciences, 17, 55–88, https://doi.org/10.5194/bg-17-55-2020, 2020.
Landschützer, P., Laruelle, G. G., Roobaert, A., and Regnier, P.: A uniform pCO2 climatology combining open and coastal oceans, Earth Syst. Sci. Data, 12, 2537–2553, https://doi.org/10.5194/essd-12-2537-2020, 2020.
Lentz, S. J.: The Amazon River plume during AMASSEDS: subtidal current variability and the importance of wind forcing, J. Geophys. Res.-Oceans, 100, 2377–2390, https://doi.org/10.1029/94JC00343, 1995a.
Lentz, S. J.: Seasonal variations in the horizontal structure of the Amazon plume inferred from historical hydrographic data, J. Geophys. Res.-Oceans, 100, 2391–2400, https://doi.org/10.1029/94JC01847, 1995b.
Liang, L., Xue, H., and Shu, Y.: The Indonesian throughflow and the circulation in the Banda Sea: A modeling study, J. Geophys. Res.-Oceans, 124, 3089–3106, https://doi.org/10.1029/2018JC014926, 2019.
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.-Oceans, 102, 5753–5766, https://doi.org/10.1029/96jc02775, 1997.
Mecklenburg, S., Drusch, M., Kerr, Y. H., Font, J., Martin-Neira, M., Delwart, S., and Crapolicchio, R.: ESA's soil moisture and ocean salinity mission: Mission performance and operations, IEEE T. Geosci. Remote, 50, 1354–1366, https://doi.org/10.1109/TGRS.2012.2187666, 2012.
Menemenlis, D.: ECCOv4 setup, available at: http://wwwcvs.mitgcm.org/viewvc/MITgcm/MITgcm_contrib/llc_hires/ (last access: 29 March 2021), 2020a.
Menemenlis, D.: SMAP observations, available at: http://apdrc.soest.hawaii.edu/las/v6/dataset?catitem=2928 (last access: 29 March 2021), 2020b.
Menemenlis, D., Hill, C. N., Adcroft, A. J., Campin, J.-M., Cheng, B., Ciotti, R. B., and Zhang, J.: NASA Supercomputer Improves Prospects for Ocean Climate Research, EOS Transactions AGU, 86, 89–96, https://doi.org/10.1029/2005EO090002, 2005.
Menemenlis, D., Campin, J.-M., Heimbach, P., Hill, C. N., Lee, T., Nguyen, A. T., and Zhang, H.: ECCO2: High Resolution Global Ocean and Sea Ice Data Synthesis, Mercator Ocean Quarterly Newsletter, 31, 13–21, 2008.
Meng, Z., Ning, L. Yuping G., and Yang, F.: Exchanges of surface plastic particles in the South China Sea through straits using Lagrangian method, J. Tropical Oceanogr., 39, 109–116, available at: http://journal15.magtechjournal.com/Jwk3_rdhyxb/article/2020/1009-5470/1009-5470-39-5-109.shtml (last access: 29 March 2021), 2020 (in Chinese with English abstract).
Molleri, G. S. F., Novo, E. M. L. M., and Kampel, M.: Space-time variability of the Amazon River plume based on satellite ocean color, Cont. Shelf Res., 30, 342–352, https://doi.org/10.1016/j.csr.2009.11.015, 2010.
Neetu, S., Lengaigne, M., Vincent, E. M., Vialard, J., Madec, G., Samson, G., and Durand, F.: Influence of upper-ocean stratification on tropical cyclones-induced surface cooling in the Bay of Bengal, J. Geophys. Res.-Oceans, 117, C12020, https://doi.org/10.1029/2012JC008433, 2012.
Palma, E. D. and Matano, R. P.: An idealized study of near equatorial river plumes, J. Geophys. Res.-Oceans, 122, 3599–3620, https://doi.org/10.1002/2016JC012554, 2017.
Piecuch, C. G. and Wadehra, R.: Dynamic sea level variability due to seasonal river discharge: A preliminary global ocean model study. Geophys. Res. Lett., 47, e2020GL086984, https://doi.org/10.1029/2020GL086984, 2020.
Rao, R. R. and Sivakumar, R.: Seasonal variability of the salt budget of the mixed layer and near-surface layer salinity structure of the tropical Indian Ocean from a new global ocean salinity climatology, J. Geophys. Res.-Oceans, 108, 3009, https://doi.org/10.1029/2001JC000907, 2003.
Resplandy, L., Keeling, R. F., Rödenbeck, C., Stephens, B. B., Khatiwala, S., Rodgers, K. B., Long, M. C., Bopp, L., and Tans, P. P.: Revision of global carbon fluxes based on a reassessment of oceanic and riverine carbon transport, Nat. Geosci., 11, 504–509, https://doi.org/10.1038/s41561-018-0151-3, 2018.
Roobaert, A., Laruelle, G. G. Landschützer, P., Gruber, N., Chou, L., and Regnier, P.: The Spatiotemporal Dynamics of the Sources and Sinks of CO2 in the Global Coastal Ocean, Global Biogeochem. Cy., 33, 1693–1714, https://doi.org/10.1029/2019GB006239, 2019.
Roullet, G. and Madec, G.: Salt conservation, free surface, and varying levels: A new formulation for ocean general circulation models, J. Geophys. Res.-Oceans, 105, 23927–23942, https://doi.org/10.1029/2000jc900089, 2000.
Santini, M. and Caporaso, L.: Evaluation of freshwater flow from rivers to the sea in CMIP5 simulations: Insights from the Congo River basin, J. Geophys. Res.-Atmos., 123, 10278–10300, https://doi.org/10.1029/2017JD027422, 2018.
Schiller, R. V. and Kourafalou, V. H.: Modeling river plume dynamics with the HYbrid Coordinate Ocean Model, Ocean Model., 33, 101–117, https://doi.org/10.1016/j.ocemod.2009.12.005, 2011.
Seitzinger, S. P., Harrison, J. A., Dumont, E., Beusen, A. H. W., and Bouwman, A. F.: Sources and delivery of carbon, nitrogen, and phosphorus to the coastal zone: An overview of Global Nutrient Export from Watersheds (NEWS) models and their application, Global Biogeochem. Cy., 19, GB4S01, https://doi.org/10.1029/2005GB002606, 2005.
Seitzinger, S. P., Mayorga, E., Bouwman, A. F., Kroeze, C., Beusen, A. H. W., Billen, G., Drecht, G. V., Dumont, E., Fekete, B. M., Garnier, J., and Harrison, J. A.: Global river nutrient export: A scenario analysis of past and future trends, Global Biogeochem. Cy., 24, GB0A08, https://doi.org/10.1029/2009GB003587, 2010.
Sengupta, D., Goddalehundi, B. R., and Anitha, D. S.: Cyclone-induced mixing does not cool SST in the post-monsoon North Bay of Bengal, Atmos. Sci. Lett., 9, 1–6, https://doi.org/10.1002/asl.162, 2008.
Stammer, D., Ueyoshi, K., Köhl, A., Large, W. G., Josey, S. A., and Wunsch, C.: Estimating air-sea fluxes of heat, freshwater, and momentum through global ocean data assimilation, J. Geophys. Res.-Oceans, 109, C05023, https://doi.org/10.1029/2003jc002082, 2004.
Su, Z., Wang, J., Klein, P., Thompson, A. F., and Menemenlis, D.: Ocean sub mesoscales as a key component of the global heat budget, Nat. Commun., 9, 775, https://doi.org/10.1038/s41467-018-02983-w, 2018.
Suzuki, T., Yamazaki, D., Tsujino, H., Komuro, Y., Nakano, H., and Urakawa, S.: A dataset of continental river discharge based on JRA-55 for use in a global ocean circulation model, J. Oceanogr., 74, 421–429, https://doi.org/10.1007/s10872-017-0458-5, 2018.
Timmermann, R., Danilov, S., Schröter, J., Böning, C., Sidorenko, D., and Rollenhagen, K.: Ocean circulation and sea ice distribution in a finite element global sea ice–ocean model, Ocean Model., 27, 114–129, https://doi.org/10.1016/j.ocemod.2008.10.009, 2009.
Tseng, Y.-H., Bryan, F. O., and Whitney, M. M.: Impacts of the representation of riverine freshwater input in the community earth system model, Ocean Model., 105, 71–86, https://doi.org/10.1016/j.ocemod.2016.08.002, 2016.
Tsujino, H., Urakawa, S., Nakano, H., Small, R. J., Kim, W. M., Yeager, S. G., Danabasoglu, G., Suzuki, T., Bamber, J. L., Bentsen, M., Böning, C. W., Bozec, A., Chassignet, E. P., Curchitser, E., Boeira Dias, F., Durack, P. J., Griffies, S. M., Harada, Y., Ilicak, M., Josey, S. A., Kobayashi, C., Kobayashi, S., Komuro, Y., Large, W. G., Sommer, J. L., Marsland, S. J., Masina, S., Scheinert, M., Tomita, H., Valdivieso, M., and Yamazaki, D.: JRA-55 based surface dataset for driving ocean–sea-ice models (JRA55-do), Ocean Model., 130, 79–139, https://doi.org/10.1016/j.ocemod.2018.07.002, 2018.
Vialard, J. and Delecluse, P.: An OGCM study for the TOGA decade. Part I: Role of salinity in the physics of the western Pacific fresh pool, J. Phys. Oceanogr., 28, 1071–1088, https://doi.org/10.1175/1520-0485(1998)028<1071:AOSFTT>2.0.CO;2, 1998.
Vinaychandran, P., Murty, V. S. N., and Ramesh Babu, V.: Observations of barrier layer formation in the Bay of Bengal during summer monsoon, J. Geophys. Res.-Oceans, 107, 8018, https://doi.org/10.1029/2001JC000831, 2002.
Volodin, E. M., Dianskii, N. A., and Gusev, A. V.: Simulating present-day climate with the INMCM4.0 coupled model of the atmospheric and oceanic general circulations, Izvestiya, Atmos. Ocean. Phys., 46, 414–431, https://doi.org/10.1134/S000143381004002X, 2010.
Walker, N. D.: Satellite assessment of Mississippi River plume variability: causes and predictability, Remote Sens. Environ., 58, 21–35, https://doi.org/10.1016/0034-4257(95)00259-6, 1996.
Ward, N. D., Megonigal, J. P., Bond-Lamberty, B., Bailey, V. L., Butman, D., Canuel, E. A., Diefenderfer, H., Ganju, N. K., Goñi, M. A., Graham, E. B., Hopkinson, C. S., Khangaonkar, T., Langley, J. A., McDowell, N. G., Myers-Pigg, A. N., Neumann, R. B., Osburn, C. L., Price, R. M., Rowland, J., Sengupta, A., Simard, M., Thornton, P. E., Tzortziou, M., Vargas, R., Weisenhorn, P. B., and Windham-Myers, L.: Representing the function and sensitivity of coastal interfaces in Earth system models, Nat. Commun., 11, 2458, https://doi.org/10.1038/s41467-020-16236-2, 2020.
Willmott, C. J.: On the validation of models, Phys. Geogr., 2, 184–194, https://doi.org/10.1080/02723646.1981.10642213, 1981.
Yankovsky, A. E. and Chapman D. C.: A Simple Theory for the Fate of Buoyant Coastal Discharges, J. Phys. Oceanogr., 27, 1386–1401, https://doi.org/10.1175/1520-0485(1997)027<1386:ASTFTF>2.0.CO;2, 1997.
Yueh, S. H., Tang, W., Fore, A. G., Neumann, G., Hayashi, A., Freedman, A., and Lagerloef, G. S. L-band passive and active microwave geophysical model functions of ocean surface winds and applications to Aquarius retrieval, IEEE T. Geosci. Remote, 51, 4619–4632, https://doi.org/10.1109/TGRS.2013.2266915, 2013.
Zhang, H.: MITgcm model setup and output for “Improved representation of river runoff in ECCO simulations: implementation, evaluation, and impacts to coastal plume regions” [Data set], Zenodo, https://doi.org/10.5281/zenodo.4095613, 2020.
Zhang, H., Menemenlis, D., and Fenty, G.: ECCO LLC270 ocean‐ice state estimate, available at: http://hdl.handle.net/1721.1/119821 (last access: 29 March 2021), 2018.
Simulation of coastal plume regions was improved in global ECCOv4 with a series of sensitivity tests. We find modeled SSS is closer to SMAP when using daily point-source runoff as well as increasing the resolution from coarse to intermediate. The plume characteristics, freshwater transport, and critical water properties are modified greatly. But this may not happen with a further increase to high resolution. The study will advance the seamless modeling of land–ocean–atmosphere feedback in ESMs.
Simulation of coastal plume regions was improved in global ECCOv4 with a series of sensitivity...