Articles | Volume 15, issue 3
https://doi.org/10.5194/gmd-15-995-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-15-995-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
03 Feb 2022
Development and technical paper |
| 03 Feb 2022
| 03 Feb 2022
Improvements in the regional South China Sea Operational Oceanography Forecasting System (SCSOFSv2)
Xueming Zhu
Southern Marine Science and Engineering Guangdong Laboratory
(Zhuhai), Zhuhai, 519000, China
National Marine Environmental Forecasting Center, Key Laboratory of
Marine Hazards Forecasting, Ministry of Natural Resources, Beijing, 100081, China
Ziqing Zu
National Marine Environmental Forecasting Center, Key Laboratory of
Marine Hazards Forecasting, Ministry of Natural Resources, Beijing, 100081, China
National Marine Environmental Forecasting Center, Key Laboratory of
Marine Hazards Forecasting, Ministry of Natural Resources, Beijing, 100081, China
Miaoyin Zhang
National Marine Environmental Forecasting Center, Key Laboratory of
Marine Hazards Forecasting, Ministry of Natural Resources, Beijing, 100081, China
Yunfei Zhang
National Marine Environmental Forecasting Center, Key Laboratory of
Marine Hazards Forecasting, Ministry of Natural Resources, Beijing, 100081, China
Hui Wang
CORRESPONDING AUTHOR
Institute of Marine Science and Technology, Shandong University,
Qingdao, Shandong, 266237, China
National Marine Environmental Forecasting Center, Key Laboratory of
Marine Hazards Forecasting, Ministry of Natural Resources, Beijing, 100081, China
Ang Li
National Marine Environmental Forecasting Center, Key Laboratory of
Marine Hazards Forecasting, Ministry of Natural Resources, Beijing, 100081, China
Related authors
Na Li, Xueming Zhu, Hui Wang, Shouwen Zhang, and Xidong Wang
Ocean Sci., 19, 1437–1451, https://doi.org/10.5194/os-19-1437-2023, https://doi.org/10.5194/os-19-1437-2023, 2023
Short summary
Short summary
Observations of the sea surface temperature in the Arabian Sea show exceptional warming before the onset of the Indian Ocean summer monsoon. The sea surface temperature change is mainly caused by sea surface heat flux forcing, horizontal advection, and vertical entrainment. Here, we quantify the contribution of those factors to the Arabian Sea warm pool using heat budget analysis and highlight how large-scale ocean modes control its change.
Xueming Zhu, Ziqing Zu, Shihe Ren, Yunfei Zhang, Miaoyin Zhang, and Hui Wang
Ocean Sci. Discuss., https://doi.org/10.5194/os-2020-104, https://doi.org/10.5194/os-2020-104, 2020
Preprint withdrawn
Short summary
Short summary
In order to improve forecasting skills of South China Sea Operational Forecasting System operated in NMEFC of China, comprehensive updates have been conducted to the configurations of physical model and data assimilation scheme. Scientific inter-comparison and accuracy assessment has been performed by employing GODAE IV-TT Class 4 metrics. The results indicate that remarkable improvements have been achieved in the new version of SCSOFS.
Linxu Huang, Tianyu Zhang, Shouwen Zhang, and Hui Wang
EGUsphere, https://doi.org/10.5194/egusphere-2024-1940, https://doi.org/10.5194/egusphere-2024-1940, 2024
Short summary
Short summary
This study utilized a hydrodynamic model to explore the complex dynamics between storm surges and tides, the result shows that the nonlinear effect is mainly generated by local acceleration and convection while it is predominantly governed by wind stress and bottom friction in shallow water regions. By adjusting typhoon landfall times, we demonstrated that the contribution ratio of each nonlinear term changes little, their magnitudes fluctuate depending on the timing of landfall.
Na Li, Xueming Zhu, Hui Wang, Shouwen Zhang, and Xidong Wang
Ocean Sci., 19, 1437–1451, https://doi.org/10.5194/os-19-1437-2023, https://doi.org/10.5194/os-19-1437-2023, 2023
Short summary
Short summary
Observations of the sea surface temperature in the Arabian Sea show exceptional warming before the onset of the Indian Ocean summer monsoon. The sea surface temperature change is mainly caused by sea surface heat flux forcing, horizontal advection, and vertical entrainment. Here, we quantify the contribution of those factors to the Arabian Sea warm pool using heat budget analysis and highlight how large-scale ocean modes control its change.
Tian Tian, Lijing Cheng, Gongjie Wang, John Abraham, Wangxu Wei, Shihe Ren, Jiang Zhu, Junqiang Song, and Hongze Leng
Earth Syst. Sci. Data, 14, 5037–5060, https://doi.org/10.5194/essd-14-5037-2022, https://doi.org/10.5194/essd-14-5037-2022, 2022
Short summary
Short summary
A high-resolution gridded dataset is crucial for understanding ocean processes at various spatiotemporal scales. Here we used a machine learning approach and successfully reconstructed a high-resolution (0.25° × 0.25°) ocean subsurface (1–2000 m) salinity dataset for the period 1993–2018 (monthly) by merging in situ salinity profile observations with high-resolution satellite remote-sensing data. This new product could be useful in various applications in ocean and climate fields.
Ruizi Shi, Fanghua Xu, Li Liu, Zheng Fan, Hao Yu, Hong Li, Xiang Li, and Yunfei Zhang
Geosci. Model Dev., 15, 2345–2363, https://doi.org/10.5194/gmd-15-2345-2022, https://doi.org/10.5194/gmd-15-2345-2022, 2022
Short summary
Short summary
To better understand the effects of surface waves on global intraseasonal prediction, we incorporated the WW3 model into CFSv2.0. Processes of Langmuir mixing, Stokes–Coriolis force with entrainment, air–sea fluxes modified by Stokes drift, and momentum roughness length were considered. Results from two groups of 56 d experiments show that overestimated sea surface temperature, 2 m air temperature, 10 m wind, wave height, and underestimated mixed layer from the original CFSv2.0 are improved.
Shihe Ren, Xi Liang, Qizhen Sun, Hao Yu, L. Bruno Tremblay, Bo Lin, Xiaoping Mai, Fu Zhao, Ming Li, Na Liu, Zhikun Chen, and Yunfei Zhang
Geosci. Model Dev., 14, 1101–1124, https://doi.org/10.5194/gmd-14-1101-2021, https://doi.org/10.5194/gmd-14-1101-2021, 2021
Short summary
Short summary
Sea ice plays a crucial role in global energy and water budgets. To get a better simulation of sea ice, we coupled a sea ice model with an atmospheric and ocean model to form a fully coupled system. The sea ice simulation results of this coupled system demonstrated that a two-way coupled model has better performance in terms of sea ice, especially in summer. This indicates that sea-ice–ocean–atmosphere interaction plays a crucial role in controlling Arctic summertime sea ice distribution.
Xueming Zhu, Ziqing Zu, Shihe Ren, Yunfei Zhang, Miaoyin Zhang, and Hui Wang
Ocean Sci. Discuss., https://doi.org/10.5194/os-2020-104, https://doi.org/10.5194/os-2020-104, 2020
Preprint withdrawn
Short summary
Short summary
In order to improve forecasting skills of South China Sea Operational Forecasting System operated in NMEFC of China, comprehensive updates have been conducted to the configurations of physical model and data assimilation scheme. Scientific inter-comparison and accuracy assessment has been performed by employing GODAE IV-TT Class 4 metrics. The results indicate that remarkable improvements have been achieved in the new version of SCSOFS.
Ruizi Shi, Fanghua Xu, Li Liu, Zheng Fan, Hao Yu, Xiang Li, and Yunfei Zhang
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-327, https://doi.org/10.5194/gmd-2020-327, 2020
Revised manuscript not accepted
Short summary
Short summary
To better understand the effects of surface waves, we developed a coupled global atmosphere-ocean-wave system. Processes of Langmuir circulations and sea surface momentum roughness were considered. Results from a series of 7-day forecasts show the Langmuir circulations can reduce the biases of warm sea surface temperature and shallow mixed layer in the Antarctic circumpolar current during austral summer. Whereas surface roughness enables improvements to overestimated 10-m wind and wave height.
Related subject area
Oceanography
A revised ocean mixed layer model for better simulating the diurnal variation in ocean skin temperature
Evaluating an accelerated forcing approach for improving computational efficiency in coupled ice sheet–ocean modelling
An optimal transformation method for inferring ocean tracer sources and sinks
PPCon 1.0: Biogeochemical-Argo profile prediction with 1D convolutional networks
Experimental design for the Marine Ice Sheet–Ocean Model Intercomparison Project – phase 2 (MISOMIP2)
Development of a total variation diminishing (TVD) sea ice transport scheme and its application in an ocean (SCHISM v5.11) and sea ice (Icepack v1.3.4) coupled model on unstructured grids
Spurious numerical mixing under strong tidal forcing: a case study in the south-east Asian seas using the Symphonie model (v3.1.2)
Modelling the water isotope distribution in the Mediterranean Sea using a high-resolution oceanic model (NEMO-MED12-watiso v1.0): evaluation of model results against in situ observations
LIGHT-bgcArgo-1.0: using synthetic float capabilities in E3SMv2 to assess spatiotemporal variability in ocean physics and biogeochemistry
Towards a real-time modeling of global ocean waves by the fully GPU-accelerated spectral wave model WAM6-GPU v1.0
A simple approach to represent precipitation-derived freshwater fluxes into nearshore ocean models: an FVCOM4.1 case study of Quatsino Sound, British Columbia
An optimal transformation method applied to diagnose the ocean carbon budget
Implementation and assessment of a model including mixotrophs and the carbonate cycle (Eco3M_MIX-CarbOx v1.0) in a highly dynamic Mediterranean coastal environment (Bay of Marseille, France) – Part 2: Towards a better representation of total alkalinity when modeling the carbonate system and air–sea CO2 fluxes
DALROMS-NWA12 v1.0, a coupled circulation-ice-biogeochemistry modelling system for the northwest Atlantic Ocean: Development and validation
Development of a novel storm surge inundation model framework for efficient prediction
Skin sea surface temperature schemes in coupled ocean–atmosphere modelling: the impact of chlorophyll-interactive e-folding depth
A wave-resolving 2DV Lagrangian approach to model microplastic transport in the nearshore
DELWAVE 1.0: deep learning surrogate model of surface wave climate in the Adriatic Basin
StraitFlux – precise computations of water strait fluxes on various modeling grids
Comparison of the Coastal and Regional Ocean COmmunity model (CROCO) and NCAR-LES in non-hydrostatic simulations
HOTSSea v1: a NEMO-based physical Hindcast of the Salish Sea (1980–2018) supporting ecosystem model development
Intercomparisons of Tracker v1.1 and four other ocean particle-tracking software packages in the Regional Ocean Modeling System
CAR36, a regional high-resolution ocean forecasting system for improving drift and beaching of Sargassum in the Caribbean archipelago
Implementation of additional spectral wave field exchanges in a three-dimensional wave–current coupled WAVEWATCH-III (version 6.07) and CROCO (version 1.2) configuration: assessment of their implications for macro-tidal coastal hydrodynamics
Comparison of 4-dimensional variational and ensemble optimal interpolation data assimilation systems using a Regional Ocean Modeling System (v3.4) configuration of the eddy-dominated East Australian Current system
LOCATE v1.0: numerical modelling of floating marine debris dispersion in coastal regions using Parcels v2.4.2
New insights into the South China Sea throughflow and water budget seasonal cycle: evaluation and analysis of a high-resolution configuration of the ocean model SYMPHONIE version 2.4
MQGeometry-1.0: a multi-layer quasi-geostrophic solver on non-rectangular geometries
Parameter estimation for ocean background vertical diffusivity coefficients in the Community Earth System Model (v1.2.1) and its impact on El Niño–Southern Oscillation forecasts
Great Lakes wave forecast system on high-resolution unstructured meshes
Impact of increased resolution on Arctic Ocean simulations in Ocean Model Intercomparison Project phase 2 (OMIP-2)
A high-resolution physical–biogeochemical model for marine resource applications in the northwest Atlantic (MOM6-COBALT-NWA12 v1.0)
A flexible z-layers approach for the accurate representation of free surface flows in a coastal ocean model (SHYFEM v. 7_5_71)
Implementation and assessment of a model including mixotrophs and the carbonate cycle (Eco3M_MIX-CarbOx v1.0) in a highly dynamic Mediterranean coastal environment (Bay of Marseille, France) – Part 1: Evolution of ecosystem composition under limited light and nutrient conditions
Ocean wave tracing v.1: a numerical solver of the wave ray equations for ocean waves on variable currents at arbitrary depths
Design and evaluation of an efficient high-precision ocean surface wave model with a multiscale grid system (MSG_Wav1.0)
Evaluation of the CMCC global eddying ocean model for the Ocean Model Intercomparison Project (OMIP2)
Barents-2.5km v2.0: an operational data-assimilative coupled ocean and sea ice ensemble prediction model for the Barents Sea and Svalbard
Open-ocean tides simulated by ICON-O, version icon-2.6.6
Using Probability Density Functions to Evaluate Models (PDFEM, v1.0) to compare a biogeochemical model with satellite-derived chlorophyll
Data assimilation sensitivity experiments in the East Auckland Current system using 4D-Var
Using the COAsT Python package to develop a standardised validation workflow for ocean physics models
Improving Antarctic Bottom Water precursors in NEMO for climate applications
Formulation, optimization, and sensitivity of NitrOMZv1.0, a biogeochemical model of the nitrogen cycle in oceanic oxygen minimum zones
Waves in SKRIPS: WAVEWATCH III coupling implementation and a case study of Tropical Cyclone Mekunu
Adding sea ice effects to a global operational model (NEMO v3.6) for forecasting total water level: approach and impact
Enhanced ocean wave modeling by including effect of breaking under both deep- and shallow-water conditions
An internal solitary wave forecasting model in the northern South China Sea (ISWFM-NSCS)
The 3D biogeochemical marine mercury cycling model MERCY v2.0 – linking atmospheric Hg to methylmercury in fish
Global seamless tidal simulation using a 3D unstructured-grid model (SCHISM v5.10.0)
Eui-Jong Kang, Byung-Ju Sohn, Sang-Woo Kim, Wonho Kim, Young-Cheol Kwon, Seung-Bum Kim, Hyoung-Wook Chun, and Chao Liu
Geosci. Model Dev., 17, 8553–8568, https://doi.org/10.5194/gmd-17-8553-2024, https://doi.org/10.5194/gmd-17-8553-2024, 2024
Short summary
Short summary
Sea surface temperature (SST) is vital in climate, weather, and ocean sciences because it influences air–sea interactions. Errors in the ECMWF model's scheme for predicting ocean skin temperature prompted a revision of the ocean mixed layer model. Validation against infrared measurements and buoys showed a good correlation with minimal deviations. The revised model accurately simulates SST variations and aligns with solar radiation distributions, showing promise for weather and climate models.
Qin Zhou, Chen Zhao, Rupert Gladstone, Tore Hattermann, David Gwyther, and Benjamin Galton-Fenzi
Geosci. Model Dev., 17, 8243–8265, https://doi.org/10.5194/gmd-17-8243-2024, https://doi.org/10.5194/gmd-17-8243-2024, 2024
Short summary
Short summary
We introduce an accelerated forcing approach to address timescale discrepancies between the ice sheets and ocean components in coupled modelling by reducing the ocean simulation duration. The approach is evaluated using idealized coupled models, and its limitations in real-world applications are discussed. Our results suggest it can be a valuable tool for process-oriented coupled ice sheet–ocean modelling and downscaling climate simulations with such models.
Jan D. Zika and Taimoor Sohail
Geosci. Model Dev., 17, 8049–8068, https://doi.org/10.5194/gmd-17-8049-2024, https://doi.org/10.5194/gmd-17-8049-2024, 2024
Short summary
Short summary
We describe a method to relate fluxes of heat and freshwater at the sea surface to the resulting distribution of seawater among categories such as warm and salty or cold and salty. 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.
Gloria Pietropolli, Luca Manzoni, and Gianpiero Cossarini
Geosci. Model Dev., 17, 7347–7364, https://doi.org/10.5194/gmd-17-7347-2024, https://doi.org/10.5194/gmd-17-7347-2024, 2024
Short summary
Short summary
Monitoring the ocean is essential for studying marine life and human impact. Our new software, PPCon, uses ocean data to predict key factors like nitrate and chlorophyll levels, which are hard to measure directly. By leveraging machine learning, PPCon offers more accurate and efficient predictions.
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
Geosci. Model Dev., 17, 7105–7139, https://doi.org/10.5194/gmd-17-7105-2024, https://doi.org/10.5194/gmd-17-7105-2024, 2024
Short summary
Short summary
Global climate models do not reliably simulate sea-level change due to 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 second 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.
Qian Wang, Yang Zhang, Fei Chai, Y. Joseph Zhang, and Lorenzo Zampieri
Geosci. Model Dev., 17, 7067–7081, https://doi.org/10.5194/gmd-17-7067-2024, https://doi.org/10.5194/gmd-17-7067-2024, 2024
Short summary
Short summary
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.
Adrien Garinet, Marine Herrmann, Patrick Marsaleix, and Juliette Pénicaud
Geosci. Model Dev., 17, 6967–6986, https://doi.org/10.5194/gmd-17-6967-2024, https://doi.org/10.5194/gmd-17-6967-2024, 2024
Short summary
Short summary
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, compromising simulation realism. Here we illustrate the spurious effect that tides can have on simulations of south-east Asia. Although they play an important role in determining the state of the ocean, they can increase numerical errors and make simulation outputs less realistic. We also provide insights into how to reduce these errors.
Mohamed Ayache, Jean-Claude Dutay, Anne Mouchet, Kazuyo Tachikawa, Camille Risi, and Gilles Ramstein
Geosci. Model Dev., 17, 6627–6655, https://doi.org/10.5194/gmd-17-6627-2024, https://doi.org/10.5194/gmd-17-6627-2024, 2024
Short summary
Short summary
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.
Cara Nissen, Nicole S. Lovenduski, Mathew Maltrud, Alison R. Gray, Yohei Takano, Kristen Falcinelli, Jade Sauvé, and Katherine Smith
Geosci. Model Dev., 17, 6415–6435, https://doi.org/10.5194/gmd-17-6415-2024, https://doi.org/10.5194/gmd-17-6415-2024, 2024
Short summary
Short summary
Autonomous profiling floats have provided unprecedented observational coverage of the global ocean, but uncertainties remain about whether their sampling frequency and density capture the true spatiotemporal variability of physical, biogeochemical, and biological properties. Here, we present the novel synthetic biogeochemical float capabilities of the Energy Exascale Earth System Model version 2 and demonstrate their utility as a test bed to address these uncertainties.
Ye Yuan, Fujiang Yu, Zhi Chen, Xueding Li, Fang Hou, Yuanyong Gao, Zhiyi Gao, and Renbo Pang
Geosci. Model Dev., 17, 6123–6136, https://doi.org/10.5194/gmd-17-6123-2024, https://doi.org/10.5194/gmd-17-6123-2024, 2024
Short summary
Short summary
Accurate and timely forecasting of ocean waves is of great importance to the safety of marine transportation and offshore engineering. In this study, GPU-accelerated computing is introduced in WAve Modeling Cycle 6 (WAM6). With this effort, global high-resolution wave simulations can now run on GPUs up to tens of times faster than the currently available models can on a CPU node with results that are just as accurate.
Krysten Rutherford, Laura Bianucci, and William Floyd
Geosci. Model Dev., 17, 6083–6104, https://doi.org/10.5194/gmd-17-6083-2024, https://doi.org/10.5194/gmd-17-6083-2024, 2024
Short summary
Short summary
Nearshore ocean models often lack complete information about freshwater fluxes due to numerous ungauged rivers and streams. We tested a simple rain-based hydrological model as inputs into an ocean model of Quatsino Sound, Canada, with the aim of improving the representation of the land–ocean connection in the nearshore model. Through multiple tests, we found that the performance of the ocean model improved when providing 60 % or more of the freshwater inputs from the simple runoff model.
Neill Mackay, Taimoor Sohail, Jan David Zika, Richard G. Williams, Oliver Andrews, and Andrew James Watson
Geosci. Model Dev., 17, 5987–6005, https://doi.org/10.5194/gmd-17-5987-2024, https://doi.org/10.5194/gmd-17-5987-2024, 2024
Short summary
Short summary
The ocean absorbs carbon dioxide from the atmosphere, mitigating climate change, but estimates of the uptake do not always agree. There is a need to reconcile these differing estimates and to improve our understanding of ocean carbon uptake. We present a new method for estimating ocean carbon uptake and test it with model data. The method effectively diagnoses the ocean carbon uptake from limited data and therefore shows promise for reconciling different observational estimates.
Lucille Barré, Frédéric Diaz, Thibaut Wagener, Camille Mazoyer, Christophe Yohia, and Christel Pinazo
Geosci. Model Dev., 17, 5851–5882, https://doi.org/10.5194/gmd-17-5851-2024, https://doi.org/10.5194/gmd-17-5851-2024, 2024
Short summary
Short summary
The carbonate system is typically studied using measurements, but modeling can contribute valuable insights. Using a biogeochemical model, we propose a new representation of total alkalinity, dissolved inorganic carbon, pCO2, and pH in a highly dynamic Mediterranean coastal area, the Bay of Marseille, a useful addition to measurements. Through a detailed analysis of pCO2 and air–sea CO2 fluxes, we show that variations are strongly impacted by the hydrodynamic processes that affect the bay.
Kyoko Ohashi, Arnaud Laurent, Christoph Renkl, Jinyu Sheng, Katja Fennel, and Eric Oliver
EGUsphere, https://doi.org/10.5194/egusphere-2024-1372, https://doi.org/10.5194/egusphere-2024-1372, 2024
Short summary
Short summary
We developed a modelling system of the northwest Atlantic Ocean that simulates the currents, temperature, salinity, and parts of the biochemical cycle of the ocean, as well as sea ice. The system combines advanced, open-source models and can be used to study, for example, the oceans’ capture of atmospheric carbon dioxide which is a key process in the global climate. The system produces realistic results, and we use it to investigate the roles of tides and sea ice in the northwest Atlantic Ocean.
Xuanxuan Gao, Shuiqing Li, Dongxue Mo, Yahao Liu, and Po Hu
Geosci. Model Dev., 17, 5497–5509, https://doi.org/10.5194/gmd-17-5497-2024, https://doi.org/10.5194/gmd-17-5497-2024, 2024
Short summary
Short summary
Storm surges generate coastal inundation and expose populations and properties to danger. We developed a novel storm surge inundation model for efficient prediction. Estimates compare well with in situ measurements and results from a numerical model. The new model is a significant improvement on existing numerical models, with much higher computational efficiency and stability, which allows timely disaster prevention and mitigation.
Vincenzo de Toma, Daniele Ciani, Yassmin Hesham Essa, Chunxue Yang, Vincenzo Artale, Andrea Pisano, Davide Cavaliere, Rosalia Santoleri, and Andrea Storto
Geosci. Model Dev., 17, 5145–5165, https://doi.org/10.5194/gmd-17-5145-2024, https://doi.org/10.5194/gmd-17-5145-2024, 2024
Short summary
Short summary
This study explores methods to reconstruct diurnal variations in skin sea surface temperature in a model of the Mediterranean Sea. Our new approach, considering chlorophyll concentration, enhances spatial and temporal variations in the warm layer. Comparative analysis shows context-dependent improvements. The proposed "chlorophyll-interactive" method brings the surface net total heat flux closer to zero annually, despite a net heat loss from the ocean to the atmosphere.
Isabel Jalón-Rojas, Damien Sous, and Vincent Marieu
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-100, https://doi.org/10.5194/gmd-2024-100, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
This study presents a novel modeling approach for understanding microplastic transport in coastal waters. The model accurately replicates experimental data and reveals key transport mechanisms. The findings enhance our knowledge of how microplastics move in nearshore environments, aiding in coastal management and efforts to combat plastic pollution globally.
Peter Mlakar, Antonio Ricchi, Sandro Carniel, Davide Bonaldo, and Matjaž Ličer
Geosci. Model Dev., 17, 4705–4725, https://doi.org/10.5194/gmd-17-4705-2024, https://doi.org/10.5194/gmd-17-4705-2024, 2024
Short summary
Short summary
We propose a new point-prediction model, the DEep Learning WAVe Emulating model (DELWAVE), which successfully emulates the Simulating WAves Nearshore model (SWAN) over synoptic to climate timescales. Compared to control climatology over all wind directions, the mismatch between DELWAVE and SWAN is generally small compared to the difference between scenario and control conditions, suggesting that the noise introduced by surrogate modelling is substantially weaker than the climate change signal.
Susanna Winkelbauer, Michael Mayer, and Leopold Haimberger
Geosci. Model Dev., 17, 4603–4620, https://doi.org/10.5194/gmd-17-4603-2024, https://doi.org/10.5194/gmd-17-4603-2024, 2024
Short summary
Short summary
Oceanic transports shape the global climate, but the evaluation and validation of this key quantity based on reanalysis and model data are complicated by the distortion of the used modelling grids and the large number of different grid types. We present two new methods that allow the calculation of oceanic fluxes of volume, heat, salinity, and ice through almost arbitrary sections for various models and reanalyses that are independent of the used modelling grids.
Xiaoyu Fan, Baylor Fox-Kemper, Nobuhiro Suzuki, Qing Li, Patrick Marchesiello, Peter P. Sullivan, and Paul S. Hall
Geosci. Model Dev., 17, 4095–4113, https://doi.org/10.5194/gmd-17-4095-2024, https://doi.org/10.5194/gmd-17-4095-2024, 2024
Short summary
Short summary
Simulations of the oceanic turbulent boundary layer using the nonhydrostatic CROCO ROMS and NCAR-LES models are compared. CROCO and the NCAR-LES are accurate in a similar manner, but CROCO’s additional features (e.g., nesting and realism) and its compressible turbulence formulation carry additional costs.
Greig Oldford, Tereza Jarníková, Villy Christensen, and Michael Dunphy
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-58, https://doi.org/10.5194/gmd-2024-58, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
We developed a physical ocean model called the Hindcast of the Salish Sea (HOTSSea) that recreates conditions throughout the Salish Sea from 1980 to 2018, filling in the gaps in patchy measurements. The model predicts physical ocean properties with sufficient accuracy to be useful for a variety of applications. The model corroborates observed ocean temperature trends and was used to examine areas with few observations. Results indicate that some seasons and areas are warming faster than others.
Jilian Xiong and Parker MacCready
Geosci. Model Dev., 17, 3341–3356, https://doi.org/10.5194/gmd-17-3341-2024, https://doi.org/10.5194/gmd-17-3341-2024, 2024
Short summary
Short summary
The new offline particle tracking package, Tracker v1.1, is introduced to the Regional Ocean Modeling System, featuring an efficient nearest-neighbor algorithm to enhance particle-tracking speed. Its performance was evaluated against four other tracking packages and passive dye. Despite unique features, all packages yield comparable results. Running multiple packages within the same circulation model allows comparison of their performance and ease of use.
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
Geosci. Model Dev., 17, 3157–3173, https://doi.org/10.5194/gmd-17-3157-2024, https://doi.org/10.5194/gmd-17-3157-2024, 2024
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Cited articles
Bao, X., Wan, X., Gao, G., and Wu, D.: The characteristics of the seasonal
variability of the sea surface temperature field in the Bohai Sea, the
Huanghai Sea and the East China Sea from AVHRR data, Acta Oceanol. Sin., 24,
125–133, 2002.
Barnier, B., Siefridt, L., and Marchesiello, P.: Thermal forcing for a
global ocean circulation model using a three-year climatology of ECMWF
analyses, J. Mar. Syst., 6, 363–380, https://doi.org/10.1016/0924-7963(94)00034-9, 1995.
Barnier, B., Patrick, M., Miranda, A. P. D., Molines, J.-M., and Coulibaly,
M.: A sigma-coordinate primitive equation model for studying the circulation
in the South Atlantic, Part I: Model configuration with error estimates,
Deep-Sea Res. Pt. I, 45, 543–572, 1998.
Beckmann, A. and Haidvogel, D. B.: Numerical simulation of flow around a tall
isolated seamount, Part I: problem formulation and model accuracy, J. Phys.
Oceanogr. 23, 1737–1753, 1993.
Bloom, S. C., Takacs, L. L., Silva, A. M. D., and Ledvina, D.: Data
Assimilation using incremental Analysis Updates, Mon. Weather Rev.,
124, 1256–1271, 1996.
Cai, S., Xie, J., Xu, J., Wang, D., Chen, Z., Deng, X., and Long, X.:
Monthly variation of some parameters about internal solitary waves in the
South China sea, Deep-Sea Res. Pt. I, 84, 73–85, https://doi.org/10.1016/j.dsr.2013.10.008, 2014.
Carnes, M. R.: Description and Evaluation of GDEM-V3.0, Naval Research Laboratory,Stennis Space Center, MS, NRL/MR/7330-09-9165, 2009.
Carton, J. A. and Giese, B. S.: A Reanalysis of Ocean Climate Using Simple
Ocean Data Assimilation (SODA), Mon. Weather Rev., 136, 2999–3017,
https://doi.org/10.1175/2007MWR1978.1, 2008.
Carton, J. A., Chepurin, G. A., and Chen, L.: SODA3: A New Ocean Climate Reanalysis, J. Clim., 31, 6967–6983, https://doi.org/10.1175/JCLI-D-18-0149.1, 2018, and data available at: https://www2.atmos.umd.edu/~ocean/index_files/soda3.3.1_mn_download.htm, last access: 3 January 2021, and https://dsrs.atmos.umd.edu/DATA/soda3.3.2/REGRIDED/ocean/, last access: 3 January 2021.
Chu, P. C. and Li, R.: South China Sea isopycnal-surface circulation, J.
Phys. Oceanogr., 30, 2419–2438, https://doi.org/10.1175/1520-0485(2000)030<2419:SCSISC>2.0.CO;2, 2000.
Cummings, J. A.: Operational multivariate ocean data assimilation, Quart. J.
R. Met. Soc., 131, 3583–3604, https://doi.org/10.1256/qj.05.105, 2005.
Ding, R., Xuan, J., Zhang, T., Zhou, L., Zhou, F., Meng, Q., and Kang, I.:
Eddy-Induced Heat Transport in the South China Sea, J. Phys. Oceanogr.,
51, 2329–2349, https://doi.org/10.1175/JPO-D-20-0206.1, 2021.
Divakaran, P., Brassington, G. B., Ryan, A. G., Regnier, C., Spindler, T.,
Mehra, A., Hernandez, F., Smith, G. C., Liu, Y., and Davidson, F.: GODAE
OceanView Inter-comparison for the Australian Region, J. Oper. Oceanogr., 8, s112–s126, https://doi.org/10.1080/1755876X.2015.1022333, 2015.
Dombrowsky, E., Bertino, L., Brassington, G. B., Chassignet, E. P.,
Davidson, F., Hurlburt, H. E., Kamachi, M., Lee, T., Martin, M. J., Mei, S.,
and Tonani, M.: GODAE systems in operation, Oceanography, 22, 80–95,
https://doi.org/10.5670/oceanog.2009.68, 2009.
Donlon, C. J., Martin, M., Stark, J., Roberts-Jones, J., Fiedler, E., and
Wimmer, W.: The Operational Sea Surface Temperature and Sea Ice Analysis
(OSTIA) system, Remote Sens. Environ. [data set], 116, 140–158,
https://doi.org/10.1016/j.rse.2010.10.017, 2012, data available at: https://resources.marine.copernicus.eu/product-detail/SST_GLO_SST_L4_NRT_OBSERVATIONS_010_001/DATA-ACCESS, last access: 28 January 2022.
E.U. Copernicus Marine Service Information: SST of the in situ drifting
BUOY, Copernicus.eu [data set], https://resources.marine.copernicus.eu/product-detail/INSITU_GLO_UV_L2_REP_OBSERVATIONS_013_044/INFORMATION, last access: 28 January 2022a.
E.U. Copernicus Marine Service Information: SLA global ocean along-track L3 sea surface heights reprocessed (1993–ongoing) tailored for data assimilation, Copernicus.eu [data set], https://resources.marine.copernicus.eu/product-detail/SEALEVEL_GLO_PHY_L3_MY_008_062/DATA-ACCESS, last access: 28 January 2022b.
Evensen, G.: The Ensemble Kalman Filter: Theoretical formulation and
practical implementation, Ocean Dynam., 53, 343–367,
https://doi.org/10.1007/s10236-003-0036-9, 2003.
Fairall, C. W., Bradley, E. F., Hare, J. E., Grachev, A. A., and Edson, J.
B.: Bulk Parameterization of Air–Sea Fluxes: Updates and Verification for
the COARE Algorithm, J. Clim., 16, 571–591, 2003.
Farris, A. and Wimbush, M.: Wind-induced Kuroshio intrusion into the South
China Sea, J. Oceanogr., 52, 771–784, https://doi.org/10.1007/BF02239465, 1996.
GEBCO: GEBCO_2014 Grid, GEBCO [data set], https://www.gebco.net/data_and_products/historical_data_sets/#gebco_2014, last access: last access: 28 January 2022.
Hellerman, S. and Rosenstein, M.: Normal Monthly Wind Stress Over the World
Ocean with Error Estimates, J. Phys. Oceanogr., 13, 1093–1104, 1983.
Hernandez, F., Bertino, L., Brassington, G. B., Chassignet, E., Cummings,
J., Davidson, F., Drevillon, M., Garric, G., Kamachi, M., Lellouche, J.-M.,
Mahdon, R., Martin, M. J., Ratsimandresy, A., and Regnier, C.: Validation
and intercomparison studies within GODAE, Oceanography, 22, 128–143,
https://doi.org/10.5670/oceanog.2009.71, 2009.
Hernandez, F., Blockley, E., Brassington, G. B., Davidson, F., Divakaran,
P., Drévillon, M., Ishizaki, S., Garcia-Sotillo, M., Hogan, P. J.,
Lagemaa, P., Levier, B., Martin, M., Mehra, A., Mooers, C., Ferry, N., Ryan,
A., Regnier, C., Sellar, A., Smith, G. C., Sofianos, S., Spindler, T.,
Volpe, G., Wilkin, J., Zaron, E. D., and Zhang, A.: Recent progress in
performance evaluations and near real-time assessment of operational ocean
products, J. Operat. Oceanogr., 8, s221–s238, https://doi.org/10.1080/1755876X.2015.1050282, 2015.
Hwang, C. and Chen, S.-A.: Circulations and eddies over the South China Sea
derived from TOPEX/Poseidon altimetry, J. Geophys. Res., 105, 23943–23965,
https://doi.org/10.1029/2000JC900092, 2000.
Ji, Q., Zhu, X., Wang, H., Liu, G., Gao, S., Ji, X., and Xu, Q.:
Assimilating operational SST and sea ice analysis data into an operational
circulation model for the coastal seas of China, Acta Oceanol. Sin., 34,
54–64, https://doi.org/10.1007/s13131-015-0691-y, 2015.
Kanamitsu, M., Ebisuzaki, W., Woollen, J., Yang, S.-K., Hnilo, J. J.,
Fiorino, M., and Potter, G. L.: Ncep-Doe Amip-II reanalysis (R-2), Bull.
Amer. Meteor. Soc., 83, 1631–1643, https://doi.org/10.1175/BAMS-83-11-1631, 2002.
Kourafalou, V. H., Mey, P. D., Hénaff, M. L., Charria, G., Edwards, C.
A., He, R., Herzfeld, M., Pascual, A., Stanev, E. V., Tintoré, J., Usui,
N., van der Westhuysen, A. J., Wilkin, J., and Zhu, X.: Coastal Ocean
Forecasting: system integration and evaluation, J. Oper. Oceanogr., 8,
s127–s146, https://doi.org/10.1080/1755876X.2015.1022336, 2015.
Large, W. G. and Yeager, S. G.: The global climatology of an interannually
varying air–sea flux data set, Clim. Dynam., 33, 341–364,
https://doi.org/10.1007/s00382-008-0441-3, 2009.
Lee, M.-S. and Barker, D.: Preliminary Tests of First Guess at Appropriate
Time (FGAT) with WRF 3DVAR and WRF Model, Asia-Pac. J. Atmos. Sci., 41,
495–505, 2005.
Lee, M.-S., Barker, D., Huang, W., and Kuo, Y.-H.: First Guess at
Appropriate Time (FGAT) with WRF 3DVAR, Preprints for WRF/MM5 Users'
Workshop, Boulder, CO, 2004.
Lellouche, J.-M., Le Galloudec, O., Drévillon, M., Régnier, C., Greiner, E., Garric, G., Ferry, N., Desportes, C., Testut, C.-E., Bricaud, C., Bourdallé-Badie, R., Tranchant, B., Benkiran, M., Drillet, Y., Daudin, A., and De Nicola, C.: Evaluation of global monitoring and forecasting systems at Mercator Océan, Ocean Sci., 9, 57–81, https://doi.org/10.5194/os-9-57-2013, 2013.
Lellouche, J.-M., Greiner, E., Le Galloudec, O., Garric, G., Regnier, C., Drevillon, M., Benkiran, M., Testut, C.-E., Bourdalle-Badie, R., Gasparin, F., Hernandez, O., Levier, B., Drillet, Y., Remy, E., and Le Traon, P.-Y.: Recent updates to the Copernicus Marine Service global ocean monitoring and forecasting real-time
Li, A., Zhang, M., Zhu, X., Zu, Z., and Wang, H.: A research on the optimal
approach of CFSR surface flux data correction based on different surface
forcing modes, Haiyang Xuebao,
41, 51–63, https://doi.org/10.3969/j.issn.0253-4193.2019.11.006, 2019. (In Chinese with English abstract)
Li, A., Zhu, X., Zhang, Y., Ren, S., Zhang, M., Zu, Z., and Wang, H.: Recent
improvements to the physical model of the Bohai Sea, the Yellow Sea and the
East China Sea Operational Oceanography Forecasting System, Acta
Oceanol. Sin., 40, 1–17, https://doi.org/10.1007/s13131-021-1840-0, 2021.
Li, B., Cao, A., and Lv, X.: Three-dimensional numerical simulation of M2
internal tides in the Luzon Strait, Acta Oceanol. Sin., 34, 55–62,
https://doi.org/10.1007/s13131-015-0748-y, 2015.
Li, H., Song, D., Chen, X., Qian, H., Mu, L., and Song, J.: Numerical study
of M2 internal tide generation and propagation in the Luzon Strait, Acta
Oceanol. Sin., 30, 23–32, https://doi.org/10.1007/s13131-011-0144-1, 2011.
Liu, Z., Chen, X., Yu, J., Xu, D., and Sun, C.: Kuroshio intrusion into the
South China Sea with an anticyclonic eddy: evidence from underwater glider
observation, J. Oceanol. Limnol., 37, 1469–1480, https://doi.org/10.1007/s00343-019-8290-y, 2019.
Mao, Q., Shi, P., and Qi, Y.: Sea surface dynamic topography and geostrophic
current over the South China Sea from Geosat altimeter observation, Acta
Oceanol. Sin., 21, 11–16, 1999.
Marchesiello, P., Debreu, L., and Couvelard, X.: Spurious diapycnal mixing
in terrain-following coordinate models: The problem and a solution, Ocean
Model., 26, 156–169, https://doi.org/10.1016/j.ocemod.2008.09.004, 2009.
Nan, F., Xue, H., and Yu, F.: Kuroshio intrusion into the South China Sea: A
review, Prog. Oceanogr., 137, 314–333, https://doi.org/10.1016/j.pocean.2014.05.012, 2015.
Naughten, K. A., Galton-Fenzi, B. K., Meissner, K. J., England, M. H.,
Brassington, G. B., Colberg, F., Hattermann, T., and Debernard, J. B.:
Spurious sea ice formation caused by oscillatory ocean tracer advection
schemes, Ocean Model., 116, 108–117, https://doi.org/10.1016/j.ocemod.2017.06.010, 2017.
NOAA/OAR/ESRL PSL: NCEP_Reanalysis 2, NOAA/OAR/ESRL PSL [data set], Boulder, Colorado, USA, https://www.psl.noaa.gov/data/gridded/data.ncep.reanalysis2.html, last access: 3 January 2021.
Oke, P. R., Brassington, G. B., Griffin, D. A., and Schiller, A.: The
Bluelink ocean data assimilation system (BODAS), Ocean Model., 21, 46–70,
https://doi.org/10.1016/j.ocemod.2007.11.002, 2008.
Ourmières, Y., Brankart, J.-M., Berline, L., Brasseur, P., and Verron,
J.: Incremental Analysis Update Implementation into a Sequential Ocean Data
Assimilation System, J. Atmos. Ocean. Technol., 23, 1729–1744, 2006.
Qiu, B. and Chen, S.: Interannual-to-Decadal Variability in the Bifurcation
of the North Equatorial Current off the Philippines, J. Phys. Oceanogr., 40,
2525–2538, https://doi.org/10.1175/2010JPO4462.1, 2010.
Ryan, A. G., Regnier, C., Divakaran, P., Spindler, T., Mehra, A., Smith, G.
C., Davidson, F., Hernandez, F., Maksymczuk, J., and Liu, Y.: GODAE
OceanView Class 4 forecast verification framework: global ocean
inter-comparison, J. Oper. Oceanogr. [data set], 8, s98–s111,
https://doi.org/10.1080/1755876X.2015.1022330, 2015, data available at ftp://ftp.ifremer.fr/ifremer/argo/, last access: 28 January 2022.
Saha, S., Moorthi, S., Pan, H. L., Wu, X., Wang, J., Nadiga, S., Tripp, P.,
Kistler, R., Woollen, J., Behringer, D., Liu, H., Stokes, D., Grumbine, R.,
Gayno, G., Wang, J., Hou, Y. T., Chuang, H. Y., Juang, H. M. H., Sela, J.,
Iredell, M., Treadon, R., Kleist, D., Van Delst, P., Keyser, D., Derber, J.,
Ek, M., Meng, J., Wei, H., Yang, R., Lord, S., Van Den Dool, H., Kumar, A.,
Wang, W., Long, C., Chelliah, M., Xue, Y., Huang, B., Schemm, J. K.,
Ebisuzaki, W., Lin, R., Xie, P., Chen, M., Zhou, S., Higgins, W., Zou, C.
Z., Liu, Q., Chen, Y., Han, Y., Cucurull, L., Reynolds, R. W., Rutledge, G.,
and Goldberg, M.: The NCEP climate forecast system reanalysis, Bull. Amer.
Meteor. Soc., 91, 1015–1057, https://doi.org/10.1175/2010BAMS3001.1, 2010a.
Saha, S., Moorthi, S., Pan, H.-L., Wu, X., Wang, J., Nadiga, S., Tripp, P., Kistler, R., Woollen, J., Behringer, D., Liu, H., Stokes, D., Grumbine, R., Gayno, G., Wang, J., Hou, Y.-T., Chuang, H.-Y., Juang, H.-M. H., Sela, J., Iredell, M., Treadon, R., Kleist, D., Van Delst, P., Keyser, D., Derber, J., Ek, M., Meng, J., Wei, H., Yang, R., Lord, S., van den Dool, H., Kumar, A., Wang, W., Long, C., Chelliah, M., Xue, Y., Huang, B., Schemm, J.-K., Ebisuzaki, W., Lin, R., Xie, P., Chen, M., Zhou, S., Higgins, W., Zou, C.-Z., Liu, Q., Chen, Y., Han, Y., Cucurull, L., Reynolds, R. W., Rutledge, G., and Goldberg, M.: NCEP Climate Forecast System Reanalysis (CFSR) 6-hourly Products, January 1979 to December 2010, Research Data Archive at the National Center for Atmospheric Research, Computational and Information Systems Laboratory [data set], https://doi.org/10.5065/D69K487J, 2010b.
Saha, S., Moorthi, S., Wu, X., Wang, J., Nadiga, S., Tripp, P., Behringer, D., Hou, Y.-T., Chuang, H.-Y., Iredell, M., Ek, M., Meng, J., Yang, R., Mendez, M. P., van den Dool, H., Zhang, Q., Wang, W., Chen, M., and Becker, E.: NCEP Climate Forecast System Version 2 (CFSv2) 6-hourly Products, updated daily, Research Data Archive at the National Center for Atmospheric Research, Computational and Information Systems Laboratory [data set], https://doi.org/10.5065/D61C1TXF, 2011.
Saha, K., Zhao, X., Zhang, H.-m., Casey, K. S., Zhang, D., Baker-Yeboah, S., Kilpatrick, K. A., Evans, R. H., Ryan, T., and Relph, J. M.: AVHRR Pathfinder version 5.3 level 3 collated (L3C) global 4 km sea surface temperature for 1981–Present, NOAA National Centers for Environmental Information [data set], https://doi.org/10.7289/v52j68xx, 2018, data available at: http://www.ncei.noaa.gov/data/sea-surface-temperature-optimum-interpolation/v2.1/access/avhrr/, last access: 3 January 2021.
Saha, S., Moorthi, S., Wu, X., Wang, J., Nadiga, S., Tripp, P., Behringer,
D., Hou, Y.-T., Cuang, H.-Y., Iredell, M., Ek, M., Meng, J., Yang, R.,
Mendez, M. P., Dool, H. V. D., Zhang, Q., Wang, W., Chen, M., and Becker,
E.: The NCEP Climate Forecast System Version 2, J. Clim., 27, 2185–2208,
https://doi.org/10.1175/JCLI-D-12-00823.1, 2014.
Sandery, P.: Data assimilation cycle length and observation impact in mesoscale ocean forecasting, Geosci. Model Dev., 11, 4011–4019, https://doi.org/10.5194/gmd-11-4011-2018, 2018.
Shchepetkin, A. F. and McWilliams, J. C.: A method for computing horizontal
pressure-gradient force in an oceanic model with a nonaligned vertical
coordinate, J. Geophys. Res., 108, 3090, https://doi.org/10.1029/2001JC001047, 2003.
Shchepetkin, A. F. and McWilliams, J. C.: The regional oceanic modeling
system (ROMS): a split-explicit, free-surface,
topography-following-coordinate oceanic model, Ocean Model., 9, 347–404,
https://doi.org/10.1016/j.ocemod.2004.08.002, 2005.
Song, Y. and Haidvogel, D.: A Semi-implicit Ocean Circulation Model Using a
Generalized Topography-Following Coordinate System, J. Comp. Phys., 115,
228–244, https://doi.org/10.1006/jcph.1994.1189, 1994.
Taburet, G.: SL-TAC team, Quality Information Document for Sea Level TAC
DUACS Products, Copernicus Marine Environment Monitoring Service, 2.4, 2018.
Tonani, M., Balmaseda, M., Bertino, L., Blockley, E., Brassington, G. B.,
Davidson, F., Drillet, Y., Hogan, P., Kuragano, T., Lee, T., Mehra, A.,
Paranathara, F., Tanajura, C. A. S., and Wang, H.: Status and future of
global and regional ocean prediction systems, J. Oper. Oceanogr., 8,
s201–s220, https://doi.org/10.1080/1755876X.2015.1049892, 2015.
Tsujino, H., Usui, N., and Nakano, H.: Dynamics of Kuroshio path variations
in a high-resolution general circulation model, J. Geophys. Res., 111,
C11001, https://doi.org/10.1029/2005JC003118, 2006.
Usui, N., Ishizaki, S., Fujii, Y., Tsujino, H., Yasuda, T., and Kamachi, M.:
Meteorological Research Institute multivariate ocean variational estimation
(MOVE) system: Some early results, Adv. Space Res., 37, 806–822,
https://doi.org/10.1016/j.asr.2005.09.022, 2006.
Usui, N., Wakamatsu, T., Tanaka, Y., Hirose, N., Toyoda, T., Nishikawa, S.,
Fujii, Y., Takatsuki, Y., Igarashi, H., Nishikawa, H., Ishikawa, Y.,
Kuragano, T., and Kamachi, M.: Four-dimensional variational ocean
reanalysis: a 30-year high-resolution dataset in the western North Pacific
(FORA-WNP30), J. Oceanogr., 73, 205–233, https://doi.org/10.1007/s10872-016-0398-5, 2017.
Wang, J.: Global Linear Stability of the Two-Dimensional Shallow-Water
Equations: An Application of the Distributive Theorem of Roots for
Polynomials on the Unit Circle, Mon. Weather Rev., 124, 1301–1310, 1996.
Wang, Q., Zeng, L., Chen, J., He, Y., Zhou, W., and Wang, D.: The Linkage of
Kuroshio Intrusion and Mesoscale Eddy Variability in the Northern South
China Sea: Subsurface Speed Maximum, Geophys. Res. Lett., 47, e2020GL087034,
https://doi.org/10.1029/2020GL087034, 2020.
Wang, W., Wang, D., Zhou, W., Liu, Q., Yu, Y., and Li, C.: Impact of the
South China Sea Throughflow on the Pacific Low-Latitude Western Boundary
Current: A Numerical Study for Seasonal and Interannual Time Scales, Adv.
Atmos. Sci., 28, 1367–1376, 10.1007/s00376-011-0142-4, 2011.
Wei, Z., Li, S., Susanto, R. D., Wang, Y., Fan, B., Xu, T., Sulistiyo, B.,
Adi, T. R., Setiawan, A., Kuswardani, A., and Fang, G.: An overview of
10-year observation of the South China Sea branch of the Pacific to Indian
Ocean throughflow at the Karimata Strait, Acta Oceanol. Sin., 38, 1–11,
https://doi.org/10.1007/s13131-019-1410-x, 2019.
Xie, J. and Zhu, J.: Ensemble optimal interpolation schemes for assimilating
Argo profiles into a hybrid coordinate ocean model, Ocean Model.,
33, 283–298, https://doi.org/10.1016/j.ocemod.2010.03.002.
Xu, D., Zhuang, W., and Yan, Y.: Could the two anticyclonic eddies during winter 2003/2004 be reproduced and predicted in the northern South China Sea?, Ocean Sci., 15, 97–111, https://doi.org/10.5194/os-15-97-2019, 2019.
Zhang, S., Qiu, F., Zhang, J., Shen, J., and Cha, J.: Monthly variation on
the propagation and evolution of internal solitary waves in the northern
South China Sea, Cont. Shelf Res., 171, 21–29, https://doi.org/10.1016/j.csr.2018.10.014, 2018.
Zhang, Z., Tian, J., Qiu, B., Zhao, W., Chang, P., Wu, D., and Wan, X.:
Observed 3D Structure, Generation, and Dissipation of Oceanic Mesoscale
Eddies in the South China Sea, Sci. Rep., 6, 24349, https://doi.org/10.1038/srep24349, 2016.
Zhao, Z. and Alford, M. H.: Source and propagation of internal solitary
waves in the northeastern South China Sea, J. Geophys. Res., 111, 1–14,
https://doi.org/10.1029/2006JC003644, 2006.
Zheng, Q., Xie, L., Zheng, Z., and Hu, J.: Progress in Research of Mesoscale
Eddies in the South China Sea, Adv. Mar. Sci., 35, 131–158,
https://doi.org/10.3969/j.issn.1671-6647.2017.02.001, 2017.
Zhu, X.: Multi-source Ocean data Online Assimilation System (2.0), Zenodo [code], https://doi.org/10.5281/zenodo.5215783, 2021.
Zhu, X., Wang, H., Liu, G., Régnier, C., Kuang, X., Wang, D., Ren, S., Jing, Z., and Drévillon, M.: Comparison and validation of global and regional ocean forecasting systems for the South China Sea, Nat. Hazards Earth Syst. Sci., 16, 1639–1655, https://doi.org/10.5194/nhess-16-1639-2016, 2016.
Zu, Y., Sun, S., Zhao, W., Li, P., Liu, B., and Fang, Y.: Seasonal
characteristics and formation mechanism of the thermohaline structure of
mesoscale eddy in the South China Sea, Acta Oceanol. Sin., 38, 29–38,
https://doi.org/10.1007/s13131-018-1222-4, 2019.
Short summary
SCSOFS has provided daily updated marine forecasting in the South China Sea for the next 5 d since 2013. Comprehensive updates have been conducted to the configurations of SCSOFS's physical model and data assimilation scheme in order to improve its forecasting skill. The three most sensitive updates are highlighted. Scientific comparison and accuracy assessment results indicate that remarkable improvements have been achieved in SCSOFSv2 with respect to the original version SCSOFSv1.
SCSOFS has provided daily updated marine forecasting in the South China Sea for the next 5 d...
